Intellectus: an AI model to enhance student cognitive performance, increase knowledge acquisition, boost academic integrity and mitigate AI over-reliance in education
Conference paper
Razvi, A. and Bashir, E. 2025. Intellectus: an AI model to enhance student cognitive performance, increase knowledge acquisition, boost academic integrity and mitigate AI over-reliance in education. 2025 IEEE International Smart Cities Conference (ISC2). Patras, Greece 06 - 09 Oct 2025 IEEE. https://doi.org/10.1109/isc266238.2025.11293322
| Type | Conference paper |
|---|---|
| Title | Intellectus: an AI model to enhance student cognitive performance, increase knowledge acquisition, boost academic integrity and mitigate AI over-reliance in education |
| Authors | Razvi, A. and Bashir, E. |
| Abstract | This study presents Intellectus, a fine-tuned large language model (LLM) designed to enhance student cognitive performance, boost knowledge acquisition and mitigate AI over-reliance in education. In contrast to traditional AI tools that provide direct answers, Intellectus engages learners through Socratic questioning, adaptive scaffolding, and structured prompting. Developed using a no-code Custom GPT approach and grounded in a systematic literature review, Intellectus was evaluated through a triangulated methodology combining student self-assessments, expert ratings, and plagiarism analysis. A/B testing with twelve university students showed significant gains across ten higher-order cognitive skills when using Intellectus compared to ChatGPT, alongside a dramatic reduction in plagiarism rates. Expert evaluations further validated these findings, confirming Intellectus' ability to promote deeper thinking and academic integrity, and T-testing proved statistical significance across domains. |
| Sustainable Development Goals | 4 Quality education |
| Middlesex University Theme | Creativity, Culture & Enterprise |
| Conference | 2025 IEEE International Smart Cities Conference (ISC2) |
| Proceedings Title | 2025 IEEE International Smart Cities Conference (ISC2) |
| ISSN | |
| Electronic | 2687-8860 |
| 2687-8852 | |
| ISBN | |
| Electronic | 9798331557737 |
| Paperback | 9798331557744 |
| Publisher | IEEE |
| Publication dates | |
| 06 Oct 2025 | |
| Online | 23 Dec 2025 |
| Publication process dates | |
| Accepted | 2025 |
| Deposited | 14 Jul 2026 |
| Output status | Published |
| Accepted author manuscript | License File Access Level Open |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/isc266238.2025.11293322 |
| Web address (URL) of conference proceedings | https://doi.org/10.1109/ISC266238.2025 |
https://repository.mdx.ac.uk/item/32x9q1
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