| C. Troussas, C. Papakostas, A. Krouska, Ph. Mylonas, C. Sgouropoulou |
| Personalized feedback using Natural Language Processing in Intelligent Tutoring Systems |
| 19th International Conference on Intelligent Tutoring Systems (ITS2023), Corfu, Greece, June 2-5, 2023 |
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ABSTRACT
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| This paper proposes a novel approach for enhancing feedback in intel-ligent tutoring systems (ITSs) for Java programming using natural language pro-cessing (NLP). The proposed approach overcomes the limitations of traditional rule-based feedback generation systems and provides more personalized and rel-evant feedback to the learner The system allows learners to input comments and/or questions through a text box in the user interface. In essence, it is com-posed of three main components: a natural language parser, a feedback generator, and a feedback evaluator. The natural language parser is responsible for convert-ing the unstructured text input of the learner into structured data, which can be analyzed for generating feedback. The feedback generator component then processes this data and generates personalized feedback for the learner based on their specific needs. Finally, the feedback evaluator component assesses the quality of the generated feedback and determines its helpfulness to the learner. The evalu-ation results are promising, indicating that using NLP techniques can improve the overall performance of intelligent tutoring systems and provide a more per-sonalized learning experience for students.
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| 02 June , 2023 |
| C. Troussas, C. Papakostas, A. Krouska, Ph. Mylonas, C. Sgouropoulou, "Personalized feedback using Natural Language Processing in Intelligent Tutoring Systems", 19th International Conference on Intelligent Tutoring Systems (ITS2023), Corfu, Greece, June 2-5, 2023 |
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