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{{T}}
[[Category:English]]
[[Category:Academic Research Methods]]

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= Introduction =

Academic research is a structured way of asking important questions, gathering and evaluating evidence, and communicating conclusions that other people can inspect. In Grades 11–13, learning research methods prepares you for extended essays, project work, laboratory reports, social-science investigations, vocational research, and university study.

Research is not simply “finding information.” You begin with a problem or question, examine what is already known, choose methods that fit the question, collect or select evidence, analyze it, and explain what the evidence does and does not justify. Strong research is transparent: another reader should be able to understand how you reached your conclusions and where uncertainty remains.

[[File:Research cycle.png|500px|frameless|center]]

'''By the end of this aiMOOC, you should be able to''' formulate a focused [[English:Research question|research question]], plan a feasible study, distinguish major research designs, evaluate sources, select data-collection methods, recognize sampling and measurement problems, apply basic research ethics, analyze evidence at an appropriate level, and present a reasoned academic report.

{{#ev:youtube|https://www.youtube.com/watch?v=Q0B3Gjlu-1o|500|center}}

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= What Academic Research Is =

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== Inquiry, Evidence, and Method ==

Academic research is a form of disciplined [[English:Inquiry|inquiry]]. A researcher makes claims only as strongly as the available evidence allows. Evidence may include measurements, observations, documents, images, interviews, survey responses, experimental results, archived records, or existing datasets. The appropriate evidence depends on the question.

A '''method''' is a specific procedure for collecting or analyzing evidence, such as a questionnaire, experiment, interview, statistical test, or thematic coding. '''Methodology''' is the broader reasoning that explains why certain methods are suitable for a particular research problem. Methodology connects your question, assumptions, design, evidence, and interpretation.

Research is often iterative rather than perfectly linear. New reading may change your question, pilot data may reveal a measurement problem, and analysis may lead to new questions. A good research plan is therefore structured but revisable.

[[File:The Scientific Method (simple).png|500px|frameless|center]]

The [[English:Scientific method|scientific method]] is especially important in empirical research, but academic research is broader than laboratory science. Historians may interpret primary documents, literature scholars may analyze texts, social scientists may combine surveys with interviews, and designers may test prototypes. What these approaches share is a commitment to explicit questions, appropriate evidence, careful reasoning, and accountable communication.

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== Theory, Concepts, and Evidence ==

A '''concept''' is an idea you want to understand, such as motivation, trust, biodiversity, or social inequality. A '''theory''' offers an organized explanation of relationships among concepts. Research can test predictions from a theory, explore a poorly understood phenomenon, describe patterns, compare cases, or develop new explanations.

You should distinguish an observation from an interpretation. “Thirty-two of forty respondents selected option A” is an observation about a dataset. “Most students prefer option A because it is more convenient” adds an interpretation and a possible causal explanation. That explanation needs additional evidence.

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= From Topic to Research Question =

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== Narrowing a Topic ==

A topic is a subject area; a research question identifies what you want to find out. “Social media” is a topic. “How does limiting evening social-media notifications for two weeks affect self-reported study concentration among students in one upper-secondary class?” is a much more specific question.

A useful research question is '''focused, researchable, significant, feasible, and ethical'''. It should fit the available time, access to evidence, learner skill level, and school rules. A question that is too broad produces shallow evidence; a question that is too narrow may not generate enough meaningful analysis.

You can narrow a topic by specifying a population, context, time period, variable, comparison, text, event, or case. Background reading is part of this process because it helps you discover useful terminology and identify what is already known.

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== Hypotheses and Variables ==

In some quantitative studies, a '''hypothesis''' is a testable prediction about a relationship or difference. For example, you might predict that students who use a structured revision schedule will report more completed practice sessions than students who do not.

A '''variable''' is a characteristic that can take different values. In an experiment, the independent variable is manipulated or used to define conditions, while the dependent variable is the measured outcome. A '''control variable''' is held constant or accounted for to reduce alternative explanations.

Not every research project needs a hypothesis. Exploratory qualitative research may begin with open questions instead of predictions. The question should determine the design, not the other way around.

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= Literature Review and Source Evaluation =

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== Finding Academic Literature ==

A [[English:Literature review|literature review]] identifies, evaluates, compares, and synthesizes relevant scholarship. Its purpose is not to create a list of summaries. Instead, you look for patterns, disagreements, methods, influential ideas, limitations, and gaps that help position your own research.

Start with key concepts from your research question. Generate synonyms and related terms, then combine them using database search tools. Boolean operators such as AND, OR, and NOT can help control a search. Phrase searching, filters, subject headings, cited-reference searching, and reference lists can help you move from broad discovery to focused evidence.

{{#ev:youtube|https://www.youtube.com/watch?v=ThCL_3GQZSc|500|center}}

Scholarly articles often contain an abstract, introduction, method section, results, discussion, and references, although structure varies by discipline. Do not assume that publication automatically makes a source correct. Read critically and compare findings across multiple credible sources.

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== Primary, Secondary, and Tertiary Sources ==

A '''primary source''' provides direct or original evidence relevant to a question. Examples include experimental data, historical letters, interview transcripts, legal documents, field observations, or original research articles. A '''secondary source''' analyzes, interprets, or synthesizes primary material. A '''tertiary source''' summarizes established knowledge, as in many encyclopedias or introductory reference works.

These categories depend on your research question. A newspaper article can be a secondary source for one project but a primary source in a study of how an event was reported.

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== Evaluating Sources ==

Evaluate a source by asking who created it, for what purpose, using what evidence, with what methods, and in what context. Check the author's expertise, publication venue, date, citations, transparency, possible conflicts of interest, and whether claims are supported by data or credible references. Distinguish expert consensus from a single study and distinguish peer review from proof.

{{#ev:youtube|https://www.youtube.com/watch?v=psaOdZFPTEM|500|center}}

A strong researcher also practices '''lateral reading''': leave the source, investigate the author or organization elsewhere, and compare the claim with independent sources. This is especially important for websites, viral posts, persuasive media, and AI-generated summaries.

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= Research Designs and Methods =

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== Quantitative, Qualitative, and Mixed Methods ==

'''Quantitative research''' represents evidence numerically and often examines frequencies, differences, relationships, or model-based estimates. Common tools include structured surveys, experiments, standardized measures, and existing numerical datasets.

'''Qualitative research''' investigates meaning, experience, process, culture, or interpretation through evidence such as interviews, observations, documents, images, and open-ended responses. Analysis often involves coding, categorizing, comparing cases, and developing themes.

'''Mixed methods research''' deliberately combines quantitative and qualitative evidence when one type alone cannot answer the full question. Combining methods should be purposeful, not simply adding more data.

{{#ev:youtube|https://www.youtube.com/watch?v=hAUgRPZ33BE|500|center}}

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== Experimental and Observational Designs ==

In a true experiment, researchers deliberately manipulate an independent variable and use comparison conditions. Random assignment can help balance pre-existing differences between groups, strengthening causal inference. Experiments also require careful control, ethical safeguards, and suitable measurement.

In an observational study, researchers measure variables without assigning the exposure or condition. Observational studies can reveal valuable associations and real-world patterns, but an association does not by itself establish causation. Confounding variables, reverse causation, selection effects, and measurement problems may offer alternative explanations.

A '''case study''' investigates a bounded case in depth. A '''survey''' collects standardized responses from a sample. A '''content analysis''' systematically examines features of texts, images, media, or documents. A '''correlational study''' examines whether variables vary together. Each design can be rigorous when it matches the question and is implemented carefully.

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= Sampling and Measurement =

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== Populations, Samples, and Sampling Bias ==

The '''population''' is the larger group or set you want to understand. The '''sample''' is the subset from which you actually collect data. A sample can be large and still biased if the selection process systematically excludes relevant parts of the population.

In '''probability sampling''', units have a known chance of selection. Simple random sampling is one probability method. Stratified sampling draws from defined subgroups. Cluster sampling selects groups or clusters. In '''non-probability sampling''', selection probabilities are not known; convenience and voluntary-response samples are common examples.

[[File:Random sampling.png|500px|frameless|center]]

Sampling decisions affect how far you can generalize. If you survey only volunteers from one class, you should describe conclusions as applying primarily to that group rather than claiming to represent all teenagers.

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== Operationalization, Reliability, and Validity ==

'''Operationalization''' means turning an abstract concept into something you can observe or measure. If your concept is “study concentration,” you might operationalize it as a score on a validated scale, the number of uninterrupted work intervals, or another clearly defined indicator.

'''Reliability''' concerns consistency. A reliable measure tends to produce stable or internally consistent results under appropriate repeated conditions. '''Validity''' concerns whether the interpretation of a measure is appropriate for the intended purpose. A measure can be reliable without being valid; for example, a badly calibrated instrument can produce consistent but inaccurate values.

Question wording, response options, observer expectations, device calibration, and coding rules can all affect measurement quality. Pilot testing helps you detect unclear instructions, missing categories, technical problems, and unrealistic procedures before the main study.

[[File:Questionnaire-checklist.png|500px|frameless|center]]

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= Research Ethics and Academic Integrity =

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== Protecting Participants ==

Research involving people must protect their rights, dignity, privacy, and welfare. Ethical expectations vary by country, institution, and type of study, so you must follow the rules that apply in your school or organization.

Three influential principles in human-subject research ethics are '''respect for persons, beneficence, and justice'''. Respect for persons supports voluntary and informed participation. Beneficence requires researchers to minimize possible harm and consider possible benefits. Justice asks whether the burdens and benefits of research are distributed fairly.

For school research, use teacher supervision, keep risks minimal, avoid collecting sensitive personal information unless a properly approved project genuinely requires it, and explain participation clearly. If participants are minors, additional consent and safeguarding requirements may apply. Participation must never depend on pressure from grades, authority, friendship, or rewards so large that they undermine voluntary choice.

Protect privacy by collecting only necessary information, separating identifiers from responses when possible, controlling access, and reporting results so individuals cannot be recognized without permission.

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== Integrity, Citation, and Responsible Use of Sources ==

Academic integrity means representing evidence and authorship accurately. '''Fabrication''' is making up data or sources. '''Falsification''' is manipulating research materials, processes, or data so that the record is misleading. '''Plagiarism''' is presenting another person's words, ideas, or work as your own without appropriate acknowledgement.

[[File:Avoiding plagiarism.pdf|500px|frameless|center]]

Quoting, paraphrasing, and summarizing all require correct citation when the idea comes from a source. A citation allows readers to trace the origin of evidence and gives credit. Your bibliography should match the in-text citations and follow the style required by your subject or institution.

AI tools can support brainstorming, language revision, coding practice, or search planning only when their use is permitted and disclosed as required. Never invent citations, submit generated claims without verification, or use an AI output as a substitute for examining the original source. You remain responsible for accuracy, attribution, confidentiality, and compliance with your institution's rules.

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= Data Analysis and Interpretation =

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== Quantitative Analysis ==

Begin by checking your data. Look for missing values, impossible entries, duplicate records, coding mistakes, and unusual observations. Document any changes rather than silently deleting inconvenient data.

'''Descriptive statistics''' summarize the data you observed. The mean, median, mode, range, interquartile range, standard deviation, percentages, and frequency tables can reveal different aspects of a distribution. Choose summaries that match the type and shape of the data.

[[File:Histogram example.svg|500px|frameless|center]]

A histogram shows the distribution of a numerical variable across intervals. A box plot can highlight the median, quartiles, spread, and unusual values. A scatterplot can display the relationship between two numerical variables. A graph should include enough context for a reader to understand what was measured, the units, and the groups shown.

The normal distribution is an important mathematical model used in many statistical procedures, but real datasets should not be assumed to be normal without inspection and justification.

[[File:Standard Normal Distribution-en.svg|500px|frameless|center]]

Inferential statistics use sample evidence to reason about a wider population under stated assumptions. Confidence intervals express a range of values compatible with the data and model. A p-value, when used, does not measure the probability that a hypothesis is true and should not replace effect size, uncertainty, study design, and substantive reasoning.

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== Qualitative Analysis ==

Qualitative analysis is systematic interpretation, not simply choosing memorable quotations. Researchers may transcribe evidence, develop codes, group codes into categories, compare cases, refine themes, and look deliberately for evidence that challenges an emerging interpretation.

Good qualitative work makes the analytic process visible. Explain how evidence was selected, how codes or categories were developed, how disagreements were handled if several researchers coded the material, and why the final interpretation is plausible.

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== Bias, Uncertainty, and Limits ==

Every study has limits. '''Bias''' is a systematic influence that pushes results or interpretations away from the target you intended to study. Random variation produces uncertainty even when methods are unbiased. Measurement error, nonresponse, attrition, researcher expectations, uncontrolled confounding, and selective reporting can all distort conclusions.

A limitation section should not merely apologize for weaknesses. It should explain how each limitation may affect interpretation and what a better future study could do differently.

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= Writing and Communicating Research =

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== Structure of an Academic Report ==

Many empirical papers use the '''IMRaD''' pattern: Introduction, Methods, Results, and Discussion. This structure is common rather than universal. Humanities essays, design reports, historical studies, and qualitative projects may use different forms.

The introduction establishes the problem, context, relevant literature, and research question. The methods section explains what you did in enough detail for a reader to evaluate the study. The results section presents evidence without hiding inconvenient findings. The discussion interprets the results, connects them to previous research, considers alternatives and limitations, and explains what can reasonably be concluded.

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== Claims, Evidence, and Reasoning ==

An academic claim should be specific enough to test against evidence. Evidence should be relevant and trustworthy. Reasoning explains why the evidence supports the claim. Good writing also marks uncertainty with language such as “suggests,” “is consistent with,” or “cannot rule out” when certainty would be unjustified.

Avoid “citation decoration,” where references are added without showing how they support the argument. Compare sources, identify agreements and disagreements, and explain why one explanation is more convincing than another.

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== Peer Review and Open Critique ==

Peer review is a process in which people with relevant expertise evaluate research or scholarly work. It can improve clarity, methods, and argumentation, but peer review does not guarantee that a paper is correct. Published claims remain open to replication, reanalysis, criticism, and revision.

[[File:Peer Review.png|500px|frameless|center]]

In your own class, structured peer feedback can model this process. Ask reviewers to identify the research question, examine whether the method answers it, check whether conclusions match the evidence, and suggest one concrete improvement.

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= A Practical Research Workflow =

A manageable school research project can follow this cycle: identify a worthwhile topic, conduct background reading, formulate a focused question, choose a design, check ethical requirements, pilot the procedure, collect or select evidence, analyze it, interpret the findings, write the report, receive feedback, revise, and share the result.

Keep a research log throughout. Record search terms, database choices, decisions, changes to the plan, data-cleaning steps, coding rules, and questions for your teacher. A well-kept log strengthens transparency and helps you write the methods and limitations sections later.

Before you begin data collection, write a short protocol stating your question, sample or materials, variables or themes, procedure, ethical safeguards, and intended analysis. Planning these elements in advance reduces the temptation to change decisions only because of results you happen to see.

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= Interactive Tasks =

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== Quiz: Test Your Knowledge ==

{{MC}}

'''What is the main purpose of a research question?'''
(To define what the study is trying to find out)
(!To guarantee that the hypothesis will be supported)
(!To replace the need for a research design)
(!To make every source equally useful)

{{E}}
<br>

{{MC}}

'''Which statement best describes a literature review?'''
(It evaluates and synthesizes relevant scholarship)
(!It lists every source in alphabetical order)
(!It reports only the researcher's own data)
(!It avoids comparing disagreements between studies)

{{E}}
<br>

{{MC}}

'''What is a sample?'''
(The subset from which a researcher collects data)
(!Every person who could ever be studied)
(!A variable that the researcher manipulates)
(!A conclusion drawn before evidence is collected)

{{E}}
<br>

{{MC}}

'''What does reliability mainly concern?'''
(The consistency of a measurement)
(!The popularity of a research topic)
(!The number of citations in a report)
(!The moral value of a hypothesis)

{{E}}
<br>

{{MC}}

'''Why can an observational correlation fail to show causation?'''
(Other explanations may account for the association)
(!Correlations can only be calculated from interviews)
(!Observational studies never use numerical data)
(!Causal claims never require comparison)

{{E}}
<br>

{{MC}}

'''Which action best supports informed participation?'''
(Explaining the study clearly before voluntary agreement)
(!Hiding possible risks so that people will participate)
(!Making participation compulsory for better grades)
(!Collecting unnecessary personal information)

{{E}}
<br>

{{MC}}

'''What is operationalization?'''
(Defining how a concept will be observed or measured)
(!Publishing an article after peer review)
(!Choosing a citation style for a bibliography)
(!Removing all unusual values from a dataset)

{{E}}
<br>

{{MC}}

'''Which practice is academic misconduct?'''
(Fabricating data that were never collected)
(!Reporting a limitation of the study)
(!Revising a question after background reading)
(!Comparing two credible explanations)

{{E}}
<br>

{{MC}}

'''What is a confidence interval used to express?'''
(A range of values compatible with data and assumptions)
(!Proof that a result will replicate)
(!The probability that every hypothesis is true)
(!The exact size of every future sample)

{{E}}
<br>

{{MC}}

'''What is the best conclusion about peer review?'''
(It improves scrutiny but does not guarantee correctness)
(!It proves that published findings cannot be revised)
(!It makes replication unnecessary)
(!It means all peer reviewed studies are equally strong)

{{E}}
<br>

{{BR}}
== Memory Game ==

<div class="memo-quiz">
{|
|-
| Research question || A focused statement of what a study aims to find out
|-
| Population || The full group or set a researcher wants to understand
|-
| Sample || The subset from which evidence is actually collected
|-
| Reliability || The consistency of a measurement under appropriate conditions
|-
| Validity || The appropriateness of an interpretation for an intended use
|-
| Operationalization || The process of turning a concept into an observable measure
|-
| Confounder || A factor that can offer an alternative explanation for an association
|-
| Triangulation || The purposeful comparison of different evidence or methods to strengthen interpretation
|}
{{E}}
<br>

{{BR}}
== Drag and Drop ==

<div class="lueckentext-quiz">

{| class="wikitable"
! Match the correct terms.
! Topic
|-
| '''Random assignment'''
| Places participants into study conditions by chance
|-
| '''Random sampling'''
| Selects units from a population by chance
|-
| '''Dependent variable'''
| Records the outcome measured in a study
|-
| '''Literature review'''
| Synthesizes relevant existing scholarship
|-
| '''Informed consent'''
| Supports voluntary participation based on adequate information
|}
{{E}}

<br>
...
<br />

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== Crossword Puzzle ==

<div class="kreuzwort-quiz">
{|
|-
| Hypothesis || What is a testable prediction about an expected relationship called?
|-
| Sampling || What process selects cases or units from a population?
|-
| Validity || What term concerns whether an interpretation or measure is appropriate?
|-
| Reliability || What term concerns the consistency of a measurement?
|-
| Citation || What acknowledges and traces the source of an idea or quotation?
|-
| Ethics || What field examines responsible conduct and participant protection?
|}
{{E}}
<br>

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== LearningApps ==

<iframe> https://learningapps.org/index.php?s=Academic+Research+Methods </iframe>

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== Cloze Text ==

<quiz display=simple>
{'''Complete the text.'''<br>
|type="{}"}
A focused { research question } states what a study is trying to find out. A literature review should { synthesize } relevant scholarship rather than merely list sources. The people or cases from which data are collected form the { sample }. Turning an abstract idea into a measurable indicator is called { operationalization }. A consistent measure demonstrates { reliability }. Appropriate interpretation of a measure concerns { validity }. An observed association may have an alternative explanation because of a { confounder }. Voluntary participation based on adequate information requires { informed consent }. Making up data is called { fabrication }. A strong conclusion reports uncertainty and respects the study's { limitations }.
</quiz>

<br>

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= Open-Ended Tasks =

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=== Easy ===
# [[English:Question Clinic|Question Clinic]]: Choose a broad school-related topic, write three possible research questions, and revise one so that it is focused, feasible, researchable, and ethical.
# [[English:Source Detective|Source Detective]]: Find one scholarly source and one popular source on the same issue, then create a one-page comparison of authorship, evidence, purpose, date, references, and limitations.
# [[English:Research Process Poster|Research Process Poster]]: Design an image or infographic that shows the research cycle and add a short caption explaining why researchers may return to earlier stages.
# [[English:Library Interview|Library Interview]]: Interview a librarian or teacher about how students can find trustworthy academic sources, then summarize three search strategies you learned.

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=== Standard ===
# [[English:Mini Literature Map|Mini Literature Map]]: Read at least four credible sources on one focused question and create a concept map showing agreements, disagreements, methods, and one gap in the literature.
# [[English:Questionnaire Pilot|Questionnaire Pilot]]: With teacher approval, draft a short non-sensitive questionnaire, pilot it with a small voluntary group, identify unclear items, and revise the instrument without collecting unnecessary personal data.
# [[English:Public Dataset Study|Public Dataset Study]]: Use an open, non-sensitive dataset to create two appropriate visualizations, calculate suitable descriptive statistics, and explain one pattern plus one limitation.
# [[English:Methods Explainer Video|Methods Explainer Video]]: Produce a three-minute video comparing an experiment, an observational study, and an interview study, including one suitable research question for each design.

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=== Advanced ===
# [[English:Comparative Research Proposal|Comparative Research Proposal]]: Write a complete proposal with background, research question, literature rationale, design, sampling plan, measures, ethical safeguards, planned analysis, and anticipated limitations.
# [[English:Replication Critique|Replication Critique]]: Select a published empirical study, explain what a direct or conceptual replication would test, and redesign one part of the method to improve transparency or measurement.
# [[English:Mixed Methods Project|Mixed Methods Project]]: With teacher approval, design a small project that combines a quantitative source with qualitative evidence and explain exactly how the two forms of evidence answer different parts of the same question.
# [[English:Research Showcase|Research Showcase]]: Produce a conference-style poster and five-minute presentation of a completed school research project, then respond to peer questions by distinguishing evidence, interpretation, uncertainty, and future research.

{{:Open Task - Create a MOOC}}

{{BR}}
= Learning Assessment =

# [[English:Design Alignment Assessment|Design Alignment Assessment]]: Given a research question, justify a suitable design, sample, measure, and analysis, then explain why two alternative designs would be weaker for that question.
# [[English:Bias Diagnosis Assessment|Bias Diagnosis Assessment]]: Analyze a short study scenario, identify at least three possible sources of bias or confounding, and propose realistic changes that would reduce them.
# [[English:Evidence Synthesis Assessment|Evidence Synthesis Assessment]]: Compare several sources that disagree, evaluate their methods and evidence, and write a reasoned conclusion that indicates which claims are strongest and why.
# [[English:Ethics Review Assessment|Ethics Review Assessment]]: Review a proposed school study involving human participants, identify ethical concerns, and rewrite the procedure to improve consent, privacy, proportionality, and fairness.
# [[English:Data Interpretation Assessment|Data Interpretation Assessment]]: Interpret a table and graph, distinguish descriptive findings from causal claims, and write conclusions that accurately express uncertainty.
# [[English:Research Communication Assessment|Research Communication Assessment]]: Produce an abstract or executive summary that states the question, method, main result, limitation, and justified conclusion without exaggeration.

<br>
<br>

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= Evidence of Learning =

Evidence of learning should show both what you know and what you can do. A strong portfolio can include the following elements.

{| class="wikitable"
! Area
! Evidence
|-
| Knowledge
| Accurate explanation of research questions, designs, sampling, measurement, ethics, analysis, and academic integrity
|-
| Skills
| Effective searching, source evaluation, operationalization, data handling, visualization, interpretation, citation, and peer feedback
|-
| Products
| A research log, literature map, proposal or protocol, cleaned dataset or coded evidence, analysis, report, poster, or presentation
|-
| Reasoning
| Clear links among question, method, evidence, claim, uncertainty, and limitation
|-
| Transfer
| Ability to choose and adapt research methods for a new school, vocational, civic, scientific, or university-level problem
|}

<br>
<br>

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= OERs on the Topic =

<iframe> https://en.m.wikipedia.org/wiki/Research </iframe>

<br>

Useful related learning areas include [[English:Research ethics|Research ethics]], [[English:Scientific method|Scientific method]], [[English:Qualitative research|Qualitative research]], [[English:Quantitative research|Quantitative research]], [[English:Statistics|Statistics]], [[English:Information literacy|Information literacy]], [[English:Academic writing|Academic writing]], [[English:Citation|Citation]], [[English:Peer review|Peer review]], and [[English:Data visualization|Data visualization]].

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= Linked Learning Areas =

{| align=center
{{:D-Tab}}
'''[[English:Academic Research Methods|Academic Research Methods]]'''
# [[English:Research question|Research question]]
# [[English:Literature review|Literature review]]
# [[English:Research design|Research design]]
# [[English:Sampling|Sampling]]
# [[English:Measurement|Measurement]]
# [[English:Research ethics|Research ethics]]
# [[English:Data analysis|Data analysis]]
# [[English:Academic writing|Academic writing]]
# [[English:Peer review|Peer review]]
|}

{{BR}}
= aiMOOC Projects =
[[Category:English]]
[[Category:Academic Research Methods]]
[[Category:Research]]
[[Category:Research methods]]
[[Category:Information literacy]]
[[Category:Academic writing]]
[[Category:Statistics]]
[[Category:Social sciences]]
[[Category:Science]]
[[Category:Grades 11-13]]
[[Category:AI_MOOC]]
[[Category:GPT aiMOOC]]
{{MT}}

English:Academic Research Methods - Versionsgeschichte

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