How Reproducible Research Leads to Non‑Rote Learning Within Socially Constructivist Statistics Education


  • Patrick Wessa


statistics education, reproducible research, reproducible computing, social constructivism, non-rote learning


This paper discusses the implementation of a new e‑learning environment that supports non‑rote learning of exploratory and inductive statistics within the pedagogical paradigm of social constructivism. The e‑ learning system is based on a new computational framework that allows us to create an electronic research environment where students are empowered to interact with reproducible computations from peers and the educator. The underlying technology effectively supports social interaction (communication), knowledge construction, collaboration, and scientific experimentation even if the student population is very large. In addition, the system allows us to measure important aspects of the actual learning process which are otherwise unobservable. With this new information it is possible to explore (and investigate) the effectiveness of e‑based learning, the impact of software usability, and the importance of knowledge construction through various feedback and communication mechanisms. Based on a preliminary empirical analysis from two courses (with large student populations) it is shown that there are strong relationships between actual constructivist learning activities and scores on objective examinations, in which the questions assess conceptual understanding. It is also explained that non‑rote learning is supported by the fact that the system allows users to reproduce results and reuse them in derived research that can be easily communicated.



1 Jun 2009