- Title
- Enhancing Learners’ Performance in Contest Through Knowledge Mapping Algorithm: The Roles of Artificial Intelligence and Blockchain in Scoring and Data Integrity
- Creator
- Luo, Zhilin; Shao, Xuefeng; Ma, Xiaochun
- Relation
- Journal of Organizational and End User Computing Vol. 36, Issue 1, p. 1-21
- Publisher Link
- http://dx.doi.org/10.4018/JOEUC.336277
- Publisher
- IGI Global
- Resource Type
- journal article
- Date
- 2024
- Description
- The fairness of vocational contest scoring is key to generating reliable competency assessments. This study examined the performance impact of the motivation of English-as-a-foreign-language learners in contests with vocabulary knowledge antecedents in the contexts of artificial intelligence (AI) and blockchain (BC). The sample comprised 185 participants of an oral English contest at higher vocational institution in China. AI-powered scoring of learners’ contest performance and a survey were used to collect data. The findings revealed that learners’ intrinsic drive was the main positive factor, outweighing their extrinsic motivation, and that AI and BC increased the trustworthiness and integrity of contest records, thus providing new opportunities to build learner trust and form psychological incentives. This study enriches foreign language motivation theory in the context of contest research and highlights the importance of using AI and BC to enhance the scoring accuracy and credibility of contests as authoritative evaluation instruments in vocational education.
- Subject
- artifical intelligence; blockchain; contest research; end user; learner performance; learning motivation; SDG 4; SDG 17; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1499383
- Identifier
- uon:54667
- Identifier
- ISSN:1546-2234
- Language
- eng
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