Predicting abandonment in online coding tutorials

An Yan, Michael J. Lee, Andrew J. Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Learners regularly abandon online coding tutorials when they get bored or frustrated, but there are few techniques for anticipating this abandonment to intervene. In this paper, we examine the feasibility of predicting abandonment with machine-learned classifiers. Using interaction logs from an online programming game, we extracted a collection of features that are potentially related to learner abandonment and engagement, then developed classifiers for each level. Across the first five levels of the game, our classifiers successfully predicted 61% to 76% of learners who did not complete the next level, achieving an average AUC of 0.68. In these classifiers, features negatively associated with abandonment included account activation and help-seeking behaviors, whereas features positively associated with abandonment included features indicating difficulty and dis-engagement. These findings highlight the feasibility of providing timely intervention to learners likely to quit.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2017
EditorsPeter Rodgers, Austin Z. Henley, Anita Sarma
PublisherIEEE Computer Society
Pages191-199
Number of pages9
ISBN (Electronic)9781538604434
DOIs
StatePublished - Nov 9 2017
Event2017 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2017 - Raleigh, United States
Duration: Oct 11 2017Oct 14 2017

Publication series

NameProceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC
Volume2017-October
ISSN (Print)1943-6092
ISSN (Electronic)1943-6106

Other

Other2017 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2017
CountryUnited States
CityRaleigh
Period10/11/1710/14/17

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Human-Computer Interaction
  • Software

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