Revolutionizing eLearning Assessments: The Role of GPT in Crafting Dynamic Content and Feedback

Michael E. Bernal
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Abstract

This study presents the Learnix project that utilizes the GPT-4 large language model (LLM) to enhance interactive learning in eLearning platforms, with a specific focus on generating dynamic multiple-choice questions (MCQs) and providing tailored feedback for Python coding problems and short-answer questions. The aim was to explore how language models can be integrated into eLearning environments to create more adaptive and engaging educational experiences. Leveraging GPT-4’s advanced natural language processing capabilities, the developed platform can generate a diverse range of MCQs and offer unique feedback, significantly improving upon traditional static learning content. This approach enhances the learner’s journey, offering a more engaging and individualized educational experience. The methodology involved the integration of GPT-4 into an eLearning platform, emphasizing user interaction and content relevance. The Learnix platform was designed to handle a variety of coding problems, with the LLM generating corresponding MCQs and feedback. This method’s effectiveness was evaluated based on content quality and relevance. Results demonstrated that GPT-4’s inclusion markedly enhanced the eLearning experience by providing diverse and up-to-date content. Customized feedback is particularly effective in reinforcing learning concepts and addressing individual learning needs. Moreover, the platform showed versatility in scaling and adapting to different educational contexts, making it a valuable tool for various learning requirements. The findings of this project emphasize the transformative potential of language models and Generative AI in redefining online education, leaning towards more adaptive and engaging learning experiences. Additionally, the Learnix project underscores the importance of continual innovation in educational technology, suggesting a new paradigm where AI becomes an integral part of the teaching and learning process. The integration of GPT-4 not only enriches the learning material but also enhances the overall effectiveness of the educational process, paving the way for future advancements in AI-driven eLearning solutions.
革新电子学习评估:GPT 在制作动态内容和反馈中的作用
本研究介绍了 Learnix 项目,该项目利用 GPT-4 大型语言模型(LLM)来增强电子学习平台中的互动学习,尤其侧重于生成动态多选题(MCQ),并为 Python 编码问题和简答题提供量身定制的反馈。目的是探索如何将语言模型集成到电子学习环境中,以创建更具适应性和吸引力的教育体验。利用 GPT-4 先进的自然语言处理能力,所开发的平台可以生成各种 MCQ 并提供独特的反馈,大大改进了传统的静态学习内容。这种方法增强了学习者的学习过程,提供了更具吸引力和个性化的教育体验。该方法涉及将 GPT-4 整合到电子学习平台中,强调用户互动和内容相关性。Learnix 平台旨在处理各种编码问题,并由 LLM 生成相应的 MCQ 和反馈。根据内容质量和相关性对该方法的有效性进行了评估。结果表明,GPT-4 的加入通过提供多样化和最新的内容,显著增强了在线学习体验。定制反馈在强化学习概念和满足个人学习需求方面尤为有效。此外,该平台在扩展和适应不同教育环境方面表现出了多功能性,使其成为满足各种学习要求的宝贵工具。本项目的研究结果强调了语言模型和生成式人工智能在重新定义在线教育方面的变革潜力,倾向于提供更具适应性和吸引力的学习体验。此外,Learnix 项目强调了教育技术持续创新的重要性,提出了一种新的模式,即人工智能成为教学过程中不可或缺的一部分。GPT-4 的集成不仅丰富了学习材料,还提高了教育过程的整体效果,为未来人工智能驱动的电子学习解决方案的发展铺平了道路。
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