Mining the patterns of graduate students' self-regulated learning behaviors in a negotiated online academic reading assessment

Xiaotong Zhang, Hercy N.H. Cheng

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

Abstract

Online academic reading assessments can test graduate students' reading ability, while the results of tests as a feedback can help students reflect on their own ability, realize their weaknesses, and then take actions to improve their ability. These behaviors form the basis of self-regulated learning ability. In this paper, a negotiated online reading assessment system is developed to provide students with the function of self-assessment and reflection. For designing the system, the authors use the concept of a negotiated learner model, so that students may negotiate with the system and try to reach an agreement. In order to explore the differences in students' learning behaviors in such a system, the authors used the hidden Markov Model to construct the behavioral model of students' self-regulated learning ability. Furthermore, the authors differentiated the negotiation behaviors of students with high and low self-regulated learning ability in the reading assessment system. The results showed that the students in the high and low self-regulated learning ability groups shared the behaviors of peer comparison and retesting. The high selfregulated learning group tended to transit among retesting, peer comparison, test reflection, and self-assessment. The students in the low self-regulated learning group tended to transit among retesting, peer comparison, viewing grades, and self-reflection. The results indicated that the students tended to re-test to negotiate with the system, and that the students in the high self-regulated learning group may reflect on learning through negotiation and further plan their learning strategies.

Original languageEnglish
Title of host publicationProceedings of 2019 the 3rd International Conference on E-Society, E-Education and E-Technology, ICSET 2019
PublisherAssociation for Computing Machinery, Inc
Pages109-114
Number of pages6
ISBN (Electronic)9781450372305
DOIs
Publication statusPublished - Aug 15 2019
Externally publishedYes
Event3rd International Conference on E-Society, E-Education and E-Technology, ICSET 2019 - Taipei, Taiwan
Duration: Aug 15 2019Aug 17 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd International Conference on E-Society, E-Education and E-Technology, ICSET 2019
Country/TerritoryTaiwan
CityTaipei
Period8/15/198/17/19

Keywords

  • Hidden Markov model
  • Negotiated learner models
  • Online reading assessment
  • Self-regulated learning

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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