Necessity for artificial intelligence in higher education: Learners’ motivation for continuous use of AI-powered tools

Contemporary AI-powered tools have significantly enhanced the efficacy of language acquisition. The growing demand for a concentrated understanding of the integration between AI-powered tools and learners’ comprehension in higher education has been highlighted in the previous literature. Among numerous investigations on AI integration and education, only a few were carried out in Arabic contexts. This study aims to explore the influences of learners’ comprehension of AI-powered tools (ChatGPT, QuillBot, Grammarly, Turnitin) on motivations for continuous usage based on the explanations of the Unified Theory of Acceptance and Use of Technology (UTAUT). Quantitative cross-sectional data were collected through 40 questions in a survey questionnaire from 351 respondents in 10 universities. The data were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM), in two models, i.e., measurement model analysis and structural model analysis. The study first draws the hypothesized relationships between the constructs. A novel finding was identified through the designed model and proposed hypotheses. In addition, behavioral intentions of learners showed significant influences on learners’ comprehension of AI-powered tools and their motivations for usage. Further, the study determined a significant correlation between the tools’ comprehension, challenges, and learners' behavioral intentions toward continuous usage in the future, as shown in the Important-Performance Analysis. The validated model displayed a total variance of 87.3% for learners’ motivation to continue using AI-powered tools. Based on the acquired results, implications and recommendations for future research in both theory and practice have been declared.

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Publication Details

Journal
International Journal of Innovative Research and Scientific Studies
Published
2025-03-14
DOI
https://doi.org/10.53894/ijirss.v8i2.5413
Citations
1
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.69
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article

Necessity for artificial intelligence in higher education: Learners’ motivation for continuous use of AI-powered tools

Bilal Khalid Khalaf, Linda S. Al-Abbas, Ihab Mahmood, Saeed Abed Khudhur
1 citations
International Journal of Innovative Research and Scientific Studies
Online Learning and Analytics
1.69
article

Necessity for artificial intelligence in higher education: Learners’ motivation for continuous use of AI-powered tools

Bilal Khalid Khalaf, Linda S. Al-Abbas, Ihab Mahmood, Saeed Abed Khudhur
article en
1 citations

Abstract

Contemporary AI-powered tools have significantly enhanced the efficacy of language acquisition. The growing demand for a concentrated understanding of the integration between AI-powered tools and learners’ comprehension in higher education has been highlighted in the previous literature. Among numerous investigations on AI integration and education, only a few were carried out in Arabic contexts. This study aims to explore the influences of learners’ comprehension of AI-powered tools (ChatGPT, QuillBot, Grammarly, Turnitin) on motivations for continuous usage based on the explanations of the Unified Theory of Acceptance and Use of Technology (UTAUT). Quantitative cross-sectional data were collected through 40 questions in a survey questionnaire from 351 respondents in 10 universities. The data were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM), in two models, i.e., measurement model analysis and structural model analysis. The study first draws the hypothesized relationships between the constructs. A novel finding was identified through the designed model and proposed hypotheses. In addition, behavioral intentions of learners showed significant influences on learners’ comprehension of AI-powered tools and their motivations for usage. Further, the study determined a significant correlation between the tools’ comprehension, challenges, and learners' behavioral intentions toward continuous usage in the future, as shown in the Important-Performance Analysis. The validated model displayed a total variance of 87.3% for learners’ motivation to continue using AI-powered tools. Based on the acquired results, implications and recommendations for future research in both theory and practice have been declared.

International Journal of Innovative Research and Scientific StudiesVol. 8(2)
University of Anbar (IQ), Middle East University (JO)
Openalex Percentile: Top 15%
Online Learning and Analytics
1.69
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