Curriculum Overview
The curriculum for the Research Methodology program at Birla Institute Of Applied Sciences is meticulously structured to provide students with a solid foundation in both theoretical and practical aspects of research while fostering innovation and creativity. The program spans eight semesters, offering a blend of core courses, departmental electives, science electives, and laboratory sessions designed to build analytical skills and research competencies.
Semester-wise Course Structure
| Semester | Course Code | Full Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | RMS101 | Introduction to Research Methodology | 3-0-0-3 | - |
| 1 | RMS102 | Scientific Writing and Communication | 2-0-0-2 | - |
| 1 | RMS103 | Data Interpretation and Visualization | 3-0-0-3 | - |
| 1 | RMS104 | Introduction to Statistics | 3-0-0-3 | - |
| 1 | RMS105 | Logic and Critical Thinking | 2-0-0-2 | - |
| 2 | RMS201 | Experimental Design and Analysis | 3-0-0-3 | RMS104 |
| 2 | RMS202 | Survey Methodology | 2-0-0-2 | RMS104 |
| 2 | RMS203 | Qualitative Research Methods | 3-0-0-3 | - |
| 2 | RMS204 | Research Ethics and Integrity | 2-0-0-2 | - |
| 2 | RMS205 | Applied Statistics with R | 3-0-0-3 | RMS104 |
| 3 | RMS301 | Causal Inference Techniques | 3-0-0-3 | RMS201, RMS202 |
| 3 | RMS302 | Mixed Methods Research | 2-0-0-2 | RMS203 |
| 3 | RMS303 | Advanced Data Analysis | 3-0-0-3 | RMS205 |
| 3 | RMS304 | Research Project I (Mini) | 2-0-0-2 | - |
| 3 | RMS305 | Computational Methods in Research | 3-0-0-3 | RMS104, RMS205 |
| 4 | RMS401 | Policy Evaluation and Impact Assessment | 3-0-0-3 | RMS301 |
| 4 | RMS402 | Behavioral Analytics in Digital Environments | 2-0-0-2 | RMS302 |
| 4 | RMS403 | Research Project II (Mini) | 2-0-0-2 | - |
| 4 | RMS404 | Research Internship | 4-0-0-4 | RMS304, RMS403 |
| 5 | RMS501 | Advanced Topics in Quantitative Research | 3-0-0-3 | RMS303 |
| 5 | RMS502 | Ethnographic Fieldwork | 2-0-0-2 | RMS203 |
| 5 | RMS503 | Thesis Preparation and Supervision | 4-0-0-4 | - |
| 6 | RMS601 | Thesis Project | 8-0-0-8 | RMS503 |
| 6 | RMS602 | Research Presentation and Defense | 2-0-0-2 | - |
| 6 | RMS603 | Capstone Workshop | 2-0-0-2 | - |
| 7 | RMS701 | Advanced Research Seminars | 2-0-0-2 | RMS601 |
| 7 | RMS702 | Research Ethics and Governance | 2-0-0-2 | - |
| 8 | RMS801 | Final Thesis Defense | 4-0-0-4 | RMS601 |
| 8 | RMS802 | Research Portfolio Development | 2-0-0-2 | - |
| 8 | RMS803 | Alumni Mentorship Program | 2-0-0-2 | - |
Detailed Course Descriptions
Below are detailed descriptions of several advanced departmental elective courses offered in the program:
- Advanced Topics in Quantitative Research (RMS501): This course delves into sophisticated statistical modeling techniques such as multilevel modeling, Bayesian inference, and time series analysis. Students will learn how to apply these methods to complex datasets from various domains including economics, medicine, and social sciences. The course emphasizes practical implementation using R and Python.
- Ethnographic Fieldwork (RMS502): Designed for students interested in qualitative research, this course introduces ethnography as a methodological tool for understanding human behavior and cultural contexts. Through fieldwork exercises and case studies, participants will develop skills in participant observation, interview techniques, and cultural analysis.
- Research Ethics and Governance (RMS702): This course explores ethical dilemmas and governance frameworks in research across different disciplines. Topics include data privacy, informed consent, conflict of interest, and regulatory compliance. The course includes interactive sessions with ethicists and regulatory experts from academia and industry.
- Policy Evaluation and Impact Assessment (RMS401): This course focuses on evaluating the effectiveness of public policies through rigorous impact assessment techniques. Students will learn about randomized controlled trials, difference-in-differences methods, and regression discontinuity designs. The curriculum includes real-world case studies from government agencies and international organizations.
- Behavioral Analytics in Digital Environments (RMS402): This course examines how digital platforms influence human behavior and decision-making. Students will analyze user data from social media, e-commerce sites, and mobile apps to uncover patterns in consumer preferences and engagement behaviors.
Project-Based Learning Philosophy
The department’s philosophy on project-based learning is grounded in the belief that students learn best when they actively engage with real-world problems. Mini-projects are introduced early in the program to help students develop foundational research skills, while capstone projects in the final year allow them to apply advanced methodologies to significant issues within their chosen field.
Mini-projects typically span two semesters and involve small teams working under faculty supervision on defined research questions. These projects culminate in a written report and presentation, providing students with experience in all stages of the research process from problem identification to dissemination of findings.
The final-year thesis project is a substantial piece of original research that requires students to independently design and execute a study, collect and analyze data, and present their findings in a formal dissertation. Faculty mentors guide students throughout this process, ensuring they meet academic standards while encouraging innovation and critical thinking.
Project selection involves a combination of student interest, faculty availability, and alignment with current research initiatives at the Institute. Students are encouraged to propose projects that bridge multiple disciplines or address societal challenges, promoting interdisciplinary collaboration and applied research.