Introduction to Research Methods
Introduction to Research Methods
RES799 - Graduate Course
Fall 2025
Course Description
The course teaches research methods applicable to scientific research in general, and AI research in particular. It covers various topics including quantitative, qualitative, and mixed methods, measurement and metrics in experimental research, critical appraisal and peer review, public communication, reproducibility and open science, and ethical issues in AI research. Students will gain knowledge in selecting, evaluating, collecting and sharing data and suitable research methods to address specific research questions. After completing the course, students will have the skills to develop a full research methodology that is rigorous and ethical.
Course Team
Assistant Professor, NLP & Speech @ MBZUAI
Learning Objectives
- Formulate a research question and design an experimental study by identifying suitable research methods and instruments.
- Conduct a literature search and identify related work.
- Identify and discuss the limitations of existing research methods through peer review.
- Communicate research findings effectively to fellow researchers through written and verbal communication.
- Understand and discuss research ethics, academic integrity principles, and the ethical implications of AI research.
Teaching Plan
| Week | Topics | Assessment |
|---|---|---|
| 1 | Lecture 1: Introduction / Philosophical
Foundations, the scientific
method, ontological and epistemological
assumptions, the role of the researcher
(positionality), alternative perspectives
Lecture 2: Quantitative Research Methods, Principles, Experimental design, Types of variables, Sampling methods, Data collection methods, agreement/reliability, Evaluation metrics, Types of validity. |
N/A |
| 2 | Lecture 3: Quantitative Research Methods
(cont.), descriptive statistics, visualization,
statistical inference, hypothesis testing,
confidence intervals, effect size,
correlation/regression
Lecture 4: Quantitative Research Methods advanced topics: longitudinal and crosssectional studies, multi-variate, more advanced visualization, examples\\critiques from AI research |
Homework 1 |
| 3 | Lecture 5: Qualitative research principles
and approaches, common types of
qualitative studies, participant selection in
qualitative research, examples from AI
research
Lecture 6: Qualitative research (cont.), qualitative data analysis methods, interpreting and presenting qualitative findings, mixed-methods research |
N/A |
| 4 | Lecture 7: Academic integrity, MBZUAI
library resources, Literature survey (types
of survey papers), the ethics of generative
AI in research
Lecture 8: Research communication & Paper writing (best practices) |
Homework 2 |
| 5 | Lecture 9: Replication and Reproducibility
in Research
Lecture 10: Open science and FAIR data |
N/A |
| 6 | Lecture 11: The publication process
Lecture 12: Peer review |
Homework 3 |
| 7 | Lecture 13: Core ethical principles,
Research ethics, informed consent,
confidentiality, IRB process, Ethical issues
in AI and digital research
Lecture 14: AI ethics (guest lecture) |
Quiz |
Course Materials
- Sharon M. Ravitch. Reason & Rigor: How Conceptual Frameworks Guide Research,2011.1st edition. Sage Publications.
- Michael P. Marder, Research Methods for Science. Cambridge University Press, 2012.Online ISBN 9781139035118
Assignments and Projects
Homework 1: Quantitative Research Analysis
Opened: Tuesday, 26 August 2025, 12:00 AM Due:Friday, 5 September 2025, 11:59 PM
Write about your thesis research question, data, instruments (metrics or other evaluation methods), and experimental design. Make sure to follow best practices in your experimental design as discussed during class, and justify the choices you make.
You can use this overleaf template or something similar.
Content: 3-4 pages (~1500-2000 words) + references (IEEE style).
NOTE: Please fill, sign, and submit the AI declaration form - submissions will not be accepted without this.
Evaluation Criteria: formatting, completeness, soundness of experimental design, depth of discussion (applying what's learned in class), writing clarity, completion and appropriateness of references.
Homework 2: Literature Review and Research Communication
Opened: Tuesday, 9 September 2025, 12:00 AM Due: Friday, 19 September 2025, 11:59 PM
Retrieve related work to your research topic, identify related methods and research gaps, and write a summary of this literature (~500 words), with appropriate citations. Use the same Overleaf template used for Homework 1. Sign and include the AI declaration form in your submission.
In addition to the above, submit another file detailing your literature review methodology: how did you find the papers, why did you select these specific papers, how did you extract information from the papers, and which tools did you use in your work? What are the limitations of your methodology? Be as detailed as possible in this.