Assessment of pedagogical and Technical Quality of Generative AI Response in Java OOP.
In this study, we examine the quality of answers returned by AI language models (GenAI) to Java Object-Oriented Programming (OOP) questions. A 20-question package was developed, including questions on Classes, Objects, Encapsulation, Inheritance Polymorphism and Constructors. Each GA was then rated...
| Published in: | Journal of Humanities & Social Sciences Studies (JHSSS) Vol. 8; no. 3; pp. 1 - 7 |
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| Format: | Article |
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Al-Kindi Center for Research & Development
2026
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=192249232&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 192249232 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 26637197 MZ5F jtl: Journal of Humanities & Social Sciences Studies (JHSSS) issn: 26637197 maglogo: N pubinfo: dt: 2026 vid: 8 iid: 3 pid: 62593 pub: Al-Kindi Center for Research & Development artinfo: ui: 192249232 10.32996/jhsss.2026.8.3.1 ppf: 1 ppct: 6 formats: tig: atl: Assessment of pedagogical and Technical Quality of Generative AI Response in Java OOP. aug: au: Alshboul, Hadeel affil: The World Islamic Sciences and Education University, Computer Science Department, Amman-Jordan su: Generative artificial intelligence Object-oriented programming Computer software quality control Hallucinations (Artificial intelligence) Educational quality sug: subj: Generative artificial intelligence Object-oriented programming Computer software quality control Hallucinations (Artificial intelligence) Educational quality keyword: AI Evaluation Generative AI Java OOP Programming Education ab: In this study, we examine the quality of answers returned by AI language models (GenAI) to Java Object-Oriented Programming (OOP) questions. A 20-question package was developed, including questions on Classes, Objects, Encapsulation, Inheritance Polymorphism and Constructors. Each GA was then rated with respect to the MAs and SAs in terms of (a) how correct it was; (b) how much understanding it revealed; (c) how clear it is; (d) if included code, whether the code quality was acceptable; and also, in terms of potential "hallucination." The experimental results demonstrate that GenAI generates high-quality answers, especially in the correctness and conceptual depth aspects, but may fail to make a clear response for questions of complex semantics. The research offers a transferable model for AI evaluation in education. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2026 holdings: @attributes: islocal: N |
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