A Learner Model Integrating Cognitive and Metacognitive and Its Application on Scratch Programming Projects

Sifeng Jing, Ying Tang, Xiwei Liu, Xiaoyan Gong

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

Abstract

learner's cognitive and metacognitive are key personal profile for individualized teaching. To evaluate learner's comprehensive characteristics, existing learner model were reviewed. Two challenges of constructing an accurate and comprehensive learner model integrating cognitive and metacognitive were summarized. A plan of constructing a comprehensive learner model was made based on analysis of existing massive online learning environment, sensor information technology and educational data-mining. As a case study, a method of how to map learning data onto learners' cognitive and metacognitive was proposed based on an analysis of a number of pupils' Scratch projects. Three mapping table were established. Pupil's cognitive skill could be evaluated from technology shown from Scratch project, namely, data structure, algorithm, computational practices and overall evaluation. Content shown from Scratch project were used to infer pupil's cognitive style. Meta-cognitive ability can be measured from computational practices and behavior in programming process.

Original languageEnglish (US)
Pages (from-to)644-649
Number of pages6
JournalIFAC-PapersOnLine
Volume53
Issue number5
DOIs
StatePublished - 2020
Event3rd IFAC Workshop on Cyber-Physical and Human Systems, CPHS 2020 - Beijing, China
Duration: Dec 3 2020Dec 5 2020

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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