Kathan Shukla

Enterprise and Innivations in Education (offered to PGP, PGPX, PGP-FABM students)

This course provides an overview of India's educational sector. Critical issues of this sector are discussed from viewpoints of multiple stakeholders – from students, parents, teachers to policymakers and administrators. We also look at the existing innovative practices at various levels of education. Students are expected to come up with enterprising solutions for the problems they identify and demonstrate their understanding of the ecology of educational sector.

Course syllabus is available here. 

Gamification, Technology and Learning Motivation (offered to PGP, PGPX, PGP-FABM students)

Motivating and engaging individuals for learning new things is often essential for organizations that strive for growth. Gamification provides a useful mechanism in this regard and is increasingly being employed across the fields of education, health, public services, business and management. It is the application of game design elements in real-world context to motivate user behaviours. This course provides an opportunity to develop an understanding of gamification, human learning and motivation theories and then apply this knowledge to devise and conduct interventions for improving academic as well as non-academic outcomes of students particularly those from underserved communities. 

Course syllabus is available here.

How to Motivate Students for Learning? [Offered to PhD students]

This course provides an opportunity to develop an in-depth understanding of human learning and motivation theories and then apply this knowledge to make a meaningful contribution to the lives of students from the local schools.  

Course syllabus is available here. 

Applied Quantitative Techniques for Educational Research (offered to PhD students)

Regression analysis is one of the most commonly used quantitative techniques used across various fields such as economics, education, psychology, sociology, and business. The course is designed to help students become more informed consumers of research and be able to apply these analytic techniques in educational/psychological research. Topics covered in the course will include: univariate and multivariate analysis of variance (ANOVA & MANOVA), simple regression, multiple regression (MR) analysis, moderation effects, regression diagnostics, the use of categorical independent variables, curvilinear regression analysis, modelling binary outcomes (logistic regression), Poisson and negative binomial regression, direct and indirect effects of predictor on the outcome variable of interest. The course will be based on a combination of theoretical and practice-oriented sessions that will provide working knowledge of statistical software like SPSS and R.

Course syllabus is available here.

Structural Equation Modeling (offered to PhD students)

The course builds on the insights and knowledge obtained in first year research methodology courses (Survey of Statistical Methods, Introduction to Research Methods and Qualitative Techniques) and provides a hands-on training of Structural Equation Modeling (SEM). The course shall introduce the participants to survey-based research designs and the SEM analytic technique used to analyze the data collected. The course shall provide inputs relating to measurement theory and ways to incorporate them in our analysis. The course will be based on a combination of theoretical and practice-oriented sessions that will provide working knowledge of statistical software like SPSS, AMOS and Mplus.

Course syllabus is available here.