Evaluating the Impact of AI Tools on Academic Performance and Student Satisfaction.
Background: This study explored the impact of artificial intelligence (AI) tools on student academic performance and satisfaction within the context of higher education. It highlights the potential of AI to personalise learning, enhance digital competencies, and foster critical thinking, while also...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 2; pp. 1 - 15 |
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| Autor principal: | |
| Formato: | research tables/charts Journal Article |
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Wiley-Blackwell
Apr2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=192476931&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192476931 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Apr2026 vid: 42 iid: 2 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 192476931 192476931 192476931 10.1002/jcal.70225 192476931 ppf: 1 ppct: 14 formats: tig: atl: Evaluating the Impact of AI Tools on Academic Performance and Student Satisfaction. aug: au: Wu, Zijing affil: School of Art and Design, Guilin University of Electronic Technology, Guilin Guangxi, , People's Republic of China sug: subj: Students, College Education, Masters Artificial Intelligence Utilization Academic Performance Evaluation Student Satisfaction Evaluation Reflection Human China Male Female Young Adult Quasi-Experimental Studies Pretest-Posttest Design Descriptive Statistics T-Tests Critical Thinking Problem Solving Communication Skills Creativeness Confidence Student Knowledge Digital Technology Male Female ab: Background: This study explored the impact of artificial intelligence (AI) tools on student academic performance and satisfaction within the context of higher education. It highlights the potential of AI to personalise learning, enhance digital competencies, and foster critical thinking, while also addressing challenges related to its integration into existing curricula. Objectives: The study aimed to assess the effectiveness of integrating AI‐based learning approaches into the educational process. Methods: The methodology involved a sample of 60 students using AI‐powered platforms such as Assessment and Learning in Knowledge Spaces (ALEKS) and Tableau and 60 students following a standard curriculum. Results: The findings indicated that AI tool integration significantly influenced students' academic performance. On average, task completion rates reached 88.75%, while non‐completion remained low at 11.25%. The highest performance was observed during reflective sessions, where over 90% of students successfully completed the tasks. This suggests that Learning Analytics tools helped participants better recognise their strengths, develop self‐reflection skills, and increase confidence in their knowledge. While working with platforms like ALEKS and Tableau, students demonstrated strong digital competencies and practical skills. Adaptive tasks, in particular, reinforced theoretical knowledge through realistic scenarios. The reasons for task non‐completion varied by task type. For instance, when working with ALEKS' personalised modules, students with low motivation or insufficient foundational knowledge encountered difficulties. In group projects involving Tableau, key challenges included handling large datasets and underdeveloped teamwork skills. Regarding critical thinking tasks, students struggled to formulate well‐reasoned conclusions by integrating knowledge from different disciplines. Conclusion: The study confirms that AI integration in education holds great potential, particularly for enhancing academic achievement, digital literacy, and reflective skills. However, to support students in complex aspects of learning, such as analytical thinking and adaptation to new technologies, further improvements in educational programmes are necessary. Practitioner Notes: What is already known about this topic? ○AI tools personalise learning and automate assessment in higher education.○Research shows AI boosts engagement and supports individual learning needs.○Integration success depends on digital literacy and institutional support.○Concerns remain about critical thinking and lecturer‐student interaction.What this paper adds? ○Reports controlled evidence of AI improving performance and satisfaction.○Shows ALEKS and Tableau enhance teamwork, reflection, and digital skills.○Identifies gaps in data analysis, critical thinking, and tech adaptation.○Highlights students' appreciation of gamification and interactive contentImplications for practice and/or policy ○Invest in AI tools with strong infrastructure and inclusive training.○Blend AI personalisation with methods that foster analytical skills.○Provide scaffolding and ethics training for responsible AI use.○Continuously evaluate AI's educational impact and technical function. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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