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Lack of Contextual Understanding: Generative models lack the ability to understand context and situation, which can lead to inappropriate or irrelevant responses. A study by Gao and colleagues (2019) showed that a generative model-based dialogue system had a limited ability to understand and generate contextually appropriate responses in a conversation.
Limited ability to personalize instruction: ChatGPT and other generative AI models can provide general information and assistance, but they may not be able to personalize instruction to meet the individual needs of a particular student. (Ribeiro & Vala, 2020)
Interactive Learning: ChatGPT can be used to create interactive learning experiences where students can interact with a virtual tutor in a conversational manner. A study by Peng and colleagues (2019) demonstrated that a generative model-based conversational agent could provide effective support for students learning English as a second language, resulting in improved language proficiency. The study showed that the agent was able to understand students' questions and to provide appropriate and relevant responses.
Adaptive Learning: ChatGPT can be used to create adaptive learning systems that adjust their teaching methods based on a student's progress and performance. A study by Chiang and colleagues (2021) showed that an adaptive learning system based on a generative model (ChatGPT) could provide more effective support for students learning programming, resulting in improved performance on programming assessments. The study showed that the model was able to understand students' knowledge and to adjust the difficulty of the problems it generated accordingly.
Overall, ChatGPT has the potential to be a powerful tool for enhancing teaching and learning by providing personalized tutoring, automated essay grading, language translation, interactive learning and adaptive learning (By ChatGPT January 24, 2023).