An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust

The rising integration of AI-driven assessment in education holds promise, yet it is crucial to evaluate the correlation between trust in general AI tools, AI-based scoring systems, and future behavioral intention toward using these technologies. This study explores students’ perspectives on AI-assi...

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Main Authors: Ari Alamäki, Umair Ali Khan, Janne Kauttonen, Stephan Schlögl
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Education Sciences
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Online Access:https://www.mdpi.com/2227-7102/14/12/1386
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author Ari Alamäki
Umair Ali Khan
Janne Kauttonen
Stephan Schlögl
author_facet Ari Alamäki
Umair Ali Khan
Janne Kauttonen
Stephan Schlögl
author_sort Ari Alamäki
collection DOAJ
description The rising integration of AI-driven assessment in education holds promise, yet it is crucial to evaluate the correlation between trust in general AI tools, AI-based scoring systems, and future behavioral intention toward using these technologies. This study explores students’ perspectives on AI-assisted assessment in higher education. We constructed a comprehensive questionnaire supported by relevant studies. Several hypotheses grounded in the literature review were formulated. In an experimental setup, the students were tasked to read a designated chapter of a paper, answer an essay question about this chapter, and then have their answers evaluated by an AI-based essay grading tool. A comprehensive data analysis using Bayesian regression was carried out to test several hypotheses. The study finds that remote learners are more inclined to use AI-based educational tools. The students who believe that AI-based essay grading is less effective than teacher feedback have less trust in AI-based essay grading, whereas those who find it more effective perceive more benefit from it. In addition, students’ affinity for technology does not significantly impact trust or perceived benefits in AI-based essay grading.
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spelling doaj-art-8f799f9a71354cbc8c44fe7c6f61f6c02025-08-20T02:00:33ZengMDPI AGEducation Sciences2227-71022024-12-011412138610.3390/educsci14121386An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and TrustAri Alamäki0Umair Ali Khan1Janne Kauttonen2Stephan Schlögl3RDI & Competences, Haaga-Helia University of Applied Sciences, Ratapihantie 13, 00520 Helsinki, FinlandRDI & Competences, Haaga-Helia University of Applied Sciences, Ratapihantie 13, 00520 Helsinki, FinlandRDI & Competences, Haaga-Helia University of Applied Sciences, Ratapihantie 13, 00520 Helsinki, FinlandDepartment of Management, Communication & IT, MCI Management Center Innsbruck, 6020 Innsbruck, AustriaThe rising integration of AI-driven assessment in education holds promise, yet it is crucial to evaluate the correlation between trust in general AI tools, AI-based scoring systems, and future behavioral intention toward using these technologies. This study explores students’ perspectives on AI-assisted assessment in higher education. We constructed a comprehensive questionnaire supported by relevant studies. Several hypotheses grounded in the literature review were formulated. In an experimental setup, the students were tasked to read a designated chapter of a paper, answer an essay question about this chapter, and then have their answers evaluated by an AI-based essay grading tool. A comprehensive data analysis using Bayesian regression was carried out to test several hypotheses. The study finds that remote learners are more inclined to use AI-based educational tools. The students who believe that AI-based essay grading is less effective than teacher feedback have less trust in AI-based essay grading, whereas those who find it more effective perceive more benefit from it. In addition, students’ affinity for technology does not significantly impact trust or perceived benefits in AI-based essay grading.https://www.mdpi.com/2227-7102/14/12/1386artificial intelligenceAI-based assessmenttechnology affinitytrusthigher educationEdTech
spellingShingle Ari Alamäki
Umair Ali Khan
Janne Kauttonen
Stephan Schlögl
An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust
Education Sciences
artificial intelligence
AI-based assessment
technology affinity
trust
higher education
EdTech
title An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust
title_full An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust
title_fullStr An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust
title_full_unstemmed An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust
title_short An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust
title_sort experiment of ai based assessment perspectives of learning preferences benefits intention technology affinity and trust
topic artificial intelligence
AI-based assessment
technology affinity
trust
higher education
EdTech
url https://www.mdpi.com/2227-7102/14/12/1386
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