AI-Based Questionnaire Design and Data Science in Social Science Research

Three-Month Hybrid Course Syllabus

Title: AI-Based Questionnaire Design and Data Science in Social Science Research

Course Duration: 3 Months (12 Weeks)

Mode: Hybrid (Online + Offline/Practical Sessions)

Weekly Structure: 2–3 hours per week (Total ~60 hours)

Components: Theory (40%) + Practical (60%) + Project

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Course Objectives

* To understand scientific questionnaire construction using AI

* To integrate psychology, Rabindrik values, and data science

* To design rank-based and adaptive questionnaires

* To apply R/Excel for psychometric and AI-based analysis

* To develop job-ready skills in research, analytics, and assessment

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Eligibility of Students

* Undergraduate (UG) students in Psychology, Education, Sociology, Management, or related fields

* Postgraduate (PG) students and PhD aspirants in Social Sciences

* Basic knowledge of statistics (mean, correlation) preferred

* No prior coding required (R/Excel will be taught from basics)

* Professionals working in HR, education, NGOs, or industry safety can also apply

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Course Structure (Month-wise)

Month 1: Foundations of AI and Questionnaire Design

Theory Topics

* Basics of Social Science Research and Measurement

* Types of Questionnaires (Likert, Ranking, Paired Comparison)

* Introduction to AI in Social Science Research

* Constructs and Scale Development (Safety, Personality, Values)

* Rabindrik Value Orientation: Murta, Raag, Saraswat

Practical Components

* Generating questionnaire items using AI tools

* Creating item pools in Excel

* Designing Likert-scale and rank-based questionnaires

* Introduction to R (basic commands, data handling, CSV files)

* Data entry and cleaning

Output

* Draft questionnaire on Safety Psychology / Value Orientation

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Month 2: AI-Based Validation and Rank Data Analytics

Theory Topics

* Reliability (Cronbach’s Alpha, Split-half)

* Validity (Content, Construct, Criterion)

* Introduction to Psychometrics and IRT

* Rank-Based Data Analysis Concepts

* AI in Item Validation and Bias Detection

Practical Components

* Reliability analysis using R (psych package)

* Factor analysis / clustering basics

* Designing paired comparison questionnaires

* Rank data handling in Excel

* Introduction to Bradley-Terry model (conceptual)

* Text analysis using AI for item validation

Output

* Validated questionnaire with reliability report

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Month 3: Adaptive Testing and AI Applications

Theory Topics

* Computer Adaptive Testing (CAT)

* Personalized Assessment Systems

* AI in Multilingual Questionnaire Design

* Integration with Behavioral and Safety Data

* Ethics in AI-based Research

Practical Components

* Designing adaptive questionnaire flow (logic-based)

* Basic machine learning concepts (classification, clustering)

* Applying simple ML models (guided)

* Data visualization in Excel/R

* Final project development

Output

* Final Project: AI-based Questionnaire + Data Analysis Report

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Project Work (Compulsory)

Students will complete one of the following:

* AI-based Safety Psychology Assessment Tool

* Rabindrik Value Orientation Rank-Based Scale

* Career Counseling Questionnaire using AI

* Educational Motivation Assessment Model

Deliverables:

* Questionnaire tool

* Dataset (real/simulated)

* Analysis report

* Presentation

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Teaching Methodology

* Hybrid lectures (online + occasional offline workshops)

* Hands-on practice using real datasets (RPRIT datasets can be used)

* AI-assisted learning (ChatGPT, NLP tools)

* Case studies (industrial safety, education, rural development)

* Mentored project work

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Software and Tools

* Excel (primary tool for beginners)

* R (for statistical and psychometric analysis)

* AI tools (ChatGPT or similar for item generation)

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Assessment Method

* Assignments (30%)

* Practical Work (30%)

* Final Project (40%)

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Job Opportunities and Career Scope

This course is strongly job-oriented and aligned with emerging roles:

1. Data Analyst (Social Science / Education / HR)

* Work with survey and behavioral data

* Use Excel/R for analysis and reporting

2. Research Assistant / Project Fellow

* Work in universities, NGOs, think tanks

* Assist in questionnaire design and data analysis

3. HR Analytics and Assessment Specialist

* Design employee surveys and psychometric tools

* Use AI-based assessment for recruitment and training

4. Safety and Industrial Psychology Analyst

* Apply questionnaire tools in industries (power plants, factories)

* Analyze safety behavior and risk patterns

5. Career Counselor (Data-Driven)

* Use AI-based questionnaires for student profiling

* Provide evidence-based career guidance

6. EdTech and Assessment Content Developer

* Design digital questionnaires and adaptive tests

* Work with online learning platforms

7. Freelance Research Consultant

* Develop questionnaires for dissertations and projects

* Offer data analysis services

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Key Advantage for Students

* Hands-on AI application in social science

* Exposure to real datasets (safety, education, values)

* Skill development in R and Excel

* Portfolio-ready project

* Strong foundation for PhD and research careers

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This course can be positioned as a bridge between psychology, data science, and AI-driven assessment, making students both academically strong and industry-ready.