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IJIET 2012 Vol.2(5): 547-551 ISSN: 2010-3689
DOI: 10.7763/IJIET.2012.V2.202

The Development of Intelligent Computer-Assisted Efficient Using the Tree Data Structure: The Case Study of the Religion Societies and Culture Subject

O. Thinnukool and K. Champhorm

Abstract—The constructions of Intelligent Computer Assistance-Instruction (iCAI) are practically less use in Thai education because they are required programming skills. The purposes of this research are developing, testing and measuring the efficiency of iCAI, especially in the religion societies and culture subject. It is constructed with the program that is supported. The tree data structure is able to respond with individual varieties. The stratified random sampling technique has been applied to measure the proposed iCAI according to sixth-grade students data. An instrument test by population is classified with GPA. The samples divided into three groups; smart, medium and low. To examine the efficiency of the iCAI lessons, The 80/80 standard criterion was used. A result of the study is 84.21/83.33, which is higher than the preset criterion of 80/80 standard it can be the theoretically substituted regular lesson. The students who studied by using iCAI had higher learning effectiveness than the students who studied in normal learning program at 0.1 of statistical significance.

Index Terms—Intelligent Computer Assistance-Instruction (iCAI), Tree Data Structure, Efficiency of a Lesson.

O. Thinnukool is with Prince of Songkhla University (webppu@hotmail.com).
K. Champhorm is with department of Education Communication and Technology Thaksin University.

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Cite: O. Thinnukool and K. Champhorm, "The Development of Intelligent Computer-Assisted Efficient Using the Tree Data Structure: The Case Study of the Religion Societies and Culture Subject," International Journal of Information and Education Technology vol. 2, no. 5, pp. 547-551, 2012.

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Jon-Chao Hong
  • Managing Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2023: 2.8), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net

 

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