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Read the textbook chapter alongside the video lesson or podcast. Use the chapter’s explanations, worked examples, Practice and Apply tasks, Short Quiz, and Answers and Explanations to check your understanding.

The short overviews and plain-English topic explanations below are simplified study support. Return to the textbook for full definitions, evidence, examples, and limitations.

Explore the 15 Chapters

Chapter titles and topic headings retain the textbook’s wording. Overviews and plain-English explanations are separate study support.

Chapter 1: Foundations of Applied Linguistics Research

Textbook: pp. 14–24

Overview: simplified study support

Research begins with a focused question about language learning, teaching, use, or communication. Learn how researchers connect a problem with evidence and explain what their findings can support.

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Five core topics

1.1 Real-World Language Problems and Researchable Inquiry
In plain English: Turn an everyday language concern into a question that can be investigated with suitable evidence.

1.2 Purposes and Forms of Applied Linguistics Research
In plain English: Identify what a study aims to explore, describe, or explain before choosing its procedures.

1.3 Evidence, Data, Claims, and Interpretation
In plain English: Distinguish recorded information from the evidence and reasoning used to support a claim.

1.4 The Research Cycle from Problem to Dissemination
In plain English: Connect the research problem, ethical planning, collection, analysis, interpretation, and sharing of findings.

1.5 Methodology, Methods, and Analysis: Key Distinctions
In plain English: Separate the overall approach from the tools used to collect information and the procedures used to analyze it.

Chapter 2: Reading, Reviewing, and Synthesizing Research Literature

Textbook: pp. 25–35

Overview: simplified study support

A literature review builds an account of what previous studies jointly suggest. Learn to search systematically, judge sources, compare findings, and explain why a new question needs investigation.

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Five core topics

2.1 Understanding the Structure of an Empirical Research Article
In plain English: Follow how an article connects its background, question, methods, findings, and interpretation.

2.2 Searching for Relevant Research
In plain English: Build a focused search from key concepts and related terms, and keep a record of the search process.

2.3 Evaluating the Quality and Relevance of Sources
In plain English: Judge both a study’s quality and its relevance to your question, participants, and setting.

2.4 Comparing and Synthesizing Previous Studies
In plain English: Compare studies by their questions, evidence, and methods rather than summarizing them separately.

2.5 Identifying Research Gaps and Building a Study Rationale
In plain English: Explain a specific unresolved issue and why addressing it could add useful understanding.

Chapter 3: Research Problems, Aims, Questions, and Hypotheses

Textbook: pp. 36–46

Overview: simplified study support

A broad topic needs clear boundaries before it can become a research project. Connect the problem, aim, questions, and possible hypotheses with evidence that can realistically answer them.

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Five core topics

3.1 Identifying and Defining a Research Problem
In plain English: Distinguish an area of interest from a specific uncertainty that needs investigation.

3.2 Writing Research Aims and Purpose Statements
In plain English: State what the study intends to do in terms that fit its problem and available evidence.

3.3 Quantitative Research Questions and Hypotheses
In plain English: Frame questions about numerical patterns and distinguish those questions from proposed relationships to be examined.

3.4 Qualitative Research Questions
In plain English: Ask focused, open questions about experiences, meanings, practices, or processes.

3.5 Aligning Questions with Evidence and Methods
In plain English: Choose participants, records, collection procedures, and analysis that fit the question.

Chapter 4: Research Perspectives and Methodological Choice

Textbook: pp. 47–57

Overview: simplified study support

Different research perspectives can address different aspects of a language problem. Examine their assumptions and justify an approach that fits the question, context, and form of evidence needed.

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Five core topics

4.1 Ways of Knowing and Research Assumptions
In plain English: Make clear what the study assumes can be known and how its evidence can support that knowledge.

4.2 The Quantitative Research Perspective
In plain English: Use carefully defined numerical measures to describe patterns, compare conditions, or examine associations.

4.3 The Qualitative Research Perspective
In plain English: Use detailed contextual records to investigate meanings, practices, experiences, and differences within the evidence.

4.4 Theory, Researcher Position, and Reflexivity
In plain English: Explain how theory and the researcher’s position relate to research decisions and interpretations.

4.5 Matching Methodology to Questions and Contexts
In plain English: Choose an approach because it can answer the question within the study’s practical and ethical conditions.

Chapter 5: Research Ethics, Integrity, and Responsible Practice

Textbook: pp. 58–68

Overview: simplified study support

Ethical responsibilities continue from the choice of a question to the sharing of findings. Consider consent, privacy, power, and honest reporting throughout the project, including when digital tools are used.

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Five core topics

5.1 Ethics Across the Research Process
In plain English: Consider responsibilities toward participants, communities, colleagues, and readers at every research stage.

5.2 Informed Consent and Voluntary Participation
In plain English: Provide understandable information and make participation a free choice, rather than relying only on a signed form.

5.3 Privacy, Confidentiality, and Anonymity
In plain English: Distinguish control over personal information, protection against disclosure, and whether people can be identified.

5.4 Power, Vulnerability, Classrooms, and Digital Data
In plain English: Consider whether authority, classroom relationships, or online conditions limit people’s ability to decline or speak freely.

5.5 Research Integrity, Human Responsibility, and Generative AI
In plain English: Report evidence honestly, acknowledge sources, and retain human responsibility for checking work produced with AI assistance.

Chapter 6: Participants, Sampling, and Research Contexts

Textbook: pp. 69–79

Overview: simplified study support

Who or what enters a study shapes the conclusions it can support. Learn to explain sampling, recruitment, and context, and judge whether the evidence is adequate for the research purpose.

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Five core topics

6.1 Populations, Samples, Cases, and Research Settings
In plain English: Distinguish the intended population, the people or materials that can be reached, and the units actually studied.

6.2 Probability Sampling
In plain English: Use a documented selection procedure that gives eligible units known, nonzero chances of inclusion.

6.3 Nonprobability and Purposeful Sampling
In plain English: Explain how accessible or deliberately selected cases serve the question and limit broader conclusions.

6.4 Sample Size and Evidence Adequacy
In plain English: Justify the amount of evidence through the question, design, analysis, and constraints, without relying on one universal number.

6.5 Recruitment, Inclusion Criteria, and Participant Description
In plain English: Describe eligibility, recruitment, and participants clearly, with criteria based on the study’s purpose and ethics.

Chapter 7: Constructs, Measurement, and Research Quality

Textbook: pp. 80–90

Overview: simplified study support

Research quality depends on how closely evidence represents the concept being studied. Examine measurement, consistency, and appropriate interpretation while selecting quality checks that fit the research approach.

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Five core topics

7.1 Constructs and Operational Definitions
In plain English: Define a concept clearly before deciding which observations or responses can represent it.

7.2 Variables, Indicators, and Levels of Measurement
In plain English: Distinguish categories, ordered responses, counts, and quantities before choosing numerical summaries.

7.3 Reliability and Consistency of Measurement
In plain English: Assess how consistently scores are produced under relevant conditions, rather than treating an instrument’s name as a guarantee.

7.4 Validity and Appropriate Inference
In plain English: Evaluate whether evidence supports the intended meaning and use of scores for these participants and conditions.

7.5 Trustworthiness, Triangulation, and Quality Across Approaches
In plain English: Connect interpretations with suitable evidence, contextual detail, and a clearly documented research process.

Chapter 8: Quantitative Research Designs

Textbook: pp. 91–101

Overview: simplified study support

Quantitative designs organize measurements and comparisons around a research question. Compare descriptive, correlational, and experimental approaches, and recognize how timing and design limit interpretation.

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Five core topics

8.1 The Logic of Quantitative Research Design
In plain English: Plan the measures, study units, timing, conditions, and comparisons before selecting a statistical test.

8.2 Descriptive and Survey Research Designs
In plain English: Describe patterns in a defined group using clear measures, suitable sampling, and accurate counts.

8.3 Correlational Research Designs
In plain English: Examine how measured variables are associated while considering alternative explanations.

8.4 Experimental and Quasi-Experimental Designs
In plain English: Distinguish designs that introduce comparison conditions and whether assignment to those conditions is randomized.

8.5 Cross-Sectional, Longitudinal, and Design-Based Limits on Inference
In plain English: Separate a snapshot from observations over time, and limit claims to what the design can support.

Chapter 9: Qualitative Research Designs

Textbook: pp. 102–112

Overview: simplified study support

Qualitative designs examine experiences and practices through detailed evidence in context. Compare cases, ethnographic work, narratives, and classroom inquiry while defining the boundaries of a feasible study.

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Five core topics

9.1 The Logic of Qualitative Inquiry
In plain English: Develop a reasoned interpretation of meanings, actions, and experiences through close work with contextual records.

9.2 Case Study Research
In plain English: Define a bounded case and explain why examining it in depth can answer the question.

9.3 Ethnography and Linguistic Ethnography
In plain English: Study social and language practices through sustained engagement with people, activities, and settings.

9.4 Narrative Inquiry and Experience-Centered Research
In plain English: Examine how stories of experience are told, organized, and connected with their social context.

9.5 Classroom-Based and Action Research
In plain English: Plan a focused classroom inquiry while recognizing that a classroom setting does not determine the research approach.

Chapter 10: Mixed Methods Research

Textbook: pp. 113–122

Overview: simplified study support

Mixed methods research needs a clear reason for connecting numerical and qualitative evidence. Compare designs and identify how the two strands contribute to a combined interpretation.

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Five core topics

10.1 Purposes for Combining Quantitative and Qualitative Evidence
In plain English: Explain why connecting the two forms of evidence helps answer the question.

10.2 Convergent Mixed Methods Designs
In plain English: Analyze evidence developed during a broadly similar phase and bring the findings together around a shared question.

10.3 Sequential Mixed Methods Designs
In plain English: Show how an earlier strand informs a later sampling, collection, or analysis decision.

10.4 Integrating Data, Results, and Interpretations
In plain English: Make the connections between strands visible in the design, analysis, or interpretation.

10.5 Quality, Feasibility, and Limits of Mixed Methods
In plain English: Judge the quality of each strand and their connections, since adding a second method does not repair weak evidence.

Chapter 11: Data Collection I: Questionnaires, Tests, and Elicitation

Textbook: pp. 123–133

Overview: simplified study support

Structured data collection requires more than choosing a familiar instrument. Examine what questionnaires, tests, and tasks actually record, and plan selection, adaptation, scoring, and piloting carefully.

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Five core topics

11.1 Questionnaires, Scales, and Survey Items
In plain English: Distinguish a questionnaire from a scale and write items and response options that fit the intended concept.

11.2 Tests and Validated Measures
In plain English: Check what a task and its scoring procedure can show about knowledge or ability in the intended setting.

11.3 Elicitation Tasks and Judgment Tasks
In plain English: Use tasks that invite relevant language responses while considering the demands those tasks create.

11.4 Think-Aloud, Stimulated Recall, and Introspective Protocols
In plain English: Treat verbal reports during or after a task as evidence about reported thinking, rather than a complete record of the mind.

11.5 Selecting, Adapting, and Piloting Research Instruments
In plain English: Check an instrument’s purpose, documentation, reuse conditions, and fit before adapting and piloting it.

Chapter 12: Data Collection II: Interviews, Observation, and Language Data

Textbook: pp. 134–144

Overview: simplified study support

Interviews, observations, and language records offer different views of a research problem. Plan their collection with attention to context, how the records are produced, and the people represented in them.

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Five core topics

12.1 Research Interviews
In plain English: Use focused prompts to invite accounts, while recognizing that an interview is a particular interaction.

12.2 Focus Groups and Group Interaction
In plain English: Examine how participants respond to one another, as well as what each person says.

12.3 Observation, Field Notes, and Classroom Data
In plain English: Record activity in ways that fit the question and distinguish observed events from interpretations.

12.4 Diaries, Journals, Logs, and Participant-Generated Records
In plain English: Use records produced over time while considering what participants choose or are able to report.

12.5 Documents, Corpora, Digital Discourse, and Multimodal Data
In plain English: Document the origin, version, purpose, and permissions of written, digital, corpus, and multimodal materials.

Chapter 13: Quantitative Data Analysis and Interpretation

Textbook: pp. 145–156

Overview: simplified study support

Numerical analysis begins with understanding the dataset and its design. Learn to summarize patterns, examine associations and differences, and interpret statistical evidence with attention to size and uncertainty.

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Five core topics

13.1 Preparing and Screening Quantitative Data
In plain English: Check what each row and variable represents, how values were recorded, and which observations are related.

13.2 Descriptive Statistics and Visual Summaries
In plain English: Choose counts, measures of center and spread, and graphs that match the meaning and form of the data.

13.3 Examining Associations between Variables
In plain English: Inspect how paired values vary together, including unusual observations and patterns hidden by a single coefficient.

13.4 Comparing Groups and Conditions
In plain English: Distinguish independent groups from linked or repeated observations before choosing a comparison.

13.5 Statistical Evidence, Effect Size, Uncertainty, and Cautious Interpretation
In plain English: Interpret statistical results alongside effect size, uncertainty, design, sampling, and measurement limits.

Chapter 14: Qualitative Data Analysis and Interpretation

Textbook: pp. 157–167

Overview: simplified study support

Qualitative analysis develops an interpretation through careful comparison of records. Connect extracts, codes, categories, and themes, and make the reasoning behind the final account clear.

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Five core topics

14.1 Preparing, Organizing, and Transcribing Qualitative Data
In plain English: Organize and transcribe records in ways that preserve the context needed for the question.

14.2 Initial Coding and Code Development
In plain English: Use concise labels to organize relevant features while keeping their connection to the original extracts.

14.3 Categories, Patterns, and Themes
In plain English: Distinguish groups of related content from developed patterns of meaning that answer the question.

14.4 Thematic and Qualitative Content Analysis
In plain English: Choose and explain an analysis approach rather than treating all thematic or content analysis as one procedure.

14.5 Interpretation, Reflexivity, and Transparent Analytic Records
In plain English: Support interpretations with contextual evidence, acknowledge variation, and document analytical decisions.

Chapter 15: Planning, Reporting, and Open Research Practices

Textbook: pp. 168–179

Overview: simplified study support

A complete study connects its purpose with feasible methods and responsible reporting. Bring the earlier decisions together in a proposal and explain how the work can be checked, shared, and understood.

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Five core topics

15.1 Building a Coherent Research Proposal
In plain English: Show how the question, rationale, evidence, methods, and ethical arrangements form a coherent proposal.

15.2 Feasibility, Piloting, Timelines, and Data Management
In plain English: Plan the time, permissions, resources, piloting, and data management needed to complete the study responsibly.

15.3 Reporting Methods, Results, Findings, and Limitations
In plain English: Describe what was done and found clearly enough for readers to assess the evidence and its limits.

15.4 Transparency, Replication, Preregistration, and Research Sharing
In plain English: Make research decisions and materials appropriately available while respecting consent and restrictions on sensitive data.

15.5 Responsible Use and Disclosure of Digital Tools and Generative AI
In plain English: Check digital and AI-assisted work for accuracy and explain how the tools were used.

About the Textbook

Foundations of Research Methods in Applied Linguistics: For EFL University Students
Prof. Munassir Alhamami · 2026 · First Edition, Version 1

Suggested citation
Alhamami, M. (2026). Foundations of research methods in applied linguistics: For EFL university students (1st ed., Version 1). Zenodo. https://doi.org/10.5281/zenodo.22944843

License
Original textbook content is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0), except where otherwise indicated. Material credited to other sources remains subject to its stated terms.

AI development assistance
The textbook discloses development assistance from ChatGPT, Claude, Gemini, and NotebookLM.

Chapter media disclosure
The chapter videos and podcasts were generated with Google NotebookLM using the textbook as their source. Narration and conversation voices are AI-generated, not recordings of the author. The original NotebookLM videos and audio are preserved unchanged; podcast audio is presented with a static textbook-cover image.

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