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

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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 Those tools though still have a significant setup cost, are already out-of-date or require already preprocessed data as a starting point.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/.

Original languageEnglish
Title of host publicationLAK 2020 Conference Proceedings - Celebrating 10 years of LAK
Subtitle of host publicationShaping the Future of the Field - 10th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery (ACM)
Pages502-511
Number of pages10
ISBN (Electronic)9781450377126
DOIs
Publication statusPublished - 23 Mar 2020
Event10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020 - Frankfurt, Germany
Duration: 23 Mar 202027 Mar 2020

Conference

Conference10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020
CountryGermany
CityFrankfurt
Period23/03/2027/03/20

Keywords

  • Edx log
  • Learning analytics
  • Log data analysis
  • Massive open online course

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    Torre, M. V., Tan, E., & Hauff, C. (2020). EdX log data analysis made easy: Introducing ELAT: An open-source, privacy-aware and browser-based edX log data analysis tool. In LAK 2020 Conference Proceedings - Celebrating 10 years of LAK: Shaping the Future of the Field - 10th International Conference on Learning Analytics and Knowledge (pp. 502-511). Association for Computing Machinery (ACM). https://doi.org/10.1145/3375462.3375510