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Analysis of Learner Timeout Behavior in Online Tests of a Bigdata Set Based on the OLAI Concept

  • Huixiao Le
  • Jiyou Jia
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 843)

Abstract

Based on a dataset of more than 7.4 million records of learners’ online tests activity in an online platform, and the concept of Online Learning Activity Index (OLAI) proposed by Jia and Yu (2017a and b), this paper analyzes the learners’ timeout behaviors in online tests. Descriptive statistics and correlation analysis are conducted to find the general pattern and characteristics underneath the cases, for example, whether the amount of questions in a test influences learners’ timeout behaviors. Taking OLAI and its three dimensions as the features, it’s hard to find any significant distinction between the LTBs (Learner with Timeout Behaviors), and LNTBs (Learner with No Timeout Behaviors). However, learners may be more likely to cease answering questions when facing a test with a large number of questions. The findings’ implication for online learning system design is discussed and further work is suggested.

Keywords

Online learning Online learning activity index OLAI  Learning analytics Timeout behaviors 

Notes

Acknowledgement

This research is supported by the project, “Lexue 100, Smart Education”, of Beijing Lexue 100 Online Education Co., Ltd. The authors thank also all the teachers and students who have participated in the program.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Educational Technology, Graduate School of EducationPeking UniversityHai Dian, BeijingChina

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