AI-driven feedback system: Implementing advanced NLP and openAI for online learning
DOI:
https://doi.org/10.17977/um031v11i32024p137Keywords:
Artificial intelligence, NLP, OpenAI, Automatic feedback, Online learningAbstract
Abstrak:
Penelitian ini bertujuan untuk mengembangkan umpan balik otomatis berbasis Artificial Intelligence (AI) dengan teknologi Natural Language Processing (NLP) dan GPT OpenAI dalam pembelajaran online. Jenis penelitian ini adalah penelitian pengembangan atau Research and Development (R&D) dengan model pengembangan Integrative Learning Design Framework (ILDF) sebagai acuan untuk merancang, memproduksi, serta menguji efektivitas produk. Produk yang dikembangkan berperan untuk menganalisis respons siswa secara otomatis, memberikan umpan balik yang cepat, relevan, serta menawarkan saran perbaikan secara real-time yang mencakup fitur-fitur utama seperti sentiment score, entities detection, syntax & grammar, correction, improvement suggestions, hingga relevance score. Pengembangan produk ini mencakup perancangan sistem hingga pengujian awal, namun tidak melibatkan evaluasi para ahli atau uji coba skala besar. Fokus penelitian adalah memastikan bahwa produk dapat berfungsi sesuai dengan rancangan teknis dan memenuhi kebutuhan awal pengguna. Hasil dari tahap pengembangan diharapkan dapat menjadi dasar bagi penelitian lanjutan dan membuka peluang baru untuk inovasi dalam teknologi pendidikan di masa depan.
Abstract: This research aims to develop Artificial Intelligence (AI)-based automatic feedback with Natural Language Processing (NLP) technology and OpenAI GPT in online learning. The type of research is Research and Development (R&D) with the Integrative Learning Design Framework (ILDF) development model as a reference for designing, producing, and testing product effectiveness. The developed product plays a role in automatically analysing student responses, providing quick and relevant feedback, and offering real-time improvement suggestions, including key features such as sentiment score, entity detection, syntax & grammar, correction, improvement suggestions, and relevance score. The product development included system design to initial testing but did not involve expert evaluation or large-scale trials. The research focuses on ensuring that the product can function according to the technical design and fulfil the initial user needs. The results of the development phase are expected to form the basis for further research and open up new opportunities for innovation in educational technology in the future.
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Copyright (c) 2024 Liberius Sabinus Koe, Cecep Kustandi, Eveline Siregar

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