Chatbots in Education: Transforming Learning and Support
Most training data comes from Western perspectives in the English language available from the internet. Human engineers, with their inherent biases, also provide additional training for these tools. Individual users bring their own perspectives into dialogue with a chatbot through prompts and queries. All these can result in subtle biases and stereotypes in the output of a chatbot. We encourage you and your students to be critical of language generated by AI chatbots and consider these important issues when using these tools (OpenAI Platform, n.d.).
However, there have been contradictory findings related to critical thinking, learning engagement, and motivation. Deng and Yu (2023) found that chatbots had a significant and positive influence on numerous learning-related aspects but they do not significantly improve motivation among students. Contrary, Okonkwo and Ade-Ibijola (Okonkwo & Ade-Ibijola, 2021), as well as (Wollny et al., 2021) find that using chatbots increases students’ motivation. This study report theoretical and practical contributions in the area of educational chatbots.
Using prompts with chatbots
Their implementation of NLP, adaptive learning, data analytics, and multilingual support enables a highly engaging and personalized learning experience. As education keeps changing, these e-learning chatbots are becoming more important. They will help students reach their learning goals and make education better for everyone.
If they answer incorrectly, they are explained why the answer is incorrect and then get asked a scaffolding question. Most researchers (25 articles; 69.44%) developed chatbots that operate on the web (Fig. 5). For example, KEMTbot (Ondáš et al., 2019) is a chatbot system that provides information about the department, its staff, and their offices. Other chatbots acted as intelligent tutoring systems, such as Oscar (Latham et al., 2011), used for teaching computer science topics. Moreover, other web-based chatbots such as EnglishBot (Ruan et al., 2021) help students learn a foreign language.
Intriguingly, one article was published in Computers in Human Behavior journal. The remaining journal articles were published in several venues such as IEEE Transactions on Affective Computing, Journal of Educational Psychology, International Journal of Human-Computer Studies, ACM Transactions on Interactive Intelligent System. Most of these journals are ranked Q1 or Q2 according to Scimago Journal and Country Rank Footnote 7.
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