Measuring Students’ Acceptance to AI-Driven Assessment in eLearning: Proposing a First TAM-Based Research Model

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Abstract

Artificial Intelligence is one of the trend areas in research. It is applied in many different contexts successfully. One of the contexts where Artificial Intelligence is applied is in Education. In the literature, we find several works in the last years that explore the application of Artificial Intelligence-related techniques to analyze students’ behavior, to enable virtual tutors or to assess the learning. However, what are the students’ perceptions on this subject of Artificial Intelligence and Education? Do they accept the use of Artificial Intelligence techniques to assess their learning? Are they reluctant to be influenced by non-human agents in such a human process like education? To try to respond to these questions, this paper presents a novel proposal of a research model based on the Technology Acceptance Model. To describe the model, we present its different main constructs and variables, as well as the hypotheses to analyze, adapted to the object of study. Finally, we discuss the main implications of this research model, the opportunities that could come based on this proposal and the future of this research.

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Cruz-Benito, J., Sánchez-Prieto, J. C., Therón, R., & García-Peñalvo, F. J. (2019). Measuring Students’ Acceptance to AI-Driven Assessment in eLearning: Proposing a First TAM-Based Research Model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11590 LNCS, pp. 15–25). Springer Verlag. https://doi.org/10.1007/978-3-030-21814-0_2

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