Empowering Secondary School Teachers: Creating, Executing, and Evaluating a Transformative Professional Development Course on ChatGPT

Heidi Reichert, Benyamin T. Tabarsi, Zifan Zhang, Cheri Fennell, Indira Bhandari, David Robinson, Madeline Drayton, Catherine Crofton, Matthew Lococo, Dongkuan Xu, Tiffany Barnes

Abstract: Background and Context. This innovative practice full paper describes the development and implementation of a professional development (PD) opportunity for secondary teachers to learn about ChatGPT. Incorporating generative AI techniques from Large Language Models (LLMs) such as ChatGPT into educational environments offers unprecedented opportunities and challenges. Prior research has highlighted their potential to personalize feedback, assist in lesson planning, generate educational content, and reduce teachers' workload, alongside concerns such as academic integrity and student privacy. However, the rapid adoption of LLMs since ChatGPT's public release in late 2022 has left educators, particularly at the secondary level, with a lack of clear guidance on how LLMs work and can be effectively adopted. Objective. This study aims to introduce a comprehensive, free, and vetted ChatGPT course tailored for secondary teachers, with the objective of enhancing their technological competencies in LLMs and fostering innovative teaching practices. Method. We developed a five-session interactive course on ChatGPT capabilities, limitations, prompt-engineering techniques, ethical considerations, and strategies for incorporating ChatGPT into teaching. We introduced the course to six middle and high school teachers. Our curriculum emphasized active learning through peer discussions, hands-on activities, and project-based learning. We conducted pre- and post-course focus groups to determine the effectiveness of the course and the extent to which teachers' attitudes toward the use of LLMs in schools had changed. To identify trends in knowledge and attitudes, we asked teachers to complete feedback forms at the end of each of the five sessions. We performed a thematic analysis to classify teacher quotes from focus groups' transcripts as positive, negative, and neutral and calculated the ratio of positive to negative comments in the pre- and post-focus groups. We also analyzed their feedback on each individual session. Finally, we interviewed all participants five months after course completion to understand the longer-term impacts of the course. Findings. Our participants unanimously shared that all five of the sessions provided a deeper understanding of ChatGPT, featured enough opportunities for hands-on practice, and achieved their learning objectives. Our thematic analysis underlined that teachers gained a more positive and nuanced understanding of ChatGPT after the course. This change is evidenced quantitatively by the fact that quotes with positive connotations rose from 45% to 68% of the total number of positive and negative quotes. Participants shared that in the longer term, the course improved their professional development, understanding of ChatGPT, and teaching practices. Implications. This research underscores the effectiveness of active learning in professional development settings, particularly for technological innovations in computing like LLMs. Our findings suggest that introducing teachers to LLM tools through active learning can improve their work processes and give them a thorough and accurate understanding of how these tools work. By detailing our process and providing a model for similar initiatives, our work contributes to the broader discourse on teaching professional educators about computing and integrating emerging technologies in educational and professional development settings.