A proposal of recommendation function for element fill-in-Blank problems in java programming learning assistant system. Issue 2 (5th April 2021)

• Record Type: Journal Article
• Authors: Wint, Su Sandy; Funabiki, Nobuo
• Is Part Of: International journal of web information systems. Volume 17:Issue 2(2021)
• Page Start: 140
• Page End: 152
• Publication Date: 2021-04-05
• Subjects: JavaScript -- Java programming -- JPLAS -- Element fill-in-blank problem -- Offline answering function -- Recommendation function; World Wide Web -- Periodicals; Internet -- Periodicals; Information storage and retrieval systems -- Periodicals; 004.678
• DOI: 10.1108/IJWIS-11-2020-0070
• Languages: English
• ISSNs: 1744-0084

Abstract

Abstract : Purpose: To advance Java programming educations, the authors have developed a Web-based Java programming learning assistant system (JPLAS). It offers the element fill-in-blank problem (EFP) for novice students to study Java grammar and basic programming skills by filling in the missing elements in a source code. An EFP instance can be generated by selecting an appropriate code, and applying the blank element selection algorithm. As it is expected to cover broad grammar topics, a number of EFP instances have been generated. This paper aims to propose a recommendation function to guide a student solving the proper EFP instances among them. Design/methodology/approach: This function considers the difficulty level of the EFP instance and the grammar topics that have been correctly answered by the student, and is implemented at the offline answering function of JPLAS using JavaScript so that students can use it even without the Internet connections. Findings: To evaluate the effectiveness of the proposal, 85 EFP instances are prepared to cover various grammar topics, and are assigned to a total of 92 students in two universities in Myanmar and Indonesia to solve them using the recommendation function. Their solution results confirmed the effectiveness of the proposal. Originality/value: The concept of the difficulty level for an EFP instance is newly defined for the proper recommendation, and the accuracy in terms of the average numbers of answer submission times among the students is verified.