Abstract
This study addresses the need for comprehensive feedback in academic physiotherapy programs. Existing methods often fall short of providing coherent feedback using keywords, leaving a gap in evaluating crucial clinical skills. Introducing iATexF, a Keyword-Based AI system, it offers instant feedback during practical exams, categorized into ’Good’, ’Improvement’, and ’Read more’, aiding students in understanding their performance. Utilizing a Seq2seq framework with diverse LSTM and attention mechanisms, iATexF excels in relevance, achieving a high similarity score of 73% and ROUGE score of 34%. It surpasses both ChatGPT and experts in providing relevant suggestions (80.7%), maintaining an appropriate tone (86.7%), and ensuring a logical structure order (100%). User experience evaluation of the iATexF web application yielded a favorable 92% rating, indicating its usability and effectiveness. This research signifies a significant advancement in educational technology and natural language processing, enhancing physiotherapy training through personalized AI-generated feedback, thereby improving the overall learning experience
| Original language | English |
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| Publication status | Published - 13 Jul 2024 |
| Event | IMSA The 2nd International Conference Intelligent Methods, Systems, And Applications - MSA University, Cairo, Egypt Duration: 13 Jul 2024 → 14 Jul 2024 https://imsa.msa.edu.eg/archive/imsa24/ |
Conference
| Conference | IMSA The 2nd International Conference Intelligent Methods, Systems, And Applications |
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| Abbreviated title | IMSA |
| Country/Territory | Egypt |
| City | Cairo |
| Period | 13/07/24 → 14/07/24 |
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