AI Chatbots to Design Elementary English Lessons: Principles and Guidelines

By Dr Silpaja Chandrasekar, PhDReviewed by Susha Cheriyedath, M.Sc.Feb 16 2024

In a paper published in the journal Humanities and Social Sciences Communications, researchers detailed a study to establish principles for designing elementary English-speaking lessons using artificial intelligence chatbots.

They crafted ten principles through design and development research methods, including media selection, creating conducive learning environments, content restructuring, fostering interest and motivation, providing guidance, scaffolded learning support, individualized feedback provision, nurturing supportive learning environments, promoting communication and collaboration, and effective learning management. Additionally, they devised 24 detailed guidelines for implementing these principles. The paper discusses theoretical and practical implications while acknowledging research limitations and suggesting future directions.

Related Work

Past work in artificial intelligence (AI) chatbots for English education has seen significant strides, especially with the surge in interest spurred by the fourth industrial revolution and the shift towards online learning accentuated by the coronavirus disease 2019 (COVID-19) pandemic. However, despite various studies exploring AI chatbots' characteristics, development, and application in teaching and learning, there still needs to be a notable gap in research, particularly concerning their utilization in elementary school settings. The scarcity of research addressing the role of teachers and the design principles for AI chatbot-assisted classes, especially tailored to elementary students, underscores a pressing need for further investigation in this area.

Research Methodology: AI Chatbots in Education

This study utilized the Design and Development research methodology to establish principles for designing elementary English-speaking classes employing AI chatbots. This approach involves two types of research: "Products and tools research" and "model research." In this instance, "model research" was employed to develop and validate a new instructional design model for such courses. The process included model development research and model validation research. Initially, researchers formulated design principles by extensively reviewing the literature on AI chatbots in educational settings.

Subsequently, researchers conducted an expert validation review to assess the validity of these principles. Following this, a usability evaluation involved elementary school teachers designing lessons based on the developed principles and providing feedback through a questionnaire. The responses from both assessments were analyzed using the content validity index (CVI) and inter-rater agreement (IRA) to refine the instructional design principles.

The study's methodology encompassed three phases: derivation of initial design principles, expert validation, and usability evaluation. Researchers reviewed the literature on AI chatbots and English-speaking classes during the derivation phase to establish foundational principles—expert validation involved assessing the validity of these principles through a panel of experts using a structured questionnaire. Usability evaluation then engaged elementary school teachers in applying the principles to lesson design and providing feedback. Analysis of responses from both evaluations informed the refinement of the instructional design principles.

AI Chatbot Instructional Design

The study utilized the design and development research methodology to establish principles for designing elementary English-speaking classes with AI chatbots. It involved deriving initial design principles through an extensive literature review, identifying five components crucial for such courses: AI chatbot learning tool, curriculum, support, activities, and learning outcomes and evaluation. Expert validation was conducted in two phases, revealing the need for reorganization and clarification of the components. Subsequently, overall design principles underwent expert validation, with scores indicating high validity and reliability. The principles were refined based on feedback, leading to second-stage design principles and guidelines.

Three elementary school teachers actively found the instructional design principles helpful in lesson planning during the usability evaluation. Feedback highlighted the need for more specific examples and terminology familiar to teachers. Incorporating this feedback alongside secondary expert validation, the final model underwent minimal structural changes but saw improvements in terminology and relationship clarity.

The final instructional design principles and guidelines were derived, comprising ten principles and 24 detailed guidelines, facilitating the systematic design of English-speaking classes using AI chatbots. These principles provide valuable resources for teachers amidst the growing interest in edu-tech tools, reducing trial and error and fostering systematic implementation. The study contributes to bridging the gap between theoretical insights and practical application in AI chatbot-assisted instruction, offering a logical process for instructional design.

Moreover, the study's implications extend beyond English language instruction, providing insights into utilizing AI chatbots for various languages and educational levels. By considering target learners' proficiency levels and curricula, educators can adapt the developed design principles and guidelines for different levels of language instruction. The research contributes to the field by offering a systematic and comprehensive approach to designing language classes with AI chatbots, enhancing instructional effectiveness and adaptability across diverse educational contexts.

Conclusion

To sum up, the study concluded that instructional design principles for elementary English-speaking classes using AI chatbots offered a structured approach adaptable to specific contexts and educational goals. It highlighted the potential of AI chatbots to enhance English language attainment and reduce proficiency gaps, particularly in South Korea's education environment. However, there were limitations regarding generalizability to other educational levels and the need for technological support. Future research should focus on extending the model to diverse educational levels and language skills while addressing implementation challenges and enhancing technological infrastructure support.