Constructs Syllabus PDF

Statistics --Meaning, Definition, Scope, Statistics in Social Science - Nature, Use and Limitations, Interpreting information in social science- Meaning, concept and importance, Measures of Central Tendency- Mean, Median and Mode- Merits and Demerits, Measures of Dispersion- Mean Deviation, Standard...

Statistics --Meaning, Definition, Scope, Statistics in Social Science - Nature, Use and Limitations, Interpreting information in social science- Meaning, concept and importance, Measures of Central Tendency- Mean, Median and Mode- Merits and Demerits, Measures of Dispersion- Mean Deviation, Standard Deviation, Correlation-Meaning and types, Karl Pearson's Correlation, Spearman's Rank Correlation Introduction to Data Interpretation and Decision Making- Types of Data in Social Science Research-Quantitative data: Methods of collection, analysis, and interpretation, Qualitative data: Approaches to analyzing and interpreting qualitative information- Visualization Techniques: Graphs, charts, and tables for representing data, Importance of effective visualization in conveying research findings - Interpretation of charts and graphs, Data Interpretation in Social Context: Considering cultural, historical, and social factors in data interpretation-Ethical considerations in interpreting social science data. Decision-Making Models in Social Science Research: Rational decision-making models-Bounded rationality and decision-making under uncertainty. E-learning and E-contents -- Introduction, Concept &Importance, Introduction to E-Content Integration in Statistics- Defining e-content and its role in modern research-Overview of the significance of statistics in social science Theoretical basis of developing E-content, Digital Resources for Statistical Learning- Online courses and tutorials in statistics- Interactive e- books and educational websites. Integration of E-Content in Statistics Education -Incorporating e-content in traditional classroom settings - Online platforms for statisticaleducation. Learning Management systems (LMS, Interaction in virtual environments, E-learning analytics-Mobile learning- Advantages and Challenges of integrating an E- contentin Statistics, Online classroom management. Pedagogy -- Meaning, nature, types and characteristics- Introduction to Pedagogical Design in Statistics Education: The significance of effective pedagogy in teaching statistics- Overview of the role of pedagogical aspects in statistical learning packages. Multi modal Content Delivery in Statistics. Pedagogical principles in online education, Application of pedagogical approaches-5E, 7E, 9E, ADDIE model, Bloom's digital taxonomy, Successive Approximation Model, Community of Inquiry Model, Universal Design for Learning (UDL) Significance of an e-content integrated learning package. Application of Statistics in real- world scenarios. Continuous Improvement and Evaluation in Statistics Education Introduction to Recent Developments in Statistical Methods - The dynamic nature of statistical methods in social science research. Advancements in Bayesian Statistics - Bayesian approaches in social science research - Applications and benefits of Bayesian statistical methods- Machine Learning in Social Science Statistics- Advanced data visualization- Challenges and opportunities handling large-scale data set in social science research - Web- Based Statistical Tools and Software - SPSS, STATA, R, MS Excel, Tableau, JAMOVI, JASP, SAS, IBMSPSS,MATLAB, JMP,HLM (Hierarchical Linear Modeling), M plus- Advantages and limitations of using web-based tools for statistical analysis -Significance of discussion of results - Ethical considerations in statistical analysis, Impact of Recent Developments on Social Science Research: Evaluating the influence of new statistical methods on research outcomes- Implications for advancing knowledge in social science disciplines.