Use an educational chatbot to let learners study at their own pace with replies suited to their specific needs¶

Strategy · All strategies
Evidence · 4 claims (3 for, 1 mixed) · 3 studies (1 causal, 1 review, 1 theoretical), q1–q2 · 0 of 3 report an effect size · 4 claims rest on one study

Description¶

This strategy deploys a conversational agent inside an e-learning system so that each learner receives replies matched to their specific needs and can progress at their own speed. The article states that integration into e-learning "can provide replies suited to each learner's specific needs, allowing them to study at their own pace". The reported experiment implemented this by having experimental classes study Logo with the chatbot-based method.

Design Implications¶

Context¶

Requirements¶

• An e-learning system hosting the chatbot; NLP-based reply generation suited to individual learner needs

Constraints¶

• Evaluated in the context of secondary school Logo instruction; findings are preliminary

Target Learners¶

• secondary school learners

Target Learning Goals¶

• self-paced learning of programming content

Claims¶

• Chatbot-based instruction enhanced secondary students' learning experience by enabling self-paced study with less stress, time savings, and maintained motivation [+W]
• AI chatbots enable flexible personalized learning by adapting teaching strategies to individual student needs [+W]
• Chatbot integration in a smart classroom is expected by the authors to increase learner engagement and academic achievement [+W]
• State-of-the-art conversational agents (Blender and GPT-3) replied adequately to students but were well behind human performance in helping the student (reported from a dialogue study) [~W]

Related Strategies¶

Examples¶

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Key Sources¶

• Ait Baha, T., El Hajji, M., Es-Saady, Y., & Fadili, H. (2024). The impact of educational chatbot on student learning experience. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12166-w