EdX log data analysis made easy

Introducing ELAT: An open-source, privacy-aware and browser-based edX log data analysis tool

Conference Paper (2020)
Author(s)

Manuel Valle Torre (TU Delft - Web Information Systems)

Esther Tan (TU Delft - Web Information Systems)

C Hauff (TU Delft - Web Information Systems)

Research Group
Web Information Systems
DOI related publication
https://doi.org/10.1145/3375462.3375510
More Info
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Publication Year
2020
Language
English
Research Group
Web Information Systems
Pages (from-to)
502-511
ISBN (electronic)
9781450377126

Abstract

Massive Open Online Courses (MOOCs), delivered on platforms such as edX and Coursera, have led to a surge in large-scale learning research. MOOC platforms gather a continuous stream of learner traces, which can amount to several Gigabytes per MOOC, that learning analytics researchers use to conduct exploratory analyses as well as to evaluate deployed interventions. edX has proven to be a popular platform for such experiments, as the data each MOOC generates is easily accessible to the institution running the MOOC. One of the issues researchers face is the preprocessing, cleaning and formatting of those large-scale learner traces. It is a tedious process that requires considerable computational skills. To reduce this burden, a number of tools have been proposed and released with the aim of simplifying this process. Those tools though still have a significant setup cost, are already out-of-date or require already preprocessed data as a starting point. In contrast, in this paper we introduce ELAT, the edX Log file Analysis Tool, which is browser-based (i.e., no setup costs), keeps the data local (i.e., no server is necessary and the privacy-sensitive learner data is not send anywhere) and takes edX data dumps as input. ELAT does not only process the raw data, but also generates semantically meaningful units (learner sessions instead of just click events) that are visualized in various ways (learning paths, forum participation, video watching sequences). We report on two evaluations we conducted: (i) a technological evaluation and a (ii) user study with potential end users of ELAT. ELAT is open-source and available at https://mvallet91.github.io/ELAT/.

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