Attitudes towards student-centered learning with Jupyter notebooks in econometrics: a semantic analysis

Abstract

Jupyter notebook is an interactive web-based programming environment commonly used in data science to facilitate learning and teaching of programming. By providing a single intelligible and reproducible environment to conduct empirical analyses and simulation studies, Jupyter notebook has only recently been adapted for econometrics instruction. This paper documents the students’ experiences using Jupyter notebook in a postgraduate introductory econometrics course using a qualitative thematic analysis methodology that transcribed and coded 27 one-to-one interviews with ten students throughout the academic term. The results show that: (1) The Jupyter notebook-based learner-centered design pedagogy increased students’ autonomies in the learning process; (2) students developed confidence throughout the learning process; (3) interactive learning tools were effective in supporting students’ econometrics learning.