Volume 14 Number 11 (Nov. 2019)
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JCP 2019 Vol.14(11): 624-633 ISSN: 1796-203X
doi: 10.17706/jcp.14.11.624-633

Identification of Factors Affecting Cognitive Load in Programming Learning with Decision Tree

So Asai1, Dinh Thi Dong Phuong2, Hiromitsu Shimakawa1
1Ritsumeikan University, Kusatsu, Shiga, Japan.
2Paracel Technology Solutions Co., Ltd, Da Nang, Vietnam.

Abstract—We propose a method to identify cognitive load and its factors affecting learning efficiency in programming learning from learning behavior by learners. In general, since concepts of programming is difficult, some learners suffer inappropriate cognitive load to understand them. Although teachers must keep the cognitive load of such learners appropriate, it is difficult for them to find learners under inappropriate cognitive load from a large number of learners. In order to find learners with inappropriate cognitive load, decision trees generated from learning behavior when learners solve fill-in-the-blank tests identifies cognitive load. An experiment shows that the decision trees generated by our method identify factors of cognitive load for IL and GL. This result clarifies learning factors affecting cognitive load of learners and lets the teachers can take measures to their cognitive load appropriate.

Index Terms—Decision tree analysis, e-learning, machine learning, programming learning.

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Cite: 作者, "Identification of Factors Affecting Cognitive Load in Programming Learning with Decision Tree," Journal of Computers vol. 14, no. 11, pp. 624-633, 2019.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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