Integration of AI Tutoring in Assessment Designs for Adult Learners

• Published in: SN computer science Vol. 6; no. 5; p. 418
• Main Authors: Por, Fei Ping, Kanesin, Thoolasi, Law, Loy Fah
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 01.06.2025; Springer Nature B.V
• Subjects: Adult learning; Adult students; Agile-blended Learning with Technology; Algorithms; Artificial intelligence; Between-subjects design; Chatbots; Colleges & universities; Computer Imaging; Computer Science; Computer Systems Organization and Communication Networks; Critical thinking; Data Structures and Information Theory; Education; Feedback; Generative artificial intelligence; Information Systems and Communication Service; Knowledge; Learning; Machine learning; Natural language processing; Original Research; Pattern Recognition and Graphics; Professionals; Skills; Software Engineering/Programming and Operating Systems; Teaching; Tutoring; Variance analysis; Vision; AI tutoring; Adult learners; Artificial intelligence; Assessment designs
• ISSN: 2661-8907; 2662-995X; 2661-8907
• DOI: 10.1007/s42979-025-03973-8

This study aims to investigate the main and interaction effects of assessment designs (authentic and non-authentic) with the integration of AI tutoring and Cumulative Grade Point Average (CGPA) on adult learners’ assignment marks. Due to work requirements and career advancement, there is an increasing trend for working adults to opt for further study in order to develop their functioning knowledge. The common assessment designs employed in universities to measure the achievement of course learning outcomes are authentic and non-authentic assessments. Authentic assessment contextualizes learning and the assignment tasks require the application of knowledge and skills in real-world scenarios; while for non-authentic assessment, standardized testing is administered with the emphasis on recalling facts. As artificial intelligence has penetrated education, the assessment designs in this study integrated AI tutoring to allow adult learners to consult the Gen-AI tutor for prompt guidance at any time. The impact of AI tutoring on both assessment designs has also been reviewed in this study. The two-way between-subjects analysis of variance (ANOVA) was employed to compute the main and interaction effects on 202 participants who enrolled in Diploma of Early Childhood Education programme and they were in-service preschool teachers. The findings revealed that there was no statistically significant interaction between the effects of assessment designs and CGPA on assignment marks. However, both assessment designs and CGPA had statistically significant main effects on the assignment marks respectively. The assignment marks for authentic assessment were comparatively higher, though AI tutoring was integrated similarly in both assessment designs. AI tutoring promotes a growth mindset through authentic assessment as there are no standardized answers for the learners to just copy and paste. The AI tutoring acts like a coach, facilitating the learners to reach the most appropriate answers.