different terms for research paper

50 Useful Academic Words & Phrases for Research

Like all good writing, writing an academic paper takes a certain level of skill to express your ideas and arguments in a way that is natural and that meets a level of academic sophistication. The terms, expressions, and phrases you use in your research paper must be of an appropriate level to be submitted to academic journals.

Therefore, authors need to know which verbs , nouns , and phrases to apply to create a paper that is not only easy to understand, but which conveys an understanding of academic conventions. Using the correct terminology and usage shows journal editors and fellow researchers that you are a competent writer and thinker, while using non-academic language might make them question your writing ability, as well as your critical reasoning skills.

What are academic words and phrases?

One way to understand what constitutes good academic writing is to read a lot of published research to find patterns of usage in different contexts. However, it may take an author countless hours of reading and might not be the most helpful advice when faced with an upcoming deadline on a manuscript draft.

Briefly, “academic” language includes terms, phrases, expressions, transitions, and sometimes symbols and abbreviations that help the pieces of an academic text fit together. When writing an academic text–whether it is a book report, annotated bibliography, research paper, research poster, lab report, research proposal, thesis, or manuscript for publication–authors must follow academic writing conventions. You can often find handy academic writing tips and guidelines by consulting the style manual of the text you are writing (i.e., APA Style , MLA Style , or Chicago Style ).

However, sometimes it can be helpful to have a list of academic words and expressions like the ones in this article to use as a “cheat sheet” for substituting the better term in a given context.

How to Choose the Best Academic Terms

You can think of writing “academically” as writing in a way that conveys one’s meaning effectively but concisely. For instance, while the term “take a look at” is a perfectly fine way to express an action in everyday English, a term like “analyze” would certainly be more suitable in most academic contexts. It takes up fewer words on the page and is used much more often in published academic papers.

You can use one handy guideline when choosing the most academic term: When faced with a choice between two different terms, use the Latinate version of the term. Here is a brief list of common verbs versus their academic counterparts:

Although this can be a useful tip to help academic authors, it can be difficult to memorize dozens of Latinate verbs. Using an AI paraphrasing tool or proofreading tool can help you instantly find more appropriate academic terms, so consider using such revision tools while you draft to improve your writing.

Top 50 Words and Phrases for Different Sections in a Research Paper

The “Latinate verb rule” is just one tool in your arsenal of academic writing, and there are many more out there. But to make the process of finding academic language a bit easier for you, we have compiled a list of 50 vital academic words and phrases, divided into specific categories and use cases, each with an explanation and contextual example.

Best Words and Phrases to use in an Introduction section

1. historically.

An adverb used to indicate a time perspective, especially when describing the background of a given topic.

2. In recent years

A temporal marker emphasizing recent developments, often used at the very beginning of your Introduction section.

3. It is widely acknowledged that

A “form phrase” indicating a broad consensus among researchers and/or the general public. Often used in the literature review section to build upon a foundation of established scientific knowledge.

4. There has been growing interest in

Highlights increasing attention to a topic and tells the reader why your study might be important to this field of research.

5. Preliminary observations indicate

Shares early insights or findings while hedging on making any definitive conclusions. Modal verbs like may , might , and could are often used with this expression.

6. This study aims to

Describes the goal of the research and is a form phrase very often used in the research objective or even the hypothesis of a research paper .

7. Despite its significance

Highlights the importance of a matter that might be overlooked. It is also frequently used in the rationale of the study section to show how your study’s aim and scope build on previous studies.

8. While numerous studies have focused on

Indicates the existing body of work on a topic while pointing to the shortcomings of certain aspects of that research. Helps focus the reader on the question, “What is missing from our knowledge of this topic?” This is often used alongside the statement of the problem in research papers.

9. The purpose of this research is

A form phrase that directly states the aim of the study.

10. The question arises (about/whether)

Poses a query or research problem statement for the reader to acknowledge.

Best Words and Phrases for Clarifying Information

11. in other words.

Introduces a synopsis or the rephrasing of a statement for clarity. This is often used in the Discussion section statement to explain the implications of the study .

12. That is to say

Provides clarification, similar to “in other words.”

13. To put it simply

Simplifies a complex idea, often for a more general readership.

14. To clarify

Specifically indicates to the reader a direct elaboration of a previous point.

15. More specifically

Narrows down a general statement from a broader one. Often used in the Discussion section to clarify the meaning of a specific result.

16. To elaborate

Expands on a point made previously.

17. In detail

Indicates a deeper dive into information.

Points out specifics. Similar meaning to “specifically” or “especially.”

19. This means that

Explains implications and/or interprets the meaning of the Results section .

20. Moreover

Expands a prior point to a broader one that shows the greater context or wider argument.

Best Words and Phrases for Giving Examples

21. for instance.

Provides a specific case that fits into the point being made.

22. As an illustration

Demonstrates a point in full or in part.

23. To illustrate

Shows a clear picture of the point being made.

24. For example

Presents a particular instance. Same meaning as “for instance.”

25. Such as

Lists specifics that comprise a broader category or assertion being made.

26. Including

Offers examples as part of a larger list.

27. Notably

Adverb highlighting an important example. Similar meaning to “especially.”

28. Especially

Adverb that emphasizes a significant instance.

29. In particular

Draws attention to a specific point.

30. To name a few

Indicates examples than previously mentioned are about to be named.

Best Words and Phrases for Comparing and Contrasting

31. however.

Introduces a contrasting idea.

32. On the other hand

Highlights an alternative view or fact.

33. Conversely

Indicates an opposing or reversed idea to the one just mentioned.

34. Similarly

Shows likeness or parallels between two ideas, objects, or situations.

35. Likewise

Indicates agreement with a previous point.

36. In contrast

Draws a distinction between two points.

37. Nevertheless

Introduces a contrasting point, despite what has been said.

38. Whereas

Compares two distinct entities or ideas.

Indicates a contrast between two points.

Signals an unexpected contrast.

Best Words and Phrases to use in a Conclusion section

41. in conclusion.

Signifies the beginning of the closing argument.

42. To sum up

Offers a brief summary.

43. In summary

Signals a concise recap.

44. Ultimately

Reflects the final or main point.

45. Overall

Gives a general concluding statement.

Indicates a resulting conclusion.

Demonstrates a logical conclusion.

48. Therefore

Connects a cause and its effect.

49. It can be concluded that

Clearly states a conclusion derived from the data.

50. Taking everything into consideration

Reflects on all the discussed points before concluding.

Edit Your Research Terms and Phrases Before Submission

Using these phrases in the proper places in your research papers can enhance the clarity, flow, and persuasiveness of your writing, especially in the Introduction section and Discussion section, which together make up the majority of your paper’s text in most academic domains.

However, it's vital to ensure each phrase is contextually appropriate to avoid redundancy or misinterpretation. As mentioned at the top of this article, the best way to do this is to 1) use an AI text editor , free AI paraphrasing tool or AI proofreading tool while you draft to enhance your writing, and 2) consult a professional proofreading service like Wordvice, which has human editors well versed in the terminology and conventions of the specific subject area of your academic documents.

For more detailed information on using AI tools to write a research paper and the best AI tools for research , check out the Wordvice AI Blog .

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Organizing Your Social Sciences Research Paper

Glossary of research terms.

• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

This glossary is intended to assist you in understanding commonly used terms and concepts when reading, interpreting, and evaluating scholarly research. Also included are common words and phrases defined within the context of how they apply to research in the social and behavioral sciences.

• Acculturation -- refers to the process of adapting to another culture, particularly in reference to blending in with the majority population [e.g., an immigrant adopting American customs]. However, acculturation also implies that both cultures add something to one another, but still remain distinct groups unto themselves.
• Accuracy -- a term used in survey research to refer to the match between the target population and the sample.
• Affective Measures -- procedures or devices used to obtain quantified descriptions of an individual's feelings, emotional states, or dispositions.
• Aggregate -- a total created from smaller units. For instance, the population of a county is an aggregate of the populations of the cities, rural areas, etc. that comprise the county. As a verb, it refers to total data from smaller units into a large unit.
• Anonymity -- a research condition in which no one, including the researcher, knows the identities of research participants.
• Baseline -- a control measurement carried out before an experimental treatment.
• Behaviorism -- school of psychological thought concerned with the observable, tangible, objective facts of behavior, rather than with subjective phenomena such as thoughts, emotions, or impulses. Contemporary behaviorism also emphasizes the study of mental states such as feelings and fantasies to the extent that they can be directly observed and measured.
• Beliefs -- ideas, doctrines, tenets, etc. that are accepted as true on grounds which are not immediately susceptible to rigorous proof.
• Benchmarking -- systematically measuring and comparing the operations and outcomes of organizations, systems, processes, etc., against agreed upon "best-in-class" frames of reference.
• Bias -- a loss of balance and accuracy in the use of research methods. It can appear in research via the sampling frame, random sampling, or non-response. It can also occur at other stages in research, such as while interviewing, in the design of questions, or in the way data are analyzed and presented. Bias means that the research findings will not be representative of, or generalizable to, a wider population.
• Case Study -- the collection and presentation of detailed information about a particular participant or small group, frequently including data derived from the subjects themselves.
• Causal Hypothesis -- a statement hypothesizing that the independent variable affects the dependent variable in some way.
• Causal Relationship -- the relationship established that shows that an independent variable, and nothing else, causes a change in a dependent variable. It also establishes how much of a change is shown in the dependent variable.
• Causality -- the relation between cause and effect.
• Central Tendency -- any way of describing or characterizing typical, average, or common values in some distribution.
• Chi-square Analysis -- a common non-parametric statistical test which compares an expected proportion or ratio to an actual proportion or ratio.
• Claim -- a statement, similar to a hypothesis, which is made in response to the research question and that is affirmed with evidence based on research.
• Classification -- ordering of related phenomena into categories, groups, or systems according to characteristics or attributes.
• Cluster Analysis -- a method of statistical analysis where data that share a common trait are grouped together. The data is collected in a way that allows the data collector to group data according to certain characteristics.
• Cohort Analysis -- group by group analytic treatment of individuals having a statistical factor in common to each group. Group members share a particular characteristic [e.g., born in a given year] or a common experience [e.g., entering a college at a given time].
• Confidentiality -- a research condition in which no one except the researcher(s) knows the identities of the participants in a study. It refers to the treatment of information that a participant has disclosed to the researcher in a relationship of trust and with the expectation that it will not be revealed to others in ways that violate the original consent agreement, unless permission is granted by the participant.
• Confirmability Objectivity -- the findings of the study could be confirmed by another person conducting the same study.
• Construct -- refers to any of the following: something that exists theoretically but is not directly observable; a concept developed [constructed] for describing relations among phenomena or for other research purposes; or, a theoretical definition in which concepts are defined in terms of other concepts. For example, intelligence cannot be directly observed or measured; it is a construct.
• Construct Validity -- seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
• Constructivism -- the idea that reality is socially constructed. It is the view that reality cannot be understood outside of the way humans interact and that the idea that knowledge is constructed, not discovered. Constructivists believe that learning is more active and self-directed than either behaviorism or cognitive theory would postulate.
• Content Analysis -- the systematic, objective, and quantitative description of the manifest or latent content of print or nonprint communications.
• Context Sensitivity -- awareness by a qualitative researcher of factors such as values and beliefs that influence cultural behaviors.
• Control Group -- the group in an experimental design that receives either no treatment or a different treatment from the experimental group. This group can thus be compared to the experimental group.
• Controlled Experiment -- an experimental design with two or more randomly selected groups [an experimental group and control group] in which the researcher controls or introduces the independent variable and measures the dependent variable at least two times [pre- and post-test measurements].
• Correlation -- a common statistical analysis, usually abbreviated as r, that measures the degree of relationship between pairs of interval variables in a sample. The range of correlation is from -1.00 to zero to +1.00. Also, a non-cause and effect relationship between two variables.
• Covariate -- a product of the correlation of two related variables times their standard deviations. Used in true experiments to measure the difference of treatment between them.
• Credibility -- a researcher's ability to demonstrate that the object of a study is accurately identified and described based on the way in which the study was conducted.
• Critical Theory -- an evaluative approach to social science research, associated with Germany's neo-Marxist “Frankfurt School,” that aims to criticize as well as analyze society, opposing the political orthodoxy of modern communism. Its goal is to promote human emancipatory forces and to expose ideas and systems that impede them.
• Data -- factual information [as measurements or statistics] used as a basis for reasoning, discussion, or calculation.
• Data Mining -- the process of analyzing data from different perspectives and summarizing it into useful information, often to discover patterns and/or systematic relationships among variables.
• Data Quality -- this is the degree to which the collected data [results of measurement or observation] meet the standards of quality to be considered valid [trustworthy] and  reliable [dependable].
• Deductive -- a form of reasoning in which conclusions are formulated about particulars from general or universal premises.
• Dependability -- being able to account for changes in the design of the study and the changing conditions surrounding what was studied.
• Dependent Variable -- a variable that varies due, at least in part, to the impact of the independent variable. In other words, its value “depends” on the value of the independent variable. For example, in the variables “gender” and “academic major,” academic major is the dependent variable, meaning that your major cannot determine whether you are male or female, but your gender might indirectly lead you to favor one major over another.
• Deviation -- the distance between the mean and a particular data point in a given distribution.
• Discourse Community -- a community of scholars and researchers in a given field who respond to and communicate to each other through published articles in the community's journals and presentations at conventions. All members of the discourse community adhere to certain conventions for the presentation of their theories and research.
• Discrete Variable -- a variable that is measured solely in whole units, such as, gender and number of siblings.
• Distribution -- the range of values of a particular variable.
• Effect Size -- the amount of change in a dependent variable that can be attributed to manipulations of the independent variable. A large effect size exists when the value of the dependent variable is strongly influenced by the independent variable. It is the mean difference on a variable between experimental and control groups divided by the standard deviation on that variable of the pooled groups or of the control group alone.
• Emancipatory Research -- research is conducted on and with people from marginalized groups or communities. It is led by a researcher or research team who is either an indigenous or external insider; is interpreted within intellectual frameworks of that group; and, is conducted largely for the purpose of empowering members of that community and improving services for them. It also engages members of the community as co-constructors or validators of knowledge.
• Empirical Research -- the process of developing systematized knowledge gained from observations that are formulated to support insights and generalizations about the phenomena being researched.
• Epistemology -- concerns knowledge construction; asks what constitutes knowledge and how knowledge is validated.
• Ethnography -- method to study groups and/or cultures over a period of time. The goal of this type of research is to comprehend the particular group/culture through immersion into the culture or group. Research is completed through various methods but, since the researcher is immersed within the group for an extended period of time, more detailed information is usually collected during the research.
• Expectancy Effect -- any unconscious or conscious cues that convey to the participant in a study how the researcher wants them to respond. Expecting someone to behave in a particular way has been shown to promote the expected behavior. Expectancy effects can be minimized by using standardized interactions with subjects, automated data-gathering methods, and double blind protocols.
• External Validity -- the extent to which the results of a study are generalizable or transferable.
• Factor Analysis -- a statistical test that explores relationships among data. The test explores which variables in a data set are most related to each other. In a carefully constructed survey, for example, factor analysis can yield information on patterns of responses, not simply data on a single response. Larger tendencies may then be interpreted, indicating behavior trends rather than simply responses to specific questions.
• Field Studies -- academic or other investigative studies undertaken in a natural setting, rather than in laboratories, classrooms, or other structured environments.
• Focus Groups -- small, roundtable discussion groups charged with examining specific topics or problems, including possible options or solutions. Focus groups usually consist of 4-12 participants, guided by moderators to keep the discussion flowing and to collect and report the results.
• Framework -- the structure and support that may be used as both the launching point and the on-going guidelines for investigating a research problem.
• Generalizability -- the extent to which research findings and conclusions conducted on a specific study to groups or situations can be applied to the population at large.
• Grey Literature -- research produced by organizations outside of commercial and academic publishing that publish materials, such as, working papers, research reports, and briefing papers.
• Grounded Theory -- practice of developing other theories that emerge from observing a group. Theories are grounded in the group's observable experiences, but researchers add their own insight into why those experiences exist.
• Group Behavior -- behaviors of a group as a whole, as well as the behavior of an individual as influenced by his or her membership in a group.
• Hypothesis -- a tentative explanation based on theory to predict a causal relationship between variables.
• Independent Variable -- the conditions of an experiment that are systematically manipulated by the researcher. A variable that is not impacted by the dependent variable, and that itself impacts the dependent variable. In the earlier example of "gender" and "academic major," (see Dependent Variable) gender is the independent variable.
• Individualism -- a theory or policy having primary regard for the liberty, rights, or independent actions of individuals.
• Inductive -- a form of reasoning in which a generalized conclusion is formulated from particular instances.
• Inductive Analysis -- a form of analysis based on inductive reasoning; a researcher using inductive analysis starts with answers, but formulates questions throughout the research process.
• Insiderness -- a concept in qualitative research that refers to the degree to which a researcher has access to and an understanding of persons, places, or things within a group or community based on being a member of that group or community.
• Internal Consistency -- the extent to which all questions or items assess the same characteristic, skill, or quality.
• Internal Validity -- the rigor with which the study was conducted [e.g., the study's design, the care taken to conduct measurements, and decisions concerning what was and was not measured]. It is also the extent to which the designers of a study have taken into account alternative explanations for any causal relationships they explore. In studies that do not explore causal relationships, only the first of these definitions should be considered when assessing internal validity.
• Life History -- a record of an event/events in a respondent's life told [written down, but increasingly audio or video recorded] by the respondent from his/her own perspective in his/her own words. A life history is different from a "research story" in that it covers a longer time span, perhaps a complete life, or a significant period in a life.
• Margin of Error -- the permittable or acceptable deviation from the target or a specific value. The allowance for slight error or miscalculation or changing circumstances in a study.
• Measurement -- process of obtaining a numerical description of the extent to which persons, organizations, or things possess specified characteristics.
• Meta-Analysis -- an analysis combining the results of several studies that address a set of related hypotheses.
• Methodology -- a theory or analysis of how research does and should proceed.
• Methods -- systematic approaches to the conduct of an operation or process. It includes steps of procedure, application of techniques, systems of reasoning or analysis, and the modes of inquiry employed by a discipline.
• Mixed-Methods -- a research approach that uses two or more methods from both the quantitative and qualitative research categories. It is also referred to as blended methods, combined methods, or methodological triangulation.
• Modeling -- the creation of a physical or computer analogy to understand a particular phenomenon. Modeling helps in estimating the relative magnitude of various factors involved in a phenomenon. A successful model can be shown to account for unexpected behavior that has been observed, to predict certain behaviors, which can then be tested experimentally, and to demonstrate that a given theory cannot account for certain phenomenon.
• Models -- representations of objects, principles, processes, or ideas often used for imitation or emulation.
• Naturalistic Observation -- observation of behaviors and events in natural settings without experimental manipulation or other forms of interference.
• Norm -- the norm in statistics is the average or usual performance. For example, students usually complete their high school graduation requirements when they are 18 years old. Even though some students graduate when they are younger or older, the norm is that any given student will graduate when he or she is 18 years old.
• Null Hypothesis -- the proposition, to be tested statistically, that the experimental intervention has "no effect," meaning that the treatment and control groups will not differ as a result of the intervention. Investigators usually hope that the data will demonstrate some effect from the intervention, thus allowing the investigator to reject the null hypothesis.
• Ontology -- a discipline of philosophy that explores the science of what is, the kinds and structures of objects, properties, events, processes, and relations in every area of reality.
• Panel Study -- a longitudinal study in which a group of individuals is interviewed at intervals over a period of time.
• Participant -- individuals whose physiological and/or behavioral characteristics and responses are the object of study in a research project.
• Peer-Review -- the process in which the author of a book, article, or other type of publication submits his or her work to experts in the field for critical evaluation, usually prior to publication. This is standard procedure in publishing scholarly research.
• Phenomenology -- a qualitative research approach concerned with understanding certain group behaviors from that group's point of view.
• Philosophy -- critical examination of the grounds for fundamental beliefs and analysis of the basic concepts, doctrines, or practices that express such beliefs.
• Phonology -- the study of the ways in which speech sounds form systems and patterns in language.
• Policy -- governing principles that serve as guidelines or rules for decision making and action in a given area.
• Policy Analysis -- systematic study of the nature, rationale, cost, impact, effectiveness, implications, etc., of existing or alternative policies, using the theories and methodologies of relevant social science disciplines.
• Population -- the target group under investigation. The population is the entire set under consideration. Samples are drawn from populations.
• Position Papers -- statements of official or organizational viewpoints, often recommending a particular course of action or response to a situation.
• Positivism -- a doctrine in the philosophy of science, positivism argues that science can only deal with observable entities known directly to experience. The positivist aims to construct general laws, or theories, which express relationships between phenomena. Observation and experiment is used to show whether the phenomena fit the theory.
• Predictive Measurement -- use of tests, inventories, or other measures to determine or estimate future events, conditions, outcomes, or trends.
• Principal Investigator -- the scientist or scholar with primary responsibility for the design and conduct of a research project.
• Probability -- the chance that a phenomenon will occur randomly. As a statistical measure, it is shown as p [the "p" factor].
• Questionnaire -- structured sets of questions on specified subjects that are used to gather information, attitudes, or opinions.
• Random Sampling -- a process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance. Random sampling can be accomplished by first numbering the population, then selecting the sample according to a table of random numbers or using a random-number computer generator. The sample is said to be random because there is no regular or discernible pattern or order. Random sample selection is used under the assumption that sufficiently large samples assigned randomly will exhibit a distribution comparable to that of the population from which the sample is drawn. The random assignment of participants increases the probability that differences observed between participant groups are the result of the experimental intervention.
• Reliability -- the degree to which a measure yields consistent results. If the measuring instrument [e.g., survey] is reliable, then administering it to similar groups would yield similar results. Reliability is a prerequisite for validity. An unreliable indicator cannot produce trustworthy results.
• Representative Sample -- sample in which the participants closely match the characteristics of the population, and thus, all segments of the population are represented in the sample. A representative sample allows results to be generalized from the sample to the population.
• Rigor -- degree to which research methods are scrupulously and meticulously carried out in order to recognize important influences occurring in an experimental study.
• Sample -- the population researched in a particular study. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferred. In studies that use inferential statistics to analyze results or which are designed to be generalizable, sample size is critical, generally the larger the number in the sample, the higher the likelihood of a representative distribution of the population.
• Sampling Error -- the degree to which the results from the sample deviate from those that would be obtained from the entire population, because of random error in the selection of respondent and the corresponding reduction in reliability.
• Saturation -- a situation in which data analysis begins to reveal repetition and redundancy and when new data tend to confirm existing findings rather than expand upon them.
• Semantics -- the relationship between symbols and meaning in a linguistic system. Also, the cuing system that connects what is written in the text to what is stored in the reader's prior knowledge.
• Social Theories -- theories about the structure, organization, and functioning of human societies.
• Sociolinguistics -- the study of language in society and, more specifically, the study of language varieties, their functions, and their speakers.
• Standard Deviation -- a measure of variation that indicates the typical distance between the scores of a distribution and the mean; it is determined by taking the square root of the average of the squared deviations in a given distribution. It can be used to indicate the proportion of data within certain ranges of scale values when the distribution conforms closely to the normal curve.
• Statistical Analysis -- application of statistical processes and theory to the compilation, presentation, discussion, and interpretation of numerical data.
• Statistical Bias -- characteristics of an experimental or sampling design, or the mathematical treatment of data, that systematically affects the results of a study so as to produce incorrect, unjustified, or inappropriate inferences or conclusions.
• Statistical Significance -- the probability that the difference between the outcomes of the control and experimental group are great enough that it is unlikely due solely to chance. The probability that the null hypothesis can be rejected at a predetermined significance level [0.05 or 0.01].
• Statistical Tests -- researchers use statistical tests to make quantitative decisions about whether a study's data indicate a significant effect from the intervention and allow the researcher to reject the null hypothesis. That is, statistical tests show whether the differences between the outcomes of the control and experimental groups are great enough to be statistically significant. If differences are found to be statistically significant, it means that the probability [likelihood] that these differences occurred solely due to chance is relatively low. Most researchers agree that a significance value of .05 or less [i.e., there is a 95% probability that the differences are real] sufficiently determines significance.
• Subcultures -- ethnic, regional, economic, or social groups exhibiting characteristic patterns of behavior sufficient to distinguish them from the larger society to which they belong.
• Testing -- the act of gathering and processing information about individuals' ability, skill, understanding, or knowledge under controlled conditions.
• Theory -- a general explanation about a specific behavior or set of events that is based on known principles and serves to organize related events in a meaningful way. A theory is not as specific as a hypothesis.
• Treatment -- the stimulus given to a dependent variable.
• Trend Samples -- method of sampling different groups of people at different points in time from the same population.
• Triangulation -- a multi-method or pluralistic approach, using different methods in order to focus on the research topic from different viewpoints and to produce a multi-faceted set of data. Also used to check the validity of findings from any one method.
• Unit of Analysis -- the basic observable entity or phenomenon being analyzed by a study and for which data are collected in the form of variables.
• Validity -- the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. A method can be reliable, consistently measuring the same thing, but not valid.
• Variable -- any characteristic or trait that can vary from one person to another [race, gender, academic major] or for one person over time [age, political beliefs].
• Weighted Scores -- scores in which the components are modified by different multipliers to reflect their relative importance.
• White Paper -- an authoritative report that often states the position or philosophy about a social, political, or other subject, or a general explanation of an architecture, framework, or product technology written by a group of researchers. A white paper seeks to contain unbiased information and analysis regarding a business or policy problem that the researchers may be facing.

Elliot, Mark, Fairweather, Ian, Olsen, Wendy Kay, and Pampaka, Maria. A Dictionary of Social Research Methods. Oxford, UK: Oxford University Press, 2016; Free Social Science Dictionary. Socialsciencedictionary.com [2008]. Glossary. Institutional Review Board. Colorado College; Glossary of Key Terms. Writing@CSU. Colorado State University; Glossary A-Z. Education.com; Glossary of Research Terms. Research Mindedness Virtual Learning Resource. Centre for Human Servive Technology. University of Southampton; Miller, Robert L. and Brewer, John D. The A-Z of Social Research: A Dictionary of Key Social Science Research Concepts London: SAGE, 2003; Jupp, Victor. The SAGE Dictionary of Social and Cultural Research Methods . London: Sage, 2006.

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Key research terms.

bias: any influence that may distort the results of a research study and lead to error; the loss of balance and accuracy in the use of research methods.

case study: presentation of data about selected settings, persons, groups or events. Data can have been gathered using variety of different research methods (e.g., questionnaire, observation, historical or literary analysis). Is chiefly descriptive and analytical, usually based on qualitative data, though statistics such as survey findings may be included.

causal relationship: relationship between variables where movements in one or more variable(s) are held to cause changes in the other (s).

coded data: data are put into groups or categories, such as age groups, and each category is given a code number. Data are usually coded for convenience, speed, and handling to enable statistical analysis. construct: a mental state that can’t be directly observed or manipulated, such as love, intelligence, hunger, feeling warm, and aggression; a concept developed (constructed) for describing relations among or between phenomena or for other research purposes.

construct validity: the degree to which the study actually measures and manipulates the elements that the researcher claims to be measuring and manipulating. If the operational definitions of the constructs are poor, the study will not have good construct validity. For example, a test claiming to measure “aggressiveness” would not have construct validity if it really measured assertiveness.

internal validity: the degree to which the study demonstrates that a particular factor caused a change in behavior. If a study lacks internal validity, the researcher may falsely believe that a factor causes an effect when it really doesn’t. Most studies involving humans do not have internal validity because they can’t rule out the possibility that some other factor may have been responsible for the effect.

controls: processes used to make uniform or constant the conditions for carrying out an investigation.

control group: in experimental research, the group or item which does not receive the treatment or intervention under investigation and is used to compare outcomes with the one that does. correlation: the extent to which two or more factors vary in relationship to one another; the extent of association between two or more variables. Correlation does not equal causation. For example, might suggest relationship between academic success and self-esteem, but cannot prove that a change in first variable causes a change in second variable. correlation coefficient: a measure of the degree of relationship between two variables. It usually lies between +1 (showing a perfect positive relationship), 0 (showing no relationship), to -1.0 (showing a perfect negative relationship). dependent variable: variable thought to be determined or influenced by others.

experiment: a special type of study (not all studies are experiments!) that allows researchers to determine the cause of an effect; usually involves randomly assigning participants to groups.

external validity: the degree to which the results of the study can be generalized to other places, people, or times.

hypothesis: a proposition which research sets out to prove or disprove: “experimental” where the hypothesis is a positive statement, or “null” where statement contains a negative.

independent variable: a variable that researcher believes precedes, influences or predicts the dependent variable.

informed consent: giving potential participants information about the study, especially in terms of factors that might lead them to refuse to be in the study, before they decide whether to participate. Institutional Review Board (IRB): a committee of at least five members--one of whom must be a nonscientist--that review proposed research and monitor approved research in an effort to protect human research participants.

literature review: often the first step in the research process, it is a review of the literature on and around the subject of inquiry. Its main purposes are to avoid duplication, to identify gaps in research and to place the researcher’s approach within the work and approaches of others.

primary/secondary sources: primary sources are original firsthand records or materials relating to an event or happening. They may include, for example, official minutes of meetings, diaries, verbatim transcripts of interviews, completed questionnaires or records of the results of experiments. Secondary sources are accounts bases upon these, which usually offer an interpretation, commentary, analysis, or restatement of the primary sources. They can include, for example, books, journal articles, and conference papers.

qualitative data: information gathered in narrative, non-numerical form (e.g., transcript of an interview). Qualitative research used for exploratory (hypothesis-generating) purposes or explaining puzzling quantitative results, while quantitative methods are used to test hypotheses.

quantitative data: information gathered in numerical form. reliability: extent to which the same result will be repeated/achieved by using the same measure.

statistical significance: tests used to estimate the likelihood that the finding in a sample is true of the population from which the sample is derived and not due to chance.

simple experiment: used to establish cause and effect, so this type often used to determine effect of treatment. Participants randomly assigned to either control group with no treatment, while the experimental group receives treatment.

validity: extent to which research findings can be said to be accurate and reliable; degree to which conclusions are justified. Internal validity is extent to which researchers can show that they have evidence for the statements they make; external validity refers to a study’s generalizability.

Reference management. Clean and simple.

What is a research paper?

A research paper is a paper that makes an argument about a topic based on research and analysis.

Any paper requiring the writer to research a particular topic is a research paper. Unlike essays, which are often based largely on opinion and are written from the author's point of view, research papers are based in fact.

A research paper requires you to form an opinion on a topic, research and gain expert knowledge on that topic, and then back up your own opinions and assertions with facts found through your thorough research.

➡️ Read more about  different types of research papers .

What is the difference between a research paper and a thesis?

A thesis is a large paper, or multi-chapter work, based on a topic relating to your field of study.

A thesis is a document students of higher education write to obtain an academic degree or qualification. Usually, it is longer than a research paper and takes multiple years to complete.

Generally associated with graduate/postgraduate studies, it is carried out under the supervision of a professor or other academic of the university.

A major difference between a research paper and a thesis is that:

• a research paper presents certain facts that have already been researched and explained by others
• a thesis starts with a certain scholarly question or statement, which then leads to further research and new findings

This means that a thesis requires the author to input original work and their own findings in a certain field, whereas the research paper can be completed with extensive research only.

➡️ Getting ready to start a research paper or thesis? Take a look at our guides on how to start a research paper or how to come up with a topic for your thesis .

Frequently Asked Questions about research papers

Take a look at this list of the top 21 Free Online Journal and Research Databases , such as ScienceOpen , Directory of Open Access Journals , ERIC , and many more.

Mason Porter, Professor at UCLA, explains in this forum post the main reasons to write a research paper:

• To create new knowledge and disseminate it.
• To teach science and how to write about it in an academic style.
• Some practical benefits: prestige, establishing credentials, requirements for grants or to help one get a future grant proposal, and so on.

Generally, people involved in the academia. Research papers are mostly written by higher education students and professional researchers.

Yes, a research paper is the same as a scientific paper. Both papers have the same purpose and format.

A major difference between a research paper and a thesis is that the former presents certain facts that have already been researched and explained by others, whereas the latter starts with a certain scholarly question or statement, which then leads to further research and new findings.

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100+ Research Vocabulary Words & Phrases

The academic community can be conservative when it comes to enforcing academic writing style , but your writing shouldn’t be so boring that people lose interest midway through the first paragraph! Given that competition is at an all-time high for academics looking to publish their papers, we know you must be anxious about what you can do to improve your publishing odds.

To be sure, your research must be sound, your paper must be structured logically, and the different manuscript sections must contain the appropriate information. But your research must also be clearly explained. Clarity obviously depends on the correct use of English, and there are many common mistakes that you should watch out for, for example when it comes to articles , prepositions , word choice , and even punctuation . But even if you are on top of your grammar and sentence structure, you can still make your writing more compelling (or more boring) by using powerful verbs and phrases (vs the same weaker ones over and over). So, how do you go about achieving the latter?

Below are a few ways to breathe life into your writing.

1. Analyze Vocabulary Using Word Clouds

Have you heard of “Wordles”? A Wordle is a visual representation of words, with the size of each word being proportional to the number of times it appears in the text it is based on. The original company website seems to have gone out of business, but there are a number of free word cloud generation sites that allow you to copy and paste your draft manuscript into a text box to quickly discover how repetitive your writing is and which verbs you might want to replace to improve your manuscript.

Seeing a visual word cloud of your work might also help you assess the key themes and points readers will glean from your paper. If the Wordle result displays words you hadn’t intended to emphasize, then that’s a sign you should revise your paper to make sure readers will focus on the right information.

As an example, below is a Wordle of our article entitled, “ How to Choose the Best title for Your Journal Manuscript .” You can see how frequently certain terms appear in that post, based on the font size of the text. The keywords, “titles,” “journal,” “research,” and “papers,” were all the intended focus of our blog post.

2. Study Language Patterns of Similarly Published Works

Study the language pattern found in the most downloaded and cited articles published by your target journal. Understanding the journal’s editorial preferences will help you write in a style that appeals to the publication’s readership.

Another way to analyze the language of a target journal’s papers is to use Wordle (see above). If you copy and paste the text of an article related to your research topic into the applet, you can discover the common phrases and terms the paper’s authors used.

For example, if you were writing a paper on  links between smoking and cancer , you might look for a recent review on the topic, preferably published by your target journal. Copy and paste the text into Wordle and examine the key phrases to see if you’ve included similar wording in your own draft. The Wordle result might look like the following, based on the example linked above.

If you are not sure yet where to publish and just want some generally good examples of descriptive verbs, analytical verbs, and reporting verbs that are commonly used in academic writing, then have a look at this list of useful phrases for research papers .

3. Use More Active and Precise Verbs

Have you heard of synonyms? Of course you have. But have you looked beyond single-word replacements and rephrased entire clauses with stronger, more vivid ones? You’ll find this task is easier to do if you use the active voice more often than the passive voice . Even if you keep your original sentence structure, you can eliminate weak verbs like “be” from your draft and choose more vivid and precise action verbs. As always, however, be careful about using only a thesaurus to identify synonyms. Make sure the substitutes fit the context in which you need a more interesting or “perfect” word. Online dictionaries such as the Merriam-Webster and the Cambridge Dictionary are good sources to check entire phrases in context in case you are unsure whether a synonym is a good match for a word you want to replace. 

To help you build a strong arsenal of commonly used phrases in academic papers, we’ve compiled a list of synonyms you might want to consider when drafting or editing your research paper . While we do not suggest that the phrases in the “Original Word/Phrase” column should be completely avoided, we do recommend interspersing these with the more dynamic terms found under “Recommended Substitutes.”

A. Describing the scope of a current project or prior research

B. outlining a topic’s background, c. describing the analytical elements of a paper, d. discussing results, e. discussing methods, f. explaining the impact of new research, wordvice writing resources.

For additional information on how to tighten your sentences (e.g., eliminate wordiness and use active voice to greater effect), you can try Wordvice’s FREE APA Citation Generator and learn more about how to proofread and edit your paper to ensure your work is free of errors.

Before submitting your manuscript to academic journals, be sure to use our free AI proofreader to catch errors in grammar, spelling, and mechanics. And use our English editing services from Wordvice, including academic editing services , cover letter editing , manuscript editing , and research paper editing services to make sure your work is up to a high academic level.

We also have a collection of other useful articles for you, for example on how to strengthen your writing style , how to avoid fillers to write more powerful sentences , and how to eliminate prepositions and avoid nominalizations . Additionally, get advice on all the other important aspects of writing a research paper on our academic resources pages .

Child Care and Early Education Research Connections

Research glossary.

The research glossary defines terms used in conducting social science and policy research, for example those describing methods, measurements, statistical procedures, and other aspects of research; the child care glossary defines terms used to describe aspects of child care and early education practice and policy.

Scientific and Scholarly Writing

• Literature Searches
• Tracking and Citing References

Parts of a Scientific & Scholarly Paper

Introduction.

• Writing Effectively
• Where to Publish?
• Capstone Resources

Different sections are needed in different types of scientific papers (lab reports, literature reviews, systematic reviews, methods papers, research papers, etc.). Projects that overlap with the social sciences or humanities may have different requirements. Generally, however, you'll need to include:

INTRODUCTION (Background)

METHODS SECTION (Materials and Methods)

What is a title

Titles have two functions: to identify the main topic or the message of the paper and to attract readers.

The title will be read by many people. Only a few will read the entire paper, therefore all words in the title should be chosen with care. Too short a title is not helpful to the potential reader. Too long a title can sometimes be even less meaningful. Remember a title is not an abstract. Neither is a title a sentence.

What makes a good title?

A good title is accurate, complete, and specific. Imagine searching for your paper in PubMed. What words would you use?

• Use the fewest possible words that describe the contents of the paper.
• Avoid waste words like "Studies on", or "Investigations on".
• Use specific terms rather than general.
• Use the same key terms in the title as the paper.
• Watch your word order and syntax.

The abstract is a miniature version of your paper. It should present the main story and a few essential details of the paper for readers who only look at the abstract and should serve as a clear preview for readers who read your whole paper. They are usually short (250 words or less).

The goal is to communicate:

•  What was done?
•  Why was it done?
•  How was it done?
•  What was found?

A good abstract is specific and selective. Try summarizing each of the sections of your paper in a sentence two. Do the abstract last, so you know exactly what you want to write.

• Use 1 or more well developed paragraphs.
• Use introduction/body/conclusion structure.
• Present purpose, results, conclusions and recommendations in that order.
• Make it understandable to a wide audience.
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13.1 Formatting a Research Paper

Learning objectives.

• Identify the major components of a research paper written using American Psychological Association (APA) style.
• Apply general APA style and formatting conventions in a research paper.

In this chapter, you will learn how to use APA style , the documentation and formatting style followed by the American Psychological Association, as well as MLA style , from the Modern Language Association. There are a few major formatting styles used in academic texts, including AMA, Chicago, and Turabian:

• AMA (American Medical Association) for medicine, health, and biological sciences
• APA (American Psychological Association) for education, psychology, and the social sciences
• Chicago—a common style used in everyday publications like magazines, newspapers, and books
• MLA (Modern Language Association) for English, literature, arts, and humanities
• Turabian—another common style designed for its universal application across all subjects and disciplines

While all the formatting and citation styles have their own use and applications, in this chapter we focus our attention on the two styles you are most likely to use in your academic studies: APA and MLA.

If you find that the rules of proper source documentation are difficult to keep straight, you are not alone. Writing a good research paper is, in and of itself, a major intellectual challenge. Having to follow detailed citation and formatting guidelines as well may seem like just one more task to add to an already-too-long list of requirements.

Following these guidelines, however, serves several important purposes. First, it signals to your readers that your paper should be taken seriously as a student’s contribution to a given academic or professional field; it is the literary equivalent of wearing a tailored suit to a job interview. Second, it shows that you respect other people’s work enough to give them proper credit for it. Finally, it helps your reader find additional materials if he or she wishes to learn more about your topic.

Furthermore, producing a letter-perfect APA-style paper need not be burdensome. Yes, it requires careful attention to detail. However, you can simplify the process if you keep these broad guidelines in mind:

• Work ahead whenever you can. Chapter 11 “Writing from Research: What Will I Learn?” includes tips for keeping track of your sources early in the research process, which will save time later on.
• Get it right the first time. Apply APA guidelines as you write, so you will not have much to correct during the editing stage. Again, putting in a little extra time early on can save time later.
• Use the resources available to you. In addition to the guidelines provided in this chapter, you may wish to consult the APA website at http://www.apa.org or the Purdue University Online Writing lab at http://owl.english.purdue.edu , which regularly updates its online style guidelines.

General Formatting Guidelines

This chapter provides detailed guidelines for using the citation and formatting conventions developed by the American Psychological Association, or APA. Writers in disciplines as diverse as astrophysics, biology, psychology, and education follow APA style. The major components of a paper written in APA style are listed in the following box.

These are the major components of an APA-style paper:

Body, which includes the following:

• Headings and, if necessary, subheadings to organize the content
• In-text citations of research sources
• References page

All these components must be saved in one document, not as separate documents.

The title page of your paper includes the following information:

• Title of the paper
• Author’s name
• Name of the institution with which the author is affiliated
• Header at the top of the page with the paper title (in capital letters) and the page number (If the title is lengthy, you may use a shortened form of it in the header.)

List the first three elements in the order given in the previous list, centered about one third of the way down from the top of the page. Use the headers and footers tool of your word-processing program to add the header, with the title text at the left and the page number in the upper-right corner. Your title page should look like the following example.

The next page of your paper provides an abstract , or brief summary of your findings. An abstract does not need to be provided in every paper, but an abstract should be used in papers that include a hypothesis. A good abstract is concise—about one hundred fifty to two hundred fifty words—and is written in an objective, impersonal style. Your writing voice will not be as apparent here as in the body of your paper. When writing the abstract, take a just-the-facts approach, and summarize your research question and your findings in a few sentences.

In Chapter 12 “Writing a Research Paper” , you read a paper written by a student named Jorge, who researched the effectiveness of low-carbohydrate diets. Read Jorge’s abstract. Note how it sums up the major ideas in his paper without going into excessive detail.

Write an abstract summarizing your paper. Briefly introduce the topic, state your findings, and sum up what conclusions you can draw from your research. Use the word count feature of your word-processing program to make sure your abstract does not exceed one hundred fifty words.

Depending on your field of study, you may sometimes write research papers that present extensive primary research, such as your own experiment or survey. In your abstract, summarize your research question and your findings, and briefly indicate how your study relates to prior research in the field.

Margins, Pagination, and Headings

APA style requirements also address specific formatting concerns, such as margins, pagination, and heading styles, within the body of the paper. Review the following APA guidelines.

Use these general guidelines to format the paper:

• Set the top, bottom, and side margins of your paper at 1 inch.
• Use double-spaced text throughout your paper.
• Use a standard font, such as Times New Roman or Arial, in a legible size (10- to 12-point).
• Use continuous pagination throughout the paper, including the title page and the references section. Page numbers appear flush right within your header.
• Section headings and subsection headings within the body of your paper use different types of formatting depending on the level of information you are presenting. Additional details from Jorge’s paper are provided.

Begin formatting the final draft of your paper according to APA guidelines. You may work with an existing document or set up a new document if you choose. Include the following:

• Your title page
• The abstract you created in Note 13.8 “Exercise 1”
• Correct headers and page numbers for your title page and abstract

APA style uses section headings to organize information, making it easy for the reader to follow the writer’s train of thought and to know immediately what major topics are covered. Depending on the length and complexity of the paper, its major sections may also be divided into subsections, sub-subsections, and so on. These smaller sections, in turn, use different heading styles to indicate different levels of information. In essence, you are using headings to create a hierarchy of information.

The following heading styles used in APA formatting are listed in order of greatest to least importance:

• Section headings use centered, boldface type. Headings use title case, with important words in the heading capitalized.
• Subsection headings use left-aligned, boldface type. Headings use title case.
• The third level uses left-aligned, indented, boldface type. Headings use a capital letter only for the first word, and they end in a period.
• The fourth level follows the same style used for the previous level, but the headings are boldfaced and italicized.
• The fifth level follows the same style used for the previous level, but the headings are italicized and not boldfaced.

Visually, the hierarchy of information is organized as indicated in Table 13.1 “Section Headings” .

Table 13.1 Section Headings

A college research paper may not use all the heading levels shown in Table 13.1 “Section Headings” , but you are likely to encounter them in academic journal articles that use APA style. For a brief paper, you may find that level 1 headings suffice. Longer or more complex papers may need level 2 headings or other lower-level headings to organize information clearly. Use your outline to craft your major section headings and determine whether any subtopics are substantial enough to require additional levels of headings.

Working with the document you developed in Note 13.11 “Exercise 2” , begin setting up the heading structure of the final draft of your research paper according to APA guidelines. Include your title and at least two to three major section headings, and follow the formatting guidelines provided above. If your major sections should be broken into subsections, add those headings as well. Use your outline to help you.

Because Jorge used only level 1 headings, his Exercise 3 would look like the following:

Citation Guidelines

In-text citations.

Throughout the body of your paper, include a citation whenever you quote or paraphrase material from your research sources. As you learned in Chapter 11 “Writing from Research: What Will I Learn?” , the purpose of citations is twofold: to give credit to others for their ideas and to allow your reader to follow up and learn more about the topic if desired. Your in-text citations provide basic information about your source; each source you cite will have a longer entry in the references section that provides more detailed information.

In-text citations must provide the name of the author or authors and the year the source was published. (When a given source does not list an individual author, you may provide the source title or the name of the organization that published the material instead.) When directly quoting a source, it is also required that you include the page number where the quote appears in your citation.

This information may be included within the sentence or in a parenthetical reference at the end of the sentence, as in these examples.

Epstein (2010) points out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Here, the writer names the source author when introducing the quote and provides the publication date in parentheses after the author’s name. The page number appears in parentheses after the closing quotation marks and before the period that ends the sentence.

Addiction researchers caution that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (Epstein, 2010, p. 137).

Here, the writer provides a parenthetical citation at the end of the sentence that includes the author’s name, the year of publication, and the page number separated by commas. Again, the parenthetical citation is placed after the closing quotation marks and before the period at the end of the sentence.

As noted in the book Junk Food, Junk Science (Epstein, 2010, p. 137), “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive.”

Here, the writer chose to mention the source title in the sentence (an optional piece of information to include) and followed the title with a parenthetical citation. Note that the parenthetical citation is placed before the comma that signals the end of the introductory phrase.

David Epstein’s book Junk Food, Junk Science (2010) pointed out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Another variation is to introduce the author and the source title in your sentence and include the publication date and page number in parentheses within the sentence or at the end of the sentence. As long as you have included the essential information, you can choose the option that works best for that particular sentence and source.

Citing a book with a single author is usually a straightforward task. Of course, your research may require that you cite many other types of sources, such as books or articles with more than one author or sources with no individual author listed. You may also need to cite sources available in both print and online and nonprint sources, such as websites and personal interviews. Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.2 “Citing and Referencing Techniques” and Section 13.3 “Creating a References Section” provide extensive guidelines for citing a variety of source types.

Writing at Work

APA is just one of several different styles with its own guidelines for documentation, formatting, and language usage. Depending on your field of interest, you may be exposed to additional styles, such as the following:

• MLA style. Determined by the Modern Languages Association and used for papers in literature, languages, and other disciplines in the humanities.
• Chicago style. Outlined in the Chicago Manual of Style and sometimes used for papers in the humanities and the sciences; many professional organizations use this style for publications as well.
• Associated Press (AP) style. Used by professional journalists.

References List

The brief citations included in the body of your paper correspond to the more detailed citations provided at the end of the paper in the references section. In-text citations provide basic information—the author’s name, the publication date, and the page number if necessary—while the references section provides more extensive bibliographical information. Again, this information allows your reader to follow up on the sources you cited and do additional reading about the topic if desired.

The specific format of entries in the list of references varies slightly for different source types, but the entries generally include the following information:

• The name(s) of the author(s) or institution that wrote the source
• The year of publication and, where applicable, the exact date of publication
• The full title of the source
• For books, the city of publication
• For articles or essays, the name of the periodical or book in which the article or essay appears
• For magazine and journal articles, the volume number, issue number, and pages where the article appears
• For sources on the web, the URL where the source is located

The references page is double spaced and lists entries in alphabetical order by the author’s last name. If an entry continues for more than one line, the second line and each subsequent line are indented five spaces. Review the following example. ( Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.3 “Creating a References Section” provides extensive guidelines for formatting reference entries for different types of sources.)

In APA style, book and article titles are formatted in sentence case, not title case. Sentence case means that only the first word is capitalized, along with any proper nouns.

Key Takeaways

• Following proper citation and formatting guidelines helps writers ensure that their work will be taken seriously, give proper credit to other authors for their work, and provide valuable information to readers.
• Working ahead and taking care to cite sources correctly the first time are ways writers can save time during the editing stage of writing a research paper.
• APA papers usually include an abstract that concisely summarizes the paper.
• APA papers use a specific headings structure to provide a clear hierarchy of information.
• In APA papers, in-text citations usually include the name(s) of the author(s) and the year of publication.
• In-text citations correspond to entries in the references section, which provide detailed bibliographical information about a source.

Writing for Success Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

How to Write a Research Paper: Parts of the Paper

• Choosing Your Topic
• Citation & Style Guides This link opens in a new window
• Critical Thinking
• Evaluating Information
• Parts of the Paper
• Writing Tips from UNC-Chapel Hill
• Librarian Contact

Parts of the Research Paper Papers should have a beginning, a middle, and an end. Your introductory paragraph should grab the reader's attention, state your main idea, and indicate how you will support it. The body of the paper should expand on what you have stated in the introduction. Finally, the conclusion restates the paper's thesis and should explain what you have learned, giving a wrap up of your main ideas.

1. The Title The title should be specific and indicate the theme of the research and what ideas it addresses. Use keywords that help explain your paper's topic to the reader. Try to avoid abbreviations and jargon. Think about keywords that people would use to search for your paper and include them in your title.

2. The Abstract The abstract is used by readers to get a quick overview of your paper. Typically, they are about 200 words in length (120 words minimum to  250 words maximum). The abstract should introduce the topic and thesis, and should provide a general statement about what you have found in your research. The abstract allows you to mention each major aspect of your topic and helps readers decide whether they want to read the rest of the paper. Because it is a summary of the entire research paper, it is often written last. 

3. The Introduction The introduction should be designed to attract the reader's attention and explain the focus of the research. You will introduce your overview of the topic,  your main points of information, and why this subject is important. You can introduce the current understanding and background information about the topic. Toward the end of the introduction, you add your thesis statement, and explain how you will provide information to support your research questions. This provides the purpose and focus for the rest of the paper.

4. Thesis Statement Most papers will have a thesis statement or main idea and supporting facts/ideas/arguments. State your main idea (something of interest or something to be proven or argued for or against) as your thesis statement, and then provide your supporting facts and arguments. A thesis statement is a declarative sentence that asserts the position a paper will be taking. It also points toward the paper's development. This statement should be both specific and arguable. Generally, the thesis statement will be placed at the end of the first paragraph of your paper. The remainder of your paper will support this thesis.

Students often learn to write a thesis as a first step in the writing process, but often, after research, a writer's viewpoint may change. Therefore a thesis statement may be one of the final steps in writing. 

Examples of Thesis Statements from Purdue OWL

5. The Literature Review The purpose of the literature review is to describe past important research and how it specifically relates to the research thesis. It should be a synthesis of the previous literature and the new idea being researched. The review should examine the major theories related to the topic to date and their contributors. It should include all relevant findings from credible sources, such as academic books and peer-reviewed journal articles. You will want  to:

• Explain how the literature helps the researcher understand the topic.
• Try to show connections and any disparities between the literature.
• Identify new ways to interpret prior research.
• Reveal any gaps that exist in the literature.

More about writing a literature review. . .

6. The Discussion ​The purpose of the discussion is to interpret and describe what you have learned from your research. Make the reader understand why your topic is important. The discussion should always demonstrate what you have learned from your readings (and viewings) and how that learning has made the topic evolve, especially from the short description of main points in the introduction.Explain any new understanding or insights you have had after reading your articles and/or books. Paragraphs should use transitioning sentences to develop how one paragraph idea leads to the next. The discussion will always connect to the introduction, your thesis statement, and the literature you reviewed, but it does not simply repeat or rearrange the introduction. You want to: 

• Demonstrate critical thinking, not just reporting back facts that you gathered.
• If possible, tell how the topic has evolved over the past and give it's implications for the future.
• Fully explain your main ideas with supporting information.
• Explain why your thesis is correct giving arguments to counter points.

7. The Conclusion A concluding paragraph is a brief summary of your main ideas and restates the paper's main thesis, giving the reader the sense that the stated goal of the paper has been accomplished. What have you learned by doing this research that you didn't know before? What conclusions have you drawn? You may also want to suggest further areas of study, improvement of research possibilities, etc. to demonstrate your critical thinking regarding your research.

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How to Research a Term Paper

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The term paper researching process

So, you wrote a great college admissions essay and were accepted at the university or college of your dreams. Now, you've been assigned your first term paper, and you don't know where to start!

The research process is an exploratory quest, a hunt for information that can be both exciting and rewarding. The word itself is derived from the French rechercher, which literally means "to investigate thoroughly." So, when embarking on writing a term paper or research paper, think of yourself as a detective. You will not only search for information but also delve into the whys and wherefores behind the subject material, seeking to provide elucidation through your term paper.

Select a topic for your term paper

Let's start at the beginning. The first step in the essay writing process is to decide on a worthy topic, choosing one that is interesting to you. Make a list of keywords—these are important words or phrases that encapsulate the essence of your topic. Good keywords will specifically describe your topic, but consider using closely related words, as well.  Use these keywords when searching print or electronic sources that you can use in your term paper.

Research your term paper topic

General-purpose reference books, such as encyclopedias and fact books, provide comprehensive summaries and suggestions for sub-topics, as well as related terminology. Although these books are not generally considered suitable sources to cite in a term paper, the bibliographies they contain can be very helpful. This initial reading may help you to narrow your interest, stimulate additional questions, and focus your research. We recommend the following general resources, as they are more global in scope:   The Oxford Companion to Politics of the World , CQ Researcher , the Political Handbook of the World, the Index to International Public Opinion, and World Opinion Update . These publications deal with particular topics, give summaries of various governments, or take other specialized approaches, which are generally considered acceptable sources to cite in a term paper.

The next step is to either narrow your topic (so you can deal with the amount of information) or to broaden it so you have enough to write about. You might have to pick a particular sub-topic and make that your area of interest, or combine certain aspects of a topic to create a narrower one. Decide the direction you want the research for your term paper to take. What are the most interesting aspects of the topic, and what do you want to learn? Be careful not to be too general. This term paper researching process will keep you from getting lost or sidetracked when searching for information.

Find suitable sources for your term paper

At this point, decide on the most likely sources of information—books, journal articles, newspapers, online databases, CD-ROM databases, interviews, etc. Dig around in the library and locate sources for your term paper. Use your library's computer access system to find books on your subject. Some topics may be so current that few, if any, books are available. If this is the case, research scholarly journals for up-to-date information and analyses. You should consult journals even for non-contemporary topics, since scholars may have unearthed new information or produced new analyses. You may also find valuable information published in the reports of a government agency, in hearings or reports of a government committee, or in the transcripts of the proceedings of a government body. The United Nations and a number of other international organizations also publish proceedings and reports.

Don't forget that when you locate the sources you want to use for your term paper, you should be trying to find answers to the questions you posed previously. Also, don't forget to make use of the reference librarian, who can help you to locate and use sources efficiently.

Get organized early! Keep track of your sources

It is very helpful to make notes about your sources on index cards or in an Excel spreadsheet . Such notes should include bibliographic information, page numbers for quotations, and source locations. This way, you can easily find the source of an idea, quote, reference, etc. Number these cards so you can link them to your term paper notes: this will make the references section of your report a snap to complete.

Remember—thoroughly peruse all the information you have gathered, making copious notes as you go. This preliminary research should answer basic factual questions, as well as interpretive ones, and should help you to refocus. Give yourself a reasonable amount of time to absorb all the information you've read.

Writing a research or term paper

In our follow-up article about writing a research paper , we explain the next steps in the term paper writing process. The article discusses your thesis statement, body of your paper, and your reference page. If you would like to learn more about essay writing, check out Scribendi's article   12 Ways to Quickly Improve Your Academic Essay Writing Skills .

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What every researcher should know about searching – clarified concepts, search advice, and an agenda to improve finding in academia

Michael gusenbauer.

1 Department of Strategic Management, Marketing and Tourism, University of Innsbruck, Innsbruck Austria

2 Chair for Strategy and Organization, Technical University of Munich, Munich Germany

Neal R. Haddaway

3 Mercator Research Institute on Global Commons and Climate Change, Berlin Germany

4 Stockholm Environmental Institute, Stockholm Sweden

5 Africa Centre for Evidence, University of Johannesburg, Johannesburg South Africa

Associated Data

Data sharing is not applicable to this article as no new data were created or analysed.

We researchers have taken searching for information for granted for far too long. The COVID‐19 pandemic shows us the boundaries of academic searching capabilities, both in terms of our know‐how and of the systems we have. With hundreds of studies published daily on COVID‐19, for example, we struggle to find, stay up‐to‐date, and synthesize information—all hampering evidence‐informed decision making. This COVID‐19 information crisis is indicative of the broader problem of information overloaded academic research. To improve our finding capabilities, we urgently need to improve how we search and the systems we use.

We respond to Klopfenstein and Dampier ( Res Syn Meth . 2020) who commented on our 2020 paper and proposed a way of improving PubMed's and Google Scholar's search functionalities. Our response puts their commentary in a larger frame and suggests how we can improve academic searching altogether. We urge that researchers need to understand that search skills require dedicated education and training. Better and more efficient searching requires an initial understanding of the different goals that define the way searching needs to be conducted. We explain the main types of searching that we academics routinely engage in; distinguishing lookup, exploratory, and systematic searching. These three types must be conducted using different search methods (heuristics) and using search systems with specific capabilities. To improve academic searching, we introduce the “Search Triangle” model emphasizing the importance of matching goals, heuristics, and systems. Further, we suggest an urgently needed agenda toward search literacy as the norm in academic research and fit‐for‐purpose search systems.

What is already known?

• To stay up‐to‐date, we researchers would need to read hundreds of research papers a day(!). Particularly, the avalanche of COVID‐19 papers exemplifies how we are chronically information overloaded.
• Evidence synthesis is more important than ever, yet we lack the knowledge and systems to effectively and efficiently identify the evidence bases for systematic reviews.

What is new?

• We claim that research discovery needs an urgent overhaul. Only with awareness of the basic concepts of academic searching, we can know how to make our search routines and systems fit‐for‐purpose.
• Our commentary clarifies these search concepts to point out the particularities of lookup, exploratory, and systematic searching. The “Search Triangle” model emphasizes that efficient and effective search only works when goals, systems, and heuristics are well matched.

Potential impact for RSM readers outside the authors' field

• Awareness for the importance of search literacy and search education is needed across disciplines.
• Better search skills not only help in research, but anywhere online.

We thank Klopfenstein and Dampier 1 for their comment on our paper and for acknowledging the need to improve both PubMed and Google Scholar with functionalities that each is currently missing. We welcome increased scrutiny of the functionality of search systems and assessing whether these are truly fit‐for‐purpose as we struggle with information overload, particularly in times of crises like the current COVID‐19 pandemic. We are also very happy to see increased research attention on the systems that we use on a day‐to‐day basis for research discovery: functionalities that have remained unquestioned by those of us who are not information specialists for too long.

Indeed, we were overwhelmed by the substantial attention given to our paper 2 (it currently has an Altmetric score of well above 300) and the positive comments we have received. This demonstrates the need for further scrutiny and improvement to academic search. It shows that researchers want to know more about the limitations of the systems they use to discover research, which limitations they must account for, and how to match their search strategies with each system. These decisions concerning the design of search strategies profoundly affect the resultant evidence that researchers identify, what they (often unknowingly) fail to identify, and what conclusions they draw based on the emergent evidence. 3

In this article, we go beyond our original article and put the work of Klopfenstein and Dampier 1 in a larger frame to discuss the kind of agenda setting needed to overhaul academic searching, and how this might be achieved by the research community.

1. SEARCHING AND BIAS IN TIME OF A GLOBAL CRISIS

The importance of effective and efficient identification of academic publications (hereafter referred to as searching ) has become particularly evident in the current COVID‐19 pandemic: This pandemic is not only a medical crisis, but also an information crisis—not because there is no information on COVID‐19, but because there is more than we can handle. Recently, a Lancet editorial called this an “infodemic” and a “major threat to public health.” 4 According to Semantic Scholar, more than 211 000 scientific articles exist to date on COVID‐19 across all disciplines a —almost all published in 2020. The National Institute of Health (NIH)'s isearch COVID‐19 Portfolio , an expert‐curated data collection, lists 60 297 medical COVID‐19 publications, whereas 79% were listed between May and August 2020 b —amounting to an average daily(!) publication rate of almost 400 publications for medicine alone. This incredible avalanche of evidence is more than any individual can process. For any particular intervention (eg, mask‐wearing), one can find a confusing and conflicting set of studies purportedly demonstrating evidence for and against (eg, face masks for the public during the COVID‐19 crisis 5 ). Thus, the way we can process and make sense of this overabundance of evidence is one of our greatest challenges the current infodemic shows us.

Currently there is overwhelming research attention trying to solve these information challenges in a diverse suite of innovative ways, each aiming to make COVID‐19‐related information readily discoverable and analyzable. On the one hand, there are dozens of new AI‐ or expert‐curated repositories: for example, NIH LitCovid , NIH isearch , OPENICPSR COVID‐19 data repository , WHO COVID‐19 database (also linking to many other repositories) , and the Center for Disease Control and Prevention (CDC) giving an overview of various repositories. On the other hand, there are new tools for visualization, access, categorization, and analysis of COVID‐19 information (eg, SciSight or CoVis ), some of them via crowdsourced idea contests (eg, Kaggle ) or hackathons organized by institutions around the globe. This host of new initiatives is important means to fight the COVID‐19 infodemic with improved information access and analysis. However, we argue that the information overload problem is exacerbated by the insufficient nature of the search systems we must use to find relevant information. If the systems and practices we have in place—to discover, analyze, and evaluate evidence—were fit‐for‐purpose, we would not need to battle COVID‐19 with context‐specific fixes that do only little in battling infodemics in all the other contexts. We advocate that fixing existing search systems and practices is at least as important as building new resources on top. This means raising researchers' awareness and understanding about the objectives of searching, along with improving search heuristics and the search systems that make the avalanche of evidence accessible. Klopfenstein and Dampier 1 provide a good example of how best practices can be adopted across platforms and how researchers across disciplines can influence search system providers in how their systems should be improved.

One of the most critical factors that can easily limit the quality of our work is the belief that how we search academically is perfectly fine. 6 , 7 It is the belief that the systems we use on a daily basis and the habits we have developed throughout our careers are adequate to find effectively and efficiently. However, searching—one of the central elements of research work—needs trained skills, careful thought, and planning. We need to understand that where and how we search greatly impacts what we find and miss, what we conclude, and what we suggest for evidence‐informed decision making. Improving academic searching helps to improve the quality of science and helps fighting so‐called infodemics. Thus, much can be gained if we improve day‐to‐day academic searching for the millions of researchers worldwide.

We argue that the COVID‐19 pandemic is an important time to consider how to improve academic searching altogether. In this text, we clarify some important concepts of academic searching that are the subject of frequent misunderstanding, we introduce the “Search Triangle”—a user‐centric search model to understand the key characteristics of academic searching, and we explore why and how we need to overhaul academic searching to better inform decision making (Box 1 ).

How we expend much effort to get around a terrible searching environment

COVID‐19 exemplifies an information crisis, with researchers building workarounds to cope with the insufficiencies of established search systems.

In theory, research on COVID‐19 could be readily identified by any user searching a database for “COVID‐19” and finding all relevant studies. However, several problems make this difficult, for example: (a) authors describe the concept using different terms; (b) many databases typically index records (and allow searches) based only on titles, abstracts, and keywords, missing potentially relevant terms in the full texts; (c) no single database catalogues all research; (d) poor search literacy in the research community means that errors or inefficiencies in searching are common; (e) paywalls restrict users' access to search facilities and the underlying research articles.

A suite of systems has been built to identify and assemble COVID‐19 relevant research to overcome these problems, making use of artificial intelligence (including machine learning), expert curation and screening for relevant information, and temporarily making resources Open Access.

These are admirable, but necessary only because accurate and efficient identification of (free‐to‐access) relevant research across comprehensive free‐to‐use databases does not exist.

2. UNDERSTANDING ACADEMIC SEARCHING—THE DIFFERENT SEARCH TYPES: LOOKUP, EXPLORATORY, SYSTEMATIC

As Klopfenstein and Dampier 1 point out, Google Scholar is by far the most commonly used resource by researchers. 8 This is not a coincidence—it allows straightforward, user‐friendly access to its vast database of research records. 9 However, Google Scholar also shows us beautifully how a system can be perfectly suited for one type of search, while failing miserably for another. On the one hand it is very capable for targeted searches aimed at finding specific research articles, 10 but has severe limitations in systematic searches (eg, a lack of transparency and reproducibility). 2 , 11 Most academics are unaware of the different types of searching that they use on a day‐to‐day basis. 12 They use the systems they know and to which they are accustomed in ways for which they were never designed. The result is substantially biased, nontransparent, and irreproducible research studies. As researchers, we must start understanding the basic types of searching we engage in and how the objectives behind each search type (why we search) should determine the search methods—that is, system choice (where we search) and search heuristics (how we search).

There is much we can learn about searching from the information retrieval and information science literature: substantial efforts have been made to determine the types of searching at various level of granularity and the capabilities required by search systems. This discipline broadly distinguishes lookup and exploratory searching as the two key search types. 13 , 14 Lookup searches—also called “known item searches” or “navigational searches”—are conducted with a clear goal in mind and “yield precise results with minimal need for result set examination and item comparison.” 14 (p. 42) Here, the search process should be swift and efficient so as not to disturb the user's workflow. However, lookup searches can also be used by researchers or decision‐makers for cherry picking. From the avalanche of studies, it is relatively easy to select evidence that supports a pre‐held belief or dogma that portrays a biased picture of reality. Sometimes, this cherry picking is deliberate; selecting whichever study provides support for an argument or decision that has already been made (ie, post hoc evidence use). And sometimes it is unintentional: when the first evidence encountered is assumed to be representative. In general, users want efficient and convenient information retrieval, particularly in lookup searches 15 , 16 —the first result that fits typically satisfies the information need. 17 However, as researchers or decision‐makers we should explore the available evidence in the least biased way or, better still, to additionally search systematically to have all available evidence for a specific topic (including the counter‐evidence to one cherry‐picked paper). Only then, we can be sure that our conclusions and decisions are sufficiently evidence‐informed.

As many topics are complex and require in‐depth understanding, and we cannot always trust anecdotal evidence (see lookup searches), we need exploratory searches to enrich our understanding. In exploratory searches, the search goal is somewhat abstract. 18 It is a desire to better understand the nature of a topic, and the path to reaching this goal is not always apparent. Exploratory searching is a process characterized by learning 19 where users aim to be exposed to a multitude of different, sometimes contradicting knowledge sources to build their mental models on a topic. Users “submit a tentative query to navigate proximal to relevant documents in the collection, then explore the environment to better understand how to exploit it, selectively seeking and passively obtaining cues about their next steps.” 20 (p. 38) The heuristics that users employ and their ultimate goals change throughout the session as they make sense of the information, linking it to and adapting their mental models iteratively. 21 A single search session might exclusively consist of lookup or exploratory searches, or might alter the two with mixed episodes of lookup (eg, fact checking, navigation) and exploratory searches (eg, discovery and learning). In exploratory searches, the search process often spans multiple sessions (ie, days, weeks, months) or media (eg, search, videos, offline conversations) where users engage with one or more systems, take notes, and save results to knowledge management systems. Users will often stop searching when they believe they have reached their goal (the information need is met) or when they conclude it cannot be reached with the resources available. 17

While both lookup and exploratory searches are established concepts in information retrieval, they do not cover systematic searches —which we claimed in our paper 2 is a distinct third search type with unique heuristics and requirements. Evidence synthesis, in the form of systematic reviews (including meta‐analyses) and systematic maps, has introduced many disciplines to the concept of systematic searches , with the goal to (a) identify all relevant records (within the resource constraints) in a (b) transparent and (c) reproducible manner. 2 None of these three systematic search goals is shared by lookup or exploratory searches. Systematic searching is similar to lookup searching in that the search goal is known, yet the level of rigor in planning and reporting and the sophistication in the search scope are unmatched making it a distinct type of search activity. One key aspect of systematic searching is that the methods used to search should be a priori and developed through careful planning, ideally involving information retrieval experts. 22

There are presently significant misunderstandings within the research community regarding what systematic searches should and should not entail. These misunderstandings have led to criticism of the systematic review method (compared to narrative reviews) which we find are unfounded—at least in view of the literature search phase that identifies the corpus of evidence for subsequent synthesis. A major criticism is that systematic reviews would not entail “hermeneutic circles” of iterative learning about a research concept, so that researchers would not include and reflect upon findings throughout the search process. 19 , 23 In practice, however, systematic searches should always be preceded by a thorough exploratory search phase, which in systematic reviews is called “scoping.” In this initial phase, the researchers use exploratory searches to familiarize themselves with the review topic: they extend their knowledge of concepts and language and define inclusion/exclusion criteria. 24 Only then do they compose a systematic search strategy that aims to identify all available, relevant records on the topic in a transparent and reproducible manner (ie, well reported in the final manuscript). We agree that, when an initial scoping phase is missing, this may limit the validity of a systematic review greatly, since key terms and concepts may have been omitted or misunderstood, even by experts. Thus, for systematic reviews it is essential that systematic searches are preceded by a thorough exploratory search phase.

It is important to note that systematic searches do not themselves entail a learning process. They should be predefined, protocol‐driven, structured means of systematically searching, and extracting all potentially relevant bibliographic records. The search area is specified by these search steps (mostly through the use of building blocks and snowballing heuristics—see Table ​ Table1) 1 ) and lays out all records for subsequent review of relevance/eligibility. In systematic searching, the “hermeneutic circle” of understanding should be well advanced (though it probably will never be finished). Thus, in systematic reviews using the building blocks heuristic (connecting concepts via Boolean operators) only the final iteration of the search string is truly systematic and must be transparently documented in detail. It is typically at this point that the researchers stop exploring for the purpose of improving the search area. While exploratory searches ( scoping ) might use the same heuristics (see Table ​ Table1), 1 ), these initial searches are iterative and incrementally improve the search area used for the systematic review. Hence, one of the main advantages of systematic reviews is that they include both an exploratory and a systematic search, upon which the subsequent synthesis is based. Unlike in narrative reviews that often rely on exploratory searching alone, the systematic search phase in systematic reviews aims to maximize comprehensiveness and full transparency and reproducibility.

Academic search types: Their goals, use cases, dominant heuristics, and key requirements to search systems

To date, systematic searching and its unique requirements have not been described by the information science literature. The influential work of Marchionini 14 that distinguishes between lookup and exploratory searching lists synthesis work as part of exploratory search and fails to capture the nature of systematic searches (as employed in systematic reviews). To help distinguishing the three search types, we define and summarize them and add associated use cases and heuristics in Table ​ Table1 1 .

3. CONDUCTING ACADEMIC SEARCHING—THE “SEARCH TRIANGLE”

We contend that good academic searching starts with users thoughtfully establishing what their search goals are: that is, what they want to know/find. Given their search goals, search‐literate users know which type of search they need to engage in and can thus then select appropriate heuristics and search systems . Whether users are search literate, that is, are able to optimally match heuristics and search systems to their (evolving) search goals, determines the effectiveness and efficiency of finding and learning. We maintain that researchers—and indeed all information seekers—should understand the following three points that span a “Search Triangle” (see Figure ​ Figure1 1 ):

• The users ' goals : what needs to be accomplished with the search task? For lookup searches, the goal is rapid and efficient identification of an artifact where the search area is already well known to users; for exploratory searches, the goal is learning about one or multiple concepts or about an evidence base; for systematic searches, the goal is the identification and extraction of all available records on an already well understood (scoped) topic.
• The appropriate heuristics : how can the search be best conducted? The user must ask which (set of) heuristics best attain the search goal. While simple lookup searches come relatively intuitively with user‐friendly search systems like Google Scholar, 17 the users' considerations of appropriate heuristics become important for effective explorative searches and particularly for systematic searches. Some of the most popular search heuristics described in information science literature (see Table ​ Table1) 1 ) are most specific first , wayfinding , snowballing (or citation chasing/chaining , pearl growing) , (post‐query) filtering , successive fraction , building blocks ( via Boolean operators) , or handsearching . 2 , 17 , 25 , 26 , 32 It is important to note that no single heuristic is associated with a single search type. Rather, the choice of appropriate heuristics depends on the particular nature of the search goal and the options at hand, given a particular search system. For example, while building blocks are primarily used in systematic searching, they might also be used in particular types or phases of exploratory searching. Snowballing, for example, is used both in exploratory and systematic searching—yet with a different level of attention to rigor, transparency, and reproducibility.
• The appropriate systems : which (set of) search system(s) best supports the required search type and the suitable search heuristics? It is important to know what can and cannot be accomplished, given the functional capabilities of a particular search system: eg, of the 28 systems analyzed in our paper 2 only half can be recommended as stand‐alone systems in systematic searches. The selection of search systems, among the dozens available, defines what users will find. The search and retrieval capabilities are defined by the implicit characteristics of the search system in terms of functionality and coverage. It cannot be emphasized enough that no single search system is like the other and that each system is more or less adequate for specific search types (lookup/exploratory/systematic) in terms of coverage and supported heuristics.

The “Search Triangle”: efficient and effective search only works when all three (search goals, search systems, and search heuristics) are matched well [Colour figure can be viewed at wileyonlinelibrary.com ]

4. IMPROVING ACADEMIC SEARCHING—SETTING AN AGENDA AND CALLS TO ACTION

To improve academic searching, we suggest an agenda that is rooted in three areas: (a) more awareness for the intricacies of academic searching; (b) better search education; and (c) pressure on search system providers to ensure their services are fit‐for‐purpose. We suggest key points that we believe the scholarly community must tackle, also jointly with institutions, publishing bodies, and search system providers.

4.1. More awareness for the intricacies of academic searching

Improving our search practice starts by creating awareness that search literacy is a crucial skill that does not come naturally through extensive computer and internet use, but needs to be trained in search education as part of research training. 33 , 34 Particularly, in the context of systematic reviews we must understand the two consecutive, yet distinct phases: exploratory searching and systematic searching. Too often, researchers skip the exploratory scoping phase and jump straight into systematic searching, while they still are (un/consciously) unsure about the meaning and language of central concepts.

Search literacy becomes increasingly needed as the number of search systems increases and the functionality they offer is diversified and continually updated, making them more or less (or not at all) suitable for specific search types. In recent years, we have seen the introduction of numerous new systems (eg, Microsoft Academic, Dimensions.ai, Meta, The Lens, Semantic Scholar) and techniques (eg, personalized or AI‐based search results) in academic search. Researchers must understand that these systems are all different and that system choice will heavily affect (or bias) what they will find. At the moment, the algorithms of so‐called semantic search systems (eg, Google Scholar or Semantic Scholar) and the precise methods of how they select and rank what is shown on the results page are unknown. However, there is evidence 6 , 35 that these opaque algorithmic decisions influence how we researchers conduct science—what we find, what we cite, how we argue, what we conclude. The academic community needs to be aware of these biases, and equip itself with the know‐how to avoid basing entire research projects (particularly systematic reviews) on potentially biased evidence bases (eg, Burivalova et al 36 ).

We currently see an alarming absence of awareness for search system choice. This is evident in the many publications that confuse search system types 37 : foremost platforms used to access databases (such as Web of Science) and the databases themselves (such as Science Citations Index Expanded). These types are confused not only by research users more generally, but also by experts in the field of Scientometrics and others, where researchers specifically research these systems. This lack of awareness illustrates how urgently we need to start understanding academic search: the search types, the heuristics, and the search systems—to find more, faster, and with less bias.

Call to action : We must raise awareness across research communities—among students, educators, journal editors, university teaching boards, and interest organizations—of the intricacies of academic searching and how it can be improved. Organizations like the Collaboration for Environmental Evidence, 38 Campbell Collaboration, 28 and Cochrane 39 can play important roles in creating awareness for the intricacies of academic search by updating their guidance to include more nuanced academic search advice. Additionally, academic journals must ensure that editors and peer‐reviewers are aware of the importance of robust search methods to encourage more rigor in academic searching (even more so as evidence synthesis become increasingly valued and prevalent). Only with this awareness, we can adequately link search goals to appropriate heuristics and systems to perform “good science”:

• It starts with the users ' goals : Raising awareness so users understand what goals they want to reach with their searching and with which (implicit) scientific standards the specific search types (lookup/exploratory/systematic) are associated.
• Search types : Raising awareness that searching is not always a quick “just Google (Scholar) it,” but in fact can be described by a “Search Triangle” that needs a matching of search goals/types with heuristics and systems (see Figure ​ Figure1 1 ).
• Search heuristics : Raising awareness that we could use better methods in searching databases and should be designing our searches around suitable heuristics that allow us meeting our diverse search goals.
• Search systems : Raising awareness that search systems are all different, not only in coverage, but also in the functions they offer and (equally important) they do not offer. It is also vital to understand that searches can be biased through the use of algorithms to adjust the order of records in search results. 40 In the context of systematic reviews, ensuring transparent and adequate reporting of which systems are searched must be a key responsibility of research authors, editors, and peer‐reviewers. Systems to support reporting of this level of detail are available (eg, PRISMA‐S 41 ) and should be adapted to all forms of research involving searching, not just systematic reviews.

4.2. Better search education: Toward search literacy as the norm

To build search literacy that enables quick choices of both heuristics and systems given an imminent information need involves more than the day‐to‐day search experience we researchers have at hand. Instead, it requires targeted search education . Such education has been shown to significantly improve search quality. 32 , 42 Without anchoring search education in research curricula, much scholarly search effort will remain wasted. 43 , 44

Call to action : we must make search literacy a priority in research education:

• What needs to be taught? Since many researchers think their current search practices and systems suffice, we need to raise awareness about problems associated with search illiteracy 45 in combination with showing better ways of searching. The teaching objective should be to improve knowledge and skills on how to effectively and efficiently find, evaluate, manage, and use information. Taught concepts should include matching: (a) user goals/search types, (b) search heuristics, and (c) search systems. Among others, this includes awareness for the importance of adequate language to describe concepts, the ability to formulate comprehensive, yet precise search strings and the skills to search the most suitable systems.
• Who teaches it? University libraries can play a key role in making emergent and established researchers and professionals search literate. 46 In times where fewer people visit physical libraries, more advice is required in the online realm. The freed‐up resources of librarians and information specialists might be used to teach new formats to students and scholars about search.
• How can it be taught? Search literacy can be taught as stand‐alone course or extend existing teaching concepts on digital literacy or information literacy, particularly also in courses on evidence‐based research. 47 , 48 , 49 As many institutions lack libraries—particularly the ones from resource‐constrained environments—education should also be freely and easily accessible to all (ie, Open Education). Perhaps this could be organized most impactfully as self‐paced online training or freely licensed teaching materials that can be used and adapted by trainers across the world.

4.3. Toward fit‐for‐purpose search systems

No two‐search systems are identical, and none is perfect. The reason for the great popularity of some systems is not because of their adequacy for each of the three search types we describe, 2 but rather because of their ease of use in day‐to‐day research practices. In the last decade, the tremendous success of Google Scholar has shown that users generally want to search intuitively, with as little effort as possible. 17

In terms of functionality, two broad types of search systems exist at present: the traditional “comprehensive‐transparent” (eg, ProQuest, PubMed, Web of Science) and the newer “efficient‐slick” (eg, Google Scholar, Semantic Scholar). The first type allows users to specify their search to the greatest detail, while the second identifies relevant results quickly. The most popular systems are efficient‐slick, while it seems the traditional systems have focused on new features rather than low latency and accessibility. The mission statements of some popular and newly created semantic systems—including Microsoft Academic, Semantic Scholar, and Meta—can be summarized with: simpler and more efficient searching , faster results . Their aim is the fast satisfaction of researchers' information needs, without detours.

While this increase in search efficiency is generally positive, it comes at a cost. We see two fundamental problems: first, in these semantic search systems it is opaque algorithms that decide about the “right” information that is shown (either absolutely or by order). We currently have neither insight, nor control over these decisions. This is particularly problematic for systematic searching, where our study has shown that all semantic search systems in our sample failed to meet the requirements. 2 Second, we must stay alert as these efficient‐slick systems aim at transforming ‘inefficient’ exploratory searching into ‘efficient’ lookup searching (eg, through presentation of pre‐selected cues). This means exploratory searching (and thus learning) might be more and more crippled toward quick, unconsciously biased lookup searching (cherry picking) that users more and more expect when engaging with online systems. 50 To be innovative as an academic it is essential to build own mental models, to connect disconnected threads that have not been connected before—by neither machine nor human. If we reduce these “hermeneutic circles” for the sake of efficiency, we must be aware of the drawbacks. It clearly makes a difference if users are efficient in finding information on for example “the capital of Kiribati” or to which president to vote in the next election. While the first should be efficient (lookup), the latter should largely remain exploratory where users are presented with a balanced information diet. We must be careful and stay alert with systems that give us readymade answers. We must question the algorithms (AI, machine learning) and behavioral data that are used to create relevance rankings and thereby determine what researchers get to see and what not. 6 Unfortunately, it seems as if the greatest level of effort of many search systems does not go into what researchers need to accomplish in all their search tasks, but rather in making users satisfied (and not smarter) sooner.

We researchers need the best of both worlds to ensure the best research outcomes: we need efficient‐slick and comprehensive‐transparent. We claim that, at present, systems could do much more in different areas than fine‐tuning for the sake of efficient lookup searching—particularly in the realm of evidence synthesis.

Call to action :

• Greater transparency : Search functionalities – that is, what can(not) be done with a search system (see our paper 2 for details of how this can be quantified) need to become transparent. This can only be done through an independent assessment of the claims of search system providers—our study, for example, has shown that one out of four systems promoted the functioning of search options (ie, Boolean search) that we found was flawed. 2 Additionally, we need clarity in the algorithms that semantic search systems use to fine‐tune their search results to reflect on how this impacts research work. With transparency, users can make informed choices on which systems to choose and systems can benchmark to compete for users, all driving a healthy competition toward better options of search facilities.
• Toward fit‐for‐purpose—matching requirements with technical possibilities : Some of the limitations we academics are confronted with when using search systems exist because of a lack of communication between the technical (what is possible) and the applied (what is needed). We believe the tools and features of search systems would greatly benefit from effective guidance and feedback from the research community (besides the user testing, etc. they are already doing). By establishing clear rules (similar to what systematic search needs to fulfill), we can help to direct the improvement of search systems, and thereby improving access to future‐proof search functionalities. Here we need to involve information technology research methods that have a long history in investigating the performance of particular search features or technologies (eg, reinforcement learning, 51 interactive intent modeling, 52 query expansion 53 ). We do not need to reinvent the wheel, yet we need to improve communication between library science/evidence‐based research methodologists (the applied) and information technology research, and importantly: the search systems we use on a daily basis (the technical). Klopfenstein and Dampier 1 demonstrate that: first, there is much room for improvement of search system workflows, features, and supported heuristics. Second, cross‐database integration might make sense to combine strengths of different databases (the coverage of Google Scholar and the specialized features of PubMed). Third, transparent comparison of features across search systems can be key to improve the systems we have. To improve our systems, we need an understanding of the exact requirements systems need to have for specific search types. The academic community should rally around these definitions and search types and demand clarity on which systems are best suited for which type of searching.
• Organize change : To see real improvements in academic searching, we must coordinate around the issue of fit‐for‐purpose research discovery. Without organized pressure this will remain a top‐down decision process, where search organizations continue deciding on what systems we use without hearing the requirements of the academic community. The popular example is Google Scholar that has refrained from improving transparency despite the many calls from, for example, the Scientometrics community in recent years. 9 , 11 , 54 , 55 COVID‐19 has shown us that positive change is possible if the pressure and a sense of urgency is great enough: for example, search systems and publishing houses have met criticism of impeding efficient, Open Science by temporarily making COVID‐19 literature Open Access. 56 Thus, we need to decide how to organize the academic community to put pressure on search system providers to design their systems in such a way that supports the three different types of searching. Such demands for improvements are warranted and should be heard particularly by the systems we are (collectively) paying for through subscription fees. As a consequence, a great amount of effort (and thereby public money) could be saved if deliberately imposed barriers (such as view and download limits, paywall barriers, or data access restrictions) were to be removed and search functionalities improved.

5. CONCLUSION

The tremendous thirst for information on COVID‐19 by policy makers, managers, and the general public has triggered an avalanche of research. While this ever‐growing evidence base shows the academic system's capabilities to produce evidence rapidly and on tremendous scale, it has also triggered a COVID‐19 infodemic. The information overloaded researchers found across subjects and disciplines highlight the vital need to improve research discovery. Newly developed COVID‐19‐specific tools and repositories are certainly helpful, yet we also must carefully evaluate what these new technologies promise and why current systems are not already adequate. To fight the COVID‐19 infodemic—and in fact all infodemics—we argue it is essential to foremost fix how we search for scholarly evidence on a daily basis. This not only has the potential to improve search literacy across academic disciplines, but may also have spillover effects to a broader audience by educating students, organizations, and institutions.

Currently, we are at an exciting point in the development of informatics: an avalanche of research publications is being catalogued more comprehensively by an expanding suite of different bibliographic databases and research platforms (interesting developments include Dimensions.ai and The Lens). Intelligent research discovery systems make it easier than ever to identify research that is relevant to us. 9 However, it has been shown how relevance rankings direct science, a phenomenon that is aggravated with new the technologies of artificial intelligence and machine learning that introduce black‐box relevance rankings and auto‐suggestions to the daily scientific enterprise of millions of scholars. Before we have fully understood the cost of such efficient systems, we need to be cautious for how we use them. Without full understanding of the different types of searching and their requirements, users of search systems are increasingly at risk of identifying a biased or unrepresentative set of search results. 6 We must improve our understanding of the intricacies of searching and ensure search systems are specifically designed to tackle all modes of searching: only then can we conduct research with a more balanced information diet and make sure the evidence bases on which decisions are based are fit‐for‐purpose.

We currently see the greatest search issues in systematic searching : both in terms of the inadequate systems we have at hand and the uneducated researchers that use them. If the available search systems were specifically tailored to the needs of search‐literate researchers, the evidence we could produce would be of significantly greater validity and at significantly lower cost. Facilitating and thus accelerating the creation of systematic reviews could particularly help in times of crises—such as we experience today with COVID‐19.

We hope the clarification of academic search concepts, the advice in form of the “Search Triangle” model and our calls to action will help improving academic search. We hope our work informs decision making in academic searching and might prove useful in structuring and conducting search education toward search literacy as a methodical skill every academic exhibits and cherishes.

CONFLICT OF INTEREST

The author reported no conflict of interest.

a Searching for “COVID‐19,” a suggested keyword by Semantic Scholar ( https://www.semanticscholar.org/search?q=COVID-19&sort=year ), accessed on 1 September 2020.

b Isearch was accessed with a blank query to access all records on the database. ( https://icite.od.nih.gov/covid19/search/#search:searchId=5f4dff240e329a34eac4e89f ), 60 297 records as of 3 August 2020, 47 514 between 1 May and 31 August 2020, accessed on 1 September 2020.

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Research Paper or Term Paper: What’s the Difference?

Research papers and term papers are common assignments for students in a variety of academic disciplines, yet they can often be difficult to distinguish from one another. This article seeks to provide insight into the differences between research papers and term papers while exploring their purpose, structure, content, referencing styles, citation formats and more. It further examines how research paper topics are selected and outlines a process for selecting an appropriate topic if one is given by instructors or peers. In addition, it explains how proper use of resources enhances quality writing within both types of documents. Ultimately this article will aid readers in better understanding the distinctions between these two academic tasks so that they may produce higher-quality results with confidence.

I. Introduction

Ii. definition of a research paper, iii. definition of a term paper, iv. similarities between research and term papers, v. differences between research and term papers, vi. benefits of writing each type of paper, vii conclusion.

The Key Difference: Research Paper vs Term Paper Writing an academic paper can be daunting for some. It involves extensive research, brainstorming ideas and organizing the information you have gathered. One of the most important decisions a student has to make when writing a paper is whether it should be written as a research or term paper. Although these two types of papers share similarities, they also contain key differences which must be taken into account in order to deliver an excellent piece of work tailored towards specific requirements and objectives.

A research paper aims at investigating scientific topics by collecting evidence through conducting experiments and analysis. A typical format includes introduction, literature review, methods section (which could include data collection & sampling procedures), results with interpretation followed by discussion and conclusion sections.

• The purpose is typically exploratory – uncovering what researchers already know about the topic
• Content is usually backed up with solid references from reliable sources such as journals.

. In comparison to this ,a term paper does not require any experimentation but instead relies on researching already existing knowledge regarding its subject matter.. As opposed to simply reporting on findings like in case of a research project; here students are required to express their opinion based on facts presented throughout their argumentation. Common elements often found within term papers are abstracts, introductions, problem/purpose statements along with relevant conclusions detailing how your ideas fit together in terms of answering initial question(s).

A Comprehensive Understanding The research paper is a comprehensive document that not only contains various pieces of evidence to support its claims, but also develops and presents an argument based on the available data. It requires considerable effort to collect all pertinent information related to the subject under investigation, analyze it in order to find meaningful patterns or connections among them, and finally synthesize these findings into a logical structure which demonstrates your conclusion about the topic.

When compared with a term paper, one major difference lies within their scope; whereas a research paper may be much longer than 10-15 pages required for most term papers due to its broader nature and complexity in presenting arguments from multiple sources. Moreover, while writing this type of academic work involves extensive background study in scholarly resources such as books and journals covering your field of interest as well as interpreting primary sources like interviews or surveys you have conducted yourself if necessary. In addition, given its strict formality with regards referencing style throughout the body text following APA guidelines for example will need careful attention during proofreading at each stage when producing this kind of written assignment.

• Research Paper:

Thorough analysis based on existing literature along with primary source material where applicable over an extended period resulting in an essay that clearly supports original ideas related to specific theme.

• Term Paper:

More limited amountof time generally restricted around certain parameters set by lecturer leading towards concisely summarizing facts obtained through study already covered within module without necessarily providing individual opinion regarding matter investigated

A term paper is a lengthy academic document that demonstrates the student’s research and writing skills. It requires extensive analysis of available information, thorough study of relevant sources, and meaningful arguments that are backed up by evidence-based facts. In contrast to a research paper , which is typically longer in length and more complex in scope, a term paper centers around an argument or issue related to its assigned topic rather than simply describing what has been previously established on said subject.

When preparing their term papers, students must take into account not only the format requirements but also any expectations set forth by their professors regarding content quality. This means taking great care when selecting sources—credible journals published by well-known publishing houses should be given precedence over online articles or blog posts written without much editorial oversight—and researching as deeply as possible into the assigned area so as to provide readers with new insights or perspectives on the discussed topics. Moreover, it is essential for students’ work to include fresh points of view accompanied with logical deductions based on critical thinking and sound reasoning throughout; anything less would weaken one’s argument instead of reinforcing it.

Research papers and term papers are quite similar, as they both require the student to do in-depth research into a subject. They share many characteristics, although there are distinct differences between them.

• Both types of academic writing involve researching and summarizing facts from credible sources.
• They also rely heavily on analyzing existing data or theories about a particular topic.

Though both research papers and term papers are commonly assigned writing tasks for college students, the two projects have distinct characteristics that set them apart. Here we will explore some of the differences between these assignments.

• Scope: Research papers typically require a much wider scope of investigation than term papers as they delve into topics more deeply and aim to uncover new knowledge or innovative solutions rather than just summarizing existing materials. Term paper assignments tend to cover information in greater depth but within a narrower range of source material.
• Goals: While research paper objectives may be quite varied depending on the topic, their ultimate purpose is generally to contribute something original to an area of study or share significant findings about it. On the other hand, though also subject-specific, term paper goals usually include proving mastery over core concepts by presenting ideas from various sources such as class notes and readings with cogency.

Different Writing for Different Purposes While all forms of writing can be beneficial in some way, each type has its own set of advantages. When it comes to research papers and term papers, here are some great benefits that can come from tackling these assignments:

• Research Papers : These more lengthy projects give you the opportunity to delve deeper into a subject than a shorter assignment would allow. You’ll have time to read multiple sources, conduct interviews if necessary, and look at different points of view before developing your thesis statement and proving your argument with evidence.
• Term Papers : A good term paper will help summarize what you’ve learned during the semester or course by bringing together important concepts discussed throughout class lectures or discussions. It is an excellent chance for professors to assess how much information their students actually retained.

In this research paper, the differences between a research paper and a term paper have been highlighted. It has been demonstrated that while both of these pieces of written work can be effective tools for understanding an academic subject in depth, they are actually quite different from one another.

• Research papers , as the name suggests, involve extensive research on a particular topic. The goal is to explore every aspect of the chosen theme before providing your own thoughtful conclusions about it.
• Term papers ,on the other hand, often require students to focus more narrowly on studying existing theories or information presented by teachers during class time. Generally speaking, less independent research is involved when writing term papers than with researching and drafting full-length research projects.

The content of each type should therefore differ accordingly – where there may be multiple topics covered within a single research project due to its wide scope; such breadth would not normally be expected in shorter assignments like term papers which will usually address only one area of study at most. Ultimately then, depending upon their purpose and respective requirements , these two types remain distinct entities worthy of comparison yet also easily differentiated .

In conclusion, it is clear that research papers and term papers are two distinct types of assignments. Research papers focus on a specific topic or subject and require the author to conduct their own research and analysis in order to present an argument with evidence to support it. Term papers generally cover course material from a particular semester or quarter, often making use of existing literature rather than requiring original content from the student. Understanding the differences between these forms of writing can help students better prepare for each assignment they undertake while increasing their overall academic performance.

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Term Paper – Format, Examples and Writing Guide

Table of Contents

Definition:

Term paper is a type of academic writing assignment that is typically assigned to students at the end of a semester or term. It is usually a research-based paper that is meant to demonstrate the student’s understanding of a particular topic, as well as their ability to analyze and synthesize information from various sources.

Term papers are usually longer than other types of academic writing assignments and can range anywhere from 5 to 20 pages or more, depending on the level of study and the specific requirements of the assignment. They often require extensive research and the use of a variety of sources, including books, articles, and other academic publications.

Term Paper Format

The format of a term paper may vary depending on the specific requirements of your professor or institution. However, a typical term paper usually consists of the following sections:

• Title page: This should include the title of your paper, your name, the course name and number, your instructor’s name, and the date.
• Abstract : This is a brief summary of your paper, usually no more than 250 words. It should provide an overview of your topic, the research question or hypothesis, your methodology, and your main findings or conclusions.
• Introduction : This section should introduce your topic and provide background information on the subject. You should also state your research question or hypothesis and explain the importance of your research.
• Literature review : This section should review the existing literature on your topic. You should summarize the key findings and arguments made by other scholars and identify any gaps in the literature that your research aims to address.
• Methodology: This section should describe the methods you used to collect and analyze your data. You should explain your research design, sampling strategy, data collection methods, and data analysis techniques.
• Results : This section should present your findings. You can use tables, graphs, and charts to illustrate your data.
• Discussion : This section should interpret your findings and explain what they mean in relation to your research question or hypothesis. You should also discuss any limitations of your study and suggest areas for future research.
• Conclusion : This section should summarize your main findings and conclusions. You should also restate the importance of your research and its implications for the field.
• References : This section should list all the sources you cited in your paper using a specific citation style (e.g., APA, MLA, Chicago).
• Appendices : This section should include any additional materials that are relevant to your study but not essential to your main argument (e.g., survey questions, interview transcripts).

Structure of Term Paper

Here’s an example structure for a term paper:

I. Introduction

A. Background information on the topic

B. Thesis statement

II. Literature Review

A. Overview of current literature on the topic

B. Discussion of key themes and findings from literature

C. Identification of gaps in current literature

III. Methodology

A. Description of research design

B. Discussion of data collection methods

C. Explanation of data analysis techniques

IV. Results

A. Presentation of findings

B. Analysis and interpretation of results

C. Comparison of results with previous studies

V. Discussion

A. Summary of key findings

B. Explanation of how results address the research questions

C. Implications of results for the field

VI. Conclusion

A. Recap of key points

B. Significance of findings

C. Future directions for research

VII. References

A. List of sources cited in the paper

How to Write Term Paper

Here are some steps to help you write a term paper:

• Choose a topic: Choose a topic that interests you and is relevant to your course. If your professor has assigned a topic, make sure you understand it and clarify any doubts before you start.
• Research : Conduct research on your topic by gathering information from various sources such as books, academic journals, and online resources. Take notes and organize your information systematically.
• Create an outline : Create an outline of your term paper by arranging your ideas and information in a logical sequence. Your outline should include an introduction, body paragraphs, and a conclusion.
• Write a thesis statement: Write a clear and concise thesis statement that states the main idea of your paper. Your thesis statement should be included in your introduction.
• Write the introduction: The introduction should grab the reader’s attention, provide background information on your topic, and introduce your thesis statement.
• Write the body : The body of your paper should provide supporting evidence for your thesis statement. Use your research to provide details and examples to support your argument. Make sure to organize your ideas logically and use transition words to connect paragraphs.
• Write the conclusion : The conclusion should summarize your main points and restate your thesis statement. Avoid introducing new information in the conclusion.
• Edit and proofread: Edit and proofread your term paper carefully to ensure that it is free of errors and flows smoothly. Check for grammar, spelling, and punctuation errors.
• Format and cite your sources: Follow the formatting guidelines provided by your professor and cite your sources properly using the appropriate citation style.
• Submit your paper : Submit your paper on time and according to the instructions provided by your professor.

Term Paper Example

Here’s an example of a term paper:

Title : The Role of Artificial Intelligence in Cybersecurity

As the world becomes more digitally interconnected, cybersecurity threats are increasing in frequency and sophistication. Traditional security measures are no longer enough to protect against these threats. This paper explores the role of artificial intelligence (AI) in cybersecurity, including how AI can be used to detect and respond to threats in real-time, the challenges of implementing AI in cybersecurity, and the potential ethical implications of AI-powered security systems. The paper concludes with recommendations for organizations looking to integrate AI into their cybersecurity strategies.

Introduction :

The increasing number of cybersecurity threats in recent years has led to a growing interest in the potential of artificial intelligence (AI) to improve cybersecurity. AI has the ability to analyze vast amounts of data and identify patterns and anomalies that may indicate a security breach. Additionally, AI can automate responses to threats, allowing for faster and more effective mitigation of security incidents. However, there are also challenges associated with implementing AI in cybersecurity, such as the need for large amounts of high-quality data, the potential for AI systems to make mistakes, and the ethical considerations surrounding the use of AI in security.

Literature Review:

This section of the paper reviews existing research on the use of AI in cybersecurity. It begins by discussing the types of AI techniques used in cybersecurity, including machine learning, natural language processing, and neural networks. The literature review then explores the advantages of using AI in cybersecurity, such as its ability to detect previously unknown threats and its potential to reduce the workload of security analysts. However, the review also highlights some of the challenges associated with implementing AI in cybersecurity, such as the need for high-quality training data and the potential for AI systems to be fooled by sophisticated attacks.

Methodology :

To better understand the challenges and opportunities associated with using AI in cybersecurity, this paper conducted a survey of cybersecurity professionals working in a variety of industries. The survey included questions about the types of AI techniques used in their organizations, the challenges they faced when implementing AI in cybersecurity, and their perceptions of the ethical implications of using AI in security.

The results of the survey showed that while many organizations are interested in using AI in cybersecurity, they face several challenges when implementing these systems. These challenges include the need for high-quality training data, the potential for AI systems to be fooled by sophisticated attacks, and the difficulty of integrating AI with existing security systems. Additionally, many respondents expressed concerns about the ethical implications of using AI in security, such as the potential for AI to be biased or to make decisions that are harmful to individuals or society as a whole.

Discussion :

Based on the results of the survey and the existing literature, this paper discusses the potential benefits and risks of using AI in cybersecurity. It also provides recommendations for organizations looking to integrate AI into their security strategies, such as the need to prioritize data quality and to ensure that AI systems are transparent and accountable.

Conclusion :

While there are challenges associated with implementing AI in cybersecurity, the potential benefits of using these systems are significant. AI can help organizations detect and respond to threats more quickly and effectively, reducing the risk of security breaches. However, it is important for organizations to be aware of the potential ethical implications of using AI in security and to take steps to ensure that these systems are transparent and accountable.

References:

• Alkhaldi, S., Al-Daraiseh, A., & Lutfiyya, H. (2019). A Survey on Artificial Intelligence Techniques in Cyber Security. Journal of Information Security, 10(03), 191-207.
• Gartner. (2019). Gartner Top 10 Strategic Technology Trends for 2020. Retrieved from https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2020/
• Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80-89.
• Lipton, Z. C. (2018). The mythos of model interpretability. arXiv preprint arXiv:1606.03490.
• Schneier, B. (2019). Click Here to Kill Everybody: Security and Survival in a Hyper-Connected World. WW Norton & Company.
• Wahab, M. A., Rahman, M. S., & Islam, M. R. (2020). A Survey on AI Techniques in Cybersecurity. International Journal of Scientific & Engineering Research, 11(2), 22-27.

When to Write Term Paper

A term paper is usually a lengthy research paper that is assigned to students at the end of a term or semester. There are several situations when writing a term paper may be required, including:

• As a course requirement: In most cases, a term paper is required as part of the coursework for a particular course. It may be assigned by the instructor as a way of assessing the student’s understanding of the course material.
• To explore a specific topic : A term paper can be an excellent opportunity for students to explore a specific topic of interest in-depth. It allows them to conduct extensive research on the topic and develop their understanding of it.
• To develop critical thinking skills : Writing a term paper requires students to engage in critical thinking and analysis. It helps them to develop their ability to evaluate and interpret information, as well as to present their ideas in a clear and coherent manner.
• To prepare for future academic or professional pursuits: Writing a term paper can be an excellent way for students to prepare for future academic or professional pursuits. It can help them to develop the research and writing skills necessary for success in higher education or in a professional career.

Purpose of Term Paper

The main purposes of a term paper are:

• Demonstrate mastery of a subject: A term paper provides an opportunity for students to showcase their knowledge and understanding of a particular subject. It requires students to research and analyze the topic, and then present their findings in a clear and organized manner.
• Develop critical thinking skills: Writing a term paper requires students to think critically about their subject matter, analyzing various sources and viewpoints, and evaluating evidence to support their arguments.
• Improve writing skills : Writing a term paper helps students improve their writing skills, including organization, clarity, and coherence. It also requires them to follow specific formatting and citation guidelines, which can be valuable skills for future academic and professional endeavors.
• Contribute to academic discourse : A well-written term paper can contribute to academic discourse by presenting new insights, ideas, and arguments that add to the existing body of knowledge on a particular topic.
• Prepare for future research : Writing a term paper can help prepare students for future research, by teaching them how to conduct a literature review, evaluate sources, and formulate research questions and hypotheses. It can also help them develop research skills that they can apply in future academic or professional endeavors.

Advantages of Term Paper

There are several advantages of writing a term paper, including:

• In-depth exploration: Writing a term paper allows you to delve deeper into a specific topic, allowing you to gain a more comprehensive understanding of the subject matter.
• Improved writing skills: Writing a term paper involves extensive research, critical thinking, and the organization of ideas into a cohesive written document. As a result, writing a term paper can improve your writing skills significantly.
• Demonstration of knowledge: A well-written term paper demonstrates your knowledge and understanding of the subject matter, which can be beneficial for academic or professional purposes.
• Development of research skills : Writing a term paper requires conducting thorough research, analyzing data, and synthesizing information from various sources. This process can help you develop essential research skills that can be applied in many other areas.
• Enhancement of critical thinking : Writing a term paper encourages you to think critically, evaluate information, and develop well-supported arguments. These skills can be useful in many areas of life, including personal and professional decision-making.
• Preparation for further academic work : Writing a term paper is excellent preparation for more extensive academic projects, such as a thesis or dissertation.

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How to Write a Research Paper Introduction (with Examples)

The research paper introduction section, along with the Title and Abstract, can be considered the face of any research paper. The following article is intended to guide you in organizing and writing the research paper introduction for a quality academic article or dissertation.

The research paper introduction aims to present the topic to the reader. A study will only be accepted for publishing if you can ascertain that the available literature cannot answer your research question. So it is important to ensure that you have read important studies on that particular topic, especially those within the last five to ten years, and that they are properly referenced in this section. 1 What should be included in the research paper introduction is decided by what you want to tell readers about the reason behind the research and how you plan to fill the knowledge gap. The best research paper introduction provides a systemic review of existing work and demonstrates additional work that needs to be done. It needs to be brief, captivating, and well-referenced; a well-drafted research paper introduction will help the researcher win half the battle.

The introduction for a research paper is where you set up your topic and approach for the reader. It has several key goals:

• Present your research topic
• Capture reader interest
• Summarize existing research
• Position your own approach
• Define your specific research problem and problem statement
• Highlight the novelty and contributions of the study
• Give an overview of the paper’s structure

The research paper introduction can vary in size and structure depending on whether your paper presents the results of original empirical research or is a review paper. Some research paper introduction examples are only half a page while others are a few pages long. In many cases, the introduction will be shorter than all of the other sections of your paper; its length depends on the size of your paper as a whole.

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What is the introduction for a research paper, why is the introduction important in a research paper, craft a compelling introduction section with paperpal. try now, 1. introduce the research topic:, 2. determine a research niche:, 3. place your research within the research niche:, craft accurate research paper introductions with paperpal. start writing now, frequently asked questions on research paper introduction, key points to remember.

The introduction in a research paper is placed at the beginning to guide the reader from a broad subject area to the specific topic that your research addresses. They present the following information to the reader

• Scope: The topic covered in the research paper
• Context: Background of your topic
• Importance: Why your research matters in that particular area of research and the industry problem that can be targeted

The research paper introduction conveys a lot of information and can be considered an essential roadmap for the rest of your paper. A good introduction for a research paper is important for the following reasons:

• It stimulates your reader’s interest: A good introduction section can make your readers want to read your paper by capturing their interest. It informs the reader what they are going to learn and helps determine if the topic is of interest to them.
• It helps the reader understand the research background: Without a clear introduction, your readers may feel confused and even struggle when reading your paper. A good research paper introduction will prepare them for the in-depth research to come. It provides you the opportunity to engage with the readers and demonstrate your knowledge and authority on the specific topic.
• It explains why your research paper is worth reading: Your introduction can convey a lot of information to your readers. It introduces the topic, why the topic is important, and how you plan to proceed with your research.
• It helps guide the reader through the rest of the paper: The research paper introduction gives the reader a sense of the nature of the information that will support your arguments and the general organization of the paragraphs that will follow. It offers an overview of what to expect when reading the main body of your paper.

What are the parts of introduction in the research?

A good research paper introduction section should comprise three main elements: 2

• What is known: This sets the stage for your research. It informs the readers of what is known on the subject.
• What is lacking: This is aimed at justifying the reason for carrying out your research. This could involve investigating a new concept or method or building upon previous research.
• What you aim to do: This part briefly states the objectives of your research and its major contributions. Your detailed hypothesis will also form a part of this section.

How to write a research paper introduction?

The first step in writing the research paper introduction is to inform the reader what your topic is and why it’s interesting or important. This is generally accomplished with a strong opening statement. The second step involves establishing the kinds of research that have been done and ending with limitations or gaps in the research that you intend to address. Finally, the research paper introduction clarifies how your own research fits in and what problem it addresses. If your research involved testing hypotheses, these should be stated along with your research question. The hypothesis should be presented in the past tense since it will have been tested by the time you are writing the research paper introduction.

The following key points, with examples, can guide you when writing the research paper introduction section:

• Highlight the importance of the research field or topic
• Describe the background of the topic
• Present an overview of current research on the topic

Example: The inclusion of experiential and competency-based learning has benefitted electronics engineering education. Industry partnerships provide an excellent alternative for students wanting to engage in solving real-world challenges. Industry-academia participation has grown in recent years due to the need for skilled engineers with practical training and specialized expertise. However, from the educational perspective, many activities are needed to incorporate sustainable development goals into the university curricula and consolidate learning innovation in universities.

• Reveal a gap in existing research or oppose an existing assumption
• Formulate the research question

Example: There have been plausible efforts to integrate educational activities in higher education electronics engineering programs. However, very few studies have considered using educational research methods for performance evaluation of competency-based higher engineering education, with a focus on technical and or transversal skills. To remedy the current need for evaluating competencies in STEM fields and providing sustainable development goals in engineering education, in this study, a comparison was drawn between study groups without and with industry partners.

• State the purpose of your study
• Highlight the key characteristics of your study
• Describe important results
• Highlight the novelty of the study.
• Offer a brief overview of the structure of the paper.

Example: The study evaluates the main competency needed in the applied electronics course, which is a fundamental core subject for many electronics engineering undergraduate programs. We compared two groups, without and with an industrial partner, that offered real-world projects to solve during the semester. This comparison can help determine significant differences in both groups in terms of developing subject competency and achieving sustainable development goals.

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The purpose of the research paper introduction is to introduce the reader to the problem definition, justify the need for the study, and describe the main theme of the study. The aim is to gain the reader’s attention by providing them with necessary background information and establishing the main purpose and direction of the research.

The length of the research paper introduction can vary across journals and disciplines. While there are no strict word limits for writing the research paper introduction, an ideal length would be one page, with a maximum of 400 words over 1-4 paragraphs. Generally, it is one of the shorter sections of the paper as the reader is assumed to have at least a reasonable knowledge about the topic. 2 For example, for a study evaluating the role of building design in ensuring fire safety, there is no need to discuss definitions and nature of fire in the introduction; you could start by commenting upon the existing practices for fire safety and how your study will add to the existing knowledge and practice.

When deciding what to include in the research paper introduction, the rest of the paper should also be considered. The aim is to introduce the reader smoothly to the topic and facilitate an easy read without much dependency on external sources. 3 Below is a list of elements you can include to prepare a research paper introduction outline and follow it when you are writing the research paper introduction. Topic introduction: This can include key definitions and a brief history of the topic. Research context and background: Offer the readers some general information and then narrow it down to specific aspects. Details of the research you conducted: A brief literature review can be included to support your arguments or line of thought. Rationale for the study: This establishes the relevance of your study and establishes its importance. Importance of your research: The main contributions are highlighted to help establish the novelty of your study Research hypothesis: Introduce your research question and propose an expected outcome. Organization of the paper: Include a short paragraph of 3-4 sentences that highlights your plan for the entire paper

Cite only works that are most relevant to your topic; as a general rule, you can include one to three. Note that readers want to see evidence of original thinking. So it is better to avoid using too many references as it does not leave much room for your personal standpoint to shine through. Citations in your research paper introduction support the key points, and the number of citations depend on the subject matter and the point discussed. If the research paper introduction is too long or overflowing with citations, it is better to cite a few review articles rather than the individual articles summarized in the review. A good point to remember when citing research papers in the introduction section is to include at least one-third of the references in the introduction.

The literature review plays a significant role in the research paper introduction section. A good literature review accomplishes the following: Introduces the topic – Establishes the study’s significance – Provides an overview of the relevant literature – Provides context for the study using literature – Identifies knowledge gaps However, remember to avoid making the following mistakes when writing a research paper introduction: Do not use studies from the literature review to aggressively support your research Avoid direct quoting Do not allow literature review to be the focus of this section. Instead, the literature review should only aid in setting a foundation for the manuscript.

Remember the following key points for writing a good research paper introduction: 4

• Avoid stuffing too much general information: Avoid including what an average reader would know and include only that information related to the problem being addressed in the research paper introduction. For example, when describing a comparative study of non-traditional methods for mechanical design optimization, information related to the traditional methods and differences between traditional and non-traditional methods would not be relevant. In this case, the introduction for the research paper should begin with the state-of-the-art non-traditional methods and methods to evaluate the efficiency of newly developed algorithms.
• Avoid packing too many references: Cite only the required works in your research paper introduction. The other works can be included in the discussion section to strengthen your findings.
• Avoid extensive criticism of previous studies: Avoid being overly critical of earlier studies while setting the rationale for your study. A better place for this would be the Discussion section, where you can highlight the advantages of your method.
• Avoid describing conclusions of the study: When writing a research paper introduction remember not to include the findings of your study. The aim is to let the readers know what question is being answered. The actual answer should only be given in the Results and Discussion section.

To summarize, the research paper introduction section should be brief yet informative. It should convince the reader the need to conduct the study and motivate him to read further. If you’re feeling stuck or unsure, choose trusted AI academic writing assistants like Paperpal to effortlessly craft your research paper introduction and other sections of your research article.

1. Jawaid, S. A., & Jawaid, M. (2019). How to write introduction and discussion. Saudi Journal of Anaesthesia, 13(Suppl 1), S18.

2. Dewan, P., & Gupta, P. (2016). Writing the title, abstract and introduction: Looks matter!. Indian pediatrics, 53, 235-241.

3. Cetin, S., & Hackam, D. J. (2005). An approach to the writing of a scientific Manuscript1. Journal of Surgical Research, 128(2), 165-167.

4. Bavdekar, S. B. (2015). Writing introduction: Laying the foundations of a research paper. Journal of the Association of Physicians of India, 63(7), 44-6.

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• Research paper

How to Create a Structured Research Paper Outline | Example

Published on August 7, 2022 by Courtney Gahan . Revised on August 15, 2023.

A research paper outline is a useful tool to aid in the writing process , providing a structure to follow with all information to be included in the paper clearly organized.

A quality outline can make writing your research paper more efficient by helping to:

• Organize your thoughts
• Understand the flow of information and how ideas are related
• Ensure nothing is forgotten

A research paper outline can also give your teacher an early idea of the final product.

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Table of contents

Research paper outline example, how to write a research paper outline, formatting your research paper outline, language in research paper outlines.

• Definition of measles
• Rise in cases in recent years in places the disease was previously eliminated or had very low rates of infection
• Figures: Number of cases per year on average, number in recent years. Relate to immunization
• Symptoms and timeframes of disease
• Risk of fatality, including statistics
• How measles is spread
• Immunization procedures in different regions
• Different regions, focusing on the arguments from those against immunization
• Immunization figures in affected regions
• High number of cases in non-immunizing regions
• Illnesses that can result from measles virus
• Fatal cases of other illnesses after patient contracted measles
• Summary of arguments of different groups
• Summary of figures and relationship with recent immunization debate
• Which side of the argument appears to be correct?

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Professional editors proofread and edit your paper by focusing on:

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See an example

Follow these steps to start your research paper outline:

• Decide on the subject of the paper
• Write down all the ideas you want to include or discuss
• Organize related ideas into sub-groups
• Arrange your ideas into a hierarchy: What should the reader learn first? What is most important? Which idea will help end your paper most effectively?
• Create headings and subheadings that are effective
• Format the outline in either alphanumeric, full-sentence or decimal format

There are three different kinds of research paper outline: alphanumeric, full-sentence and decimal outlines. The differences relate to formatting and style of writing.

• Alphanumeric
• Full-sentence

An alphanumeric outline is most commonly used. It uses Roman numerals, capitalized letters, arabic numerals, lowercase letters to organize the flow of information. Text is written with short notes rather than full sentences.

• Sub-point of sub-point 1

Essentially the same as the alphanumeric outline, but with the text written in full sentences rather than short points.

• Additional sub-point to conclude discussion of point of evidence introduced in point A

A decimal outline is similar in format to the alphanumeric outline, but with a different numbering system: 1, 1.1, 1.2, etc. Text is written as short notes rather than full sentences.

• 1.1.1 Sub-point of first point
• 1.1.2 Sub-point of first point
• 1.2 Second point

To write an effective research paper outline, it is important to pay attention to language. This is especially important if it is one you will show to your teacher or be assessed on.

There are four main considerations: parallelism, coordination, subordination and division.

Parallelism: Be consistent with grammatical form

Parallel structure or parallelism is the repetition of a particular grammatical form within a sentence, or in this case, between points and sub-points. This simply means that if the first point is a verb , the sub-point should also be a verb.

Example of parallelism:

• Include different regions, focusing on the different arguments from those against immunization

Coordination: Be aware of each point’s weight

Your chosen subheadings should hold the same significance as each other, as should all first sub-points, secondary sub-points, and so on.

Example of coordination:

• Include immunization figures in affected regions
• Illnesses that can result from the measles virus

Subordination: Work from general to specific

Subordination refers to the separation of general points from specific. Your main headings should be quite general, and each level of sub-point should become more specific.

Example of subordination:

Division: break information into sub-points.

Your headings should be divided into two or more subsections. There is no limit to how many subsections you can include under each heading, but keep in mind that the information will be structured into a paragraph during the writing stage, so you should not go overboard with the number of sub-points.

Ready to start writing or looking for guidance on a different step in the process? Read our step-by-step guide on how to write a research paper .

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Scientific Consensus

It’s important to remember that scientists always focus on the evidence, not on opinions. Scientific evidence continues to show that human activities ( primarily the human burning of fossil fuels ) have warmed Earth’s surface and its ocean basins, which in turn have continued to impact Earth’s climate . This is based on over a century of scientific evidence forming the structural backbone of today's civilization.

NASA Global Climate Change presents the state of scientific knowledge about climate change while highlighting the role NASA plays in better understanding our home planet. This effort includes citing multiple peer-reviewed studies from research groups across the world, 1 illustrating the accuracy and consensus of research results (in this case, the scientific consensus on climate change) consistent with NASA’s scientific research portfolio.

With that said, multiple studies published in peer-reviewed scientific journals 1 show that climate-warming trends over the past century are extremely likely due to human activities. In addition, most of the leading scientific organizations worldwide have issued public statements endorsing this position. The following is a partial list of these organizations, along with links to their published statements and a selection of related resources.

American Scientific Societies

Statement on climate change from 18 scientific associations.

"Observations throughout the world make it clear that climate change is occurring, and rigorous scientific research demonstrates that the greenhouse gases emitted by human activities are the primary driver." (2009) 2

American Association for the Advancement of Science

"Based on well-established evidence, about 97% of climate scientists have concluded that human-caused climate change is happening." (2014) 3

American Chemical Society

"The Earth’s climate is changing in response to increasing concentrations of greenhouse gases (GHGs) and particulate matter in the atmosphere, largely as the result of human activities." (2016-2019) 4

American Geophysical Union

"Based on extensive scientific evidence, it is extremely likely that human activities, especially emissions of greenhouse gases, are the dominant cause of the observed warming since the mid-20th century. There is no alterative explanation supported by convincing evidence." (2019) 5

American Medical Association

"Our AMA ... supports the findings of the Intergovernmental Panel on Climate Change’s fourth assessment report and concurs with the scientific consensus that the Earth is undergoing adverse global climate change and that anthropogenic contributions are significant." (2019) 6

American Meteorological Society

"Research has found a human influence on the climate of the past several decades ... The IPCC (2013), USGCRP (2017), and USGCRP (2018) indicate that it is extremely likely that human influence has been the dominant cause of the observed warming since the mid-twentieth century." (2019) 7

American Physical Society

"Earth's changing climate is a critical issue and poses the risk of significant environmental, social and economic disruptions around the globe. While natural sources of climate variability are significant, multiple lines of evidence indicate that human influences have had an increasingly dominant effect on global climate warming observed since the mid-twentieth century." (2015) 8

The Geological Society of America

"The Geological Society of America (GSA) concurs with assessments by the National Academies of Science (2005), the National Research Council (2011), the Intergovernmental Panel on Climate Change (IPCC, 2013) and the U.S. Global Change Research Program (Melillo et al., 2014) that global climate has warmed in response to increasing concentrations of carbon dioxide (CO2) and other greenhouse gases ... Human activities (mainly greenhouse-gas emissions) are the dominant cause of the rapid warming since the middle 1900s (IPCC, 2013)." (2015) 9

Science Academies

International academies: joint statement.

"Climate change is real. There will always be uncertainty in understanding a system as complex as the world’s climate. However there is now strong evidence that significant global warming is occurring. The evidence comes from direct measurements of rising surface air temperatures and subsurface ocean temperatures and from phenomena such as increases in average global sea levels, retreating glaciers, and changes to many physical and biological systems. It is likely that most of the warming in recent decades can be attributed to human activities (IPCC 2001)." (2005, 11 international science academies) 1 0

U.S. National Academy of Sciences

"Scientists have known for some time, from multiple lines of evidence, that humans are changing Earth’s climate, primarily through greenhouse gas emissions." 1 1

U.S. Government Agencies

U.s. global change research program.

"Earth’s climate is now changing faster than at any point in the history of modern civilization, primarily as a result of human activities." (2018, 13 U.S. government departments and agencies) 12

Intergovernmental Bodies

Intergovernmental panel on climate change.

“It is unequivocal that the increase of CO 2 , methane, and nitrous oxide in the atmosphere over the industrial era is the result of human activities and that human influence is the principal driver of many changes observed across the atmosphere, ocean, cryosphere, and biosphere. “Since systematic scientific assessments began in the 1970s, the influence of human activity on the warming of the climate system has evolved from theory to established fact.” 1 3-17

Other Resources

List of worldwide scientific organizations.

The following page lists the nearly 200 worldwide scientific organizations that hold the position that climate change has been caused by human action. http://www.opr.ca.gov/facts/list-of-scientific-organizations.html

U.S. Agencies

The following page contains information on what federal agencies are doing to adapt to climate change. https://www.c2es.org/site/assets/uploads/2012/02/climate-change-adaptation-what-federal-agencies-are-doing.pdf

Technically, a “consensus” is a general agreement of opinion, but the scientific method steers us away from this to an objective framework. In science, facts or observations are explained by a hypothesis (a statement of a possible explanation for some natural phenomenon), which can then be tested and retested until it is refuted (or disproved).

As scientists gather more observations, they will build off one explanation and add details to complete the picture. Eventually, a group of hypotheses might be integrated and generalized into a scientific theory, a scientifically acceptable general principle or body of principles offered to explain phenomena.

1. K. Myers, et al, "Consensus revisited: quantifying scientific agreement on climate change and climate expertise among Earth scientists 10 years later", Environmental Research Letters Vol.16 No. 10, 104030 (20 October 2021); DOI:10.1088/1748-9326/ac2774 M. Lynas, et al, "Greater than 99% consensus on human caused climate change in the peer-reviewed scientific literature", Environmental Research Letters Vol.16 No. 11, 114005 (19 October 2021); DOI:10.1088/1748-9326/ac2966 J. Cook et al., "Consensus on consensus: a synthesis of consensus estimates on human-caused global warming", Environmental Research Letters Vol. 11 No. 4, (13 April 2016); DOI:10.1088/1748-9326/11/4/048002 J. Cook et al., "Quantifying the consensus on anthropogenic global warming in the scientific literature", Environmental Research Letters Vol. 8 No. 2, (15 May 2013); DOI:10.1088/1748-9326/8/2/024024 W. R. L. Anderegg, “Expert Credibility in Climate Change”, Proceedings of the National Academy of Sciences Vol. 107 No. 27, 12107-12109 (21 June 2010); DOI: 10.1073/pnas.1003187107 P. T. Doran & M. K. Zimmerman, "Examining the Scientific Consensus on Climate Change", Eos Transactions American Geophysical Union Vol. 90 Issue 3 (2009), 22; DOI: 10.1029/2009EO030002 N. Oreskes, “Beyond the Ivory Tower: The Scientific Consensus on Climate Change”, Science Vol. 306 no. 5702, p. 1686 (3 December 2004); DOI: 10.1126/science.1103618

2. Statement on climate change from 18 scientific associations (2009)

3. AAAS Board Statement on Climate Change (2014)

4. ACS Public Policy Statement: Climate Change (2016-2019)

5. Society Must Address the Growing Climate Crisis Now (2019)

6. Global Climate Change and Human Health (2019)

7. Climate Change: An Information Statement of the American Meteorological Society (2019)

8. American Physical Society (2021)

9. GSA Position Statement on Climate Change (2015)

10. Joint science academies' statement: Global response to climate change (2005)

11. Climate at the National Academies

12. Fourth National Climate Assessment: Volume II (2018)

13. IPCC Fifth Assessment Report, Summary for Policymakers, SPM 1.1 (2014)

14. IPCC Fifth Assessment Report, Summary for Policymakers, SPM 1 (2014)

15. IPCC Sixth Assessment Report, Working Group 1 (2021)

16. IPCC Sixth Assessment Report, Working Group 2 (2022)

17. IPCC Sixth Assessment Report, Working Group 3 (2022)

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Facts About Earth

Modelling fuel oil transformation on geographically different seacoasts and assessing their self-cleansing capacity

• Research Article
• Published: 26 March 2024

Cite this article

• Andrey N. Kuznetsov   ORCID: orcid.org/0000-0002-2301-665X 1 &
• Paul Fattal 2  

The present paper considers the results of long-term (up to 17 years) in situ and laboratory research carried out on oiled French, Spanish, and Russian seacoasts. The objective of this research is to quantify the influence of geographical factors on the rates of natural transformation of the heavy fuel oil stranded ashore and to develop an empirical statistical model in order to evaluate the self-cleansing capacity of the coastal environment. In a number of field campaigns, 363 samples of weathered oil slicks and tar balls have been collected and analysed with the use of thin-layer chromatography combined with optical and gravimetric methods. The results obtained have been subjected to multiple nonlinear regression analyses. It has been shown that heavy fuel oil natural attenuation is more active in continental or estuarine environments influenced by nutrient-rich freshwater runoff and characterised by a higher number of sunny days, solar irradiation, and large temperature fluctuations. On the oceanic coasts, especially in sectors with low hydrodynamic energy, these processes take more time. The resulting model allows for the identification and mapping of the most vulnerable seacoasts, characterised by a low potential to degrade oil pollution. This information may be used in the contingency plans in order to optimise clean-up techniques and associated costs.

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The dataset used in this research is available from the corresponding author on request.

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The study was supported by the international bilateral grants of the National Centre for Scientific Research of France (PICS-3451, LIA no. 1033) and the Russian Foundation for Basic Research (no. 06–05-22001, 13–05-93105).

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The content of nutrients, temperature, salinity, solar irradiation, and surf action are the key predictors of the rates of natural attenuation of the spilt fuel oil on the seacoasts and their self-cleansing capacity.

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Kuznetsov, A.N., Fattal, P. Modelling fuel oil transformation on geographically different seacoasts and assessing their self-cleansing capacity. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-32902-0

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DOI : https://doi.org/10.1007/s11356-024-32902-0

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