Designing an Interactive Digital Learning Environment Powered by Generative Artificial Intelligence: A Pilot Model for Enhancing Student Engagement and Technological Innovation in Higher Education

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This study designed and evaluated a digital learning environment integrating Canvas and generative AI, finding significant improvements in student engagement, technological innovation, and digital confidence compared to Canvas alone.

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This paper designs and evaluates a GenAI-enhanced interactive digital learning environment by integrating generative AI applications with the Canvas platform in a quasi-experimental study in the College of Education at King Khalid University. Students were divided into an experimental group (Canvas + GenAI) and a control group (Canvas only), with pre- and post-tests using validated instruments aligned to outcomes in learning engagement, technological innovation, and digital confidence, grounded in social constructivism, generative learning theory, the technology acceptance model, and diffusion of innovations theory. The authors report significant improvements in all targeted skills for the experimental group, while explicitly noting that the work is a preprint and has not been peer reviewed. Relevance to endometriosis: the paper is not centrally about endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract The rapid development of generative artificial intelligence (GenAI) technologies has presented significant opportunities and challenges for higher education institutions worldwide. With the evolution of digital learning environments, there is an urgent need to explore how intelligent tools—such as large language models and AI-based tutoring systems—can be meaningfully integrated into existing platforms to enhance student learning experiences. However, limited empirical research exists on the pedagogical design of these environments, particularly in Arab university contexts. This research addresses this gap by designing and evaluating a digital learning environment that combines the Canvas platform and GenAI applications to develop three essential 21st-century competencies: learning engagement, technological innovation, and digital confidence. The research utilized a quasi-experimental approach with a two-group design with pre- and post-tests. Students from the College of Education at King Khalid University participated in the study. Participants were divided into an experimental group (Canvas + GenAI) and a control group (Canvas only). Data were collected using validated measurement tools aligned with the study objectives. The theoretical foundations included social constructivism, generative learning theory, the technology acceptance model, and the diffusion of innovations theory. The results showed significant improvements in the experimental group across all targeted skills, confirming the pedagogical value of GenAI when carefully integrated. The research concludes with recommendations for instructional designers and higher education policymakers to adopt AI-enhanced learning environments that support engagement, creativity, and digital effectiveness.
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Designing an Interactive Digital Learning Environment Powered by Generative Artificial Intelligence: A Pilot Model for Enhancing Student Engagement and Technological Innovation in Higher Education | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Designing an Interactive Digital Learning Environment Powered by Generative Artificial Intelligence: A Pilot Model for Enhancing Student Engagement and Technological Innovation in Higher Education Ahmed Sadek Abdelmagid, Naif Mohammed Jabli, Adel Ibrahim Qahmash This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7217017/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The rapid development of generative artificial intelligence (GenAI) technologies has presented significant opportunities and challenges for higher education institutions worldwide. With the evolution of digital learning environments, there is an urgent need to explore how intelligent tools—such as large language models and AI-based tutoring systems—can be meaningfully integrated into existing platforms to enhance student learning experiences. However, limited empirical research exists on the pedagogical design of these environments, particularly in Arab university contexts. This research addresses this gap by designing and evaluating a digital learning environment that combines the Canvas platform and GenAI applications to develop three essential 21st-century competencies: learning engagement, technological innovation, and digital confidence. The research utilized a quasi-experimental approach with a two-group design with pre- and post-tests. Students from the College of Education at King Khalid University participated in the study. Participants were divided into an experimental group (Canvas + GenAI) and a control group (Canvas only). Data were collected using validated measurement tools aligned with the study objectives. The theoretical foundations included social constructivism, generative learning theory, the technology acceptance model, and the diffusion of innovations theory. The results showed significant improvements in the experimental group across all targeted skills, confirming the pedagogical value of GenAI when carefully integrated. The research concludes with recommendations for instructional designers and higher education policymakers to adopt AI-enhanced learning environments that support engagement, creativity, and digital effectiveness. e-platforms generative artificial intelligence applications integration in learning technological innovation digital confidence e-learning future skills digital transformation higher education Full Text Additional Declarations No competing interests reported. Ethics Approval Statement: This study was approved by the Head of the Department of Learning and Teaching, College of Education, King Khalid University, under approval number 172025. We confirm that the study was reviewed and fully approved by the Research Ethics Committee at the College of Education, King Khalid University. The study complied with institutional ethical guidelines and regulations concerning research involving human participants. Participant Consent Statement: All participants provided informed consent prior to their involvement in the study. They were fully informed about the nature and objectives of the research, and assured that participation was voluntary, with the right to withdraw at any time and full confidentiality of their responses. Institutional Review Board Statement: The study does not require ethical approval Funding This work was funded by the Deanship of Scientific Research and Graduate Studies at King Khalid University through research in small groups under Grant No. (RGP1/90/1446 AH). Author Contributions Conceptualization, A.S.A., N.M.J., and A.I.Q.; methodology, A.S.A. and N.M.J.; software and resources, A.I.Q.; validation and formal analysis, N.M.J. and A.S.A.; investigation and data curation, A.S.A., N.M.J., and A.I.Q.; writing—original draft preparation, A.S.A.; writing—review and editing, N.M.J. and A.I.Q.; supervision and project administration, A.S.A.; all authors have read and agreed to the published version of the manuscript. Institutional Review Board Statement Ethical review and approval were waived for this study, as there was no intervention or collection of sensitive personal data. Participation was voluntary, and all participants were informed of the study objectives and procedures. The study adhered to the institutional guidelines of King Khalid University. Informed Consent Statement Informed consent was obtained from all research participants. Participation was voluntary, and students were informed of the research objectives and procedures and their right to withdraw at any time without penalty. Data Availability Statement The data supporting the findings of this research are available from the corresponding author upon reasonable request. Conflict of Interest The authors declare no conflict of interest. Acknowledgments The authors would like to thank the Deanship of Scientific Research and Graduate Studies at King Khalid University for funding this work through a small group research project under Grant No. (RGP1/90/1446 AH). Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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