From Prompt to Pedagogy: Designing AI-Generated Science Comics Through ChatGPT to Employ Critical Thinking Skills

Sun, 19 Apr 2026 00:00:00 +0000

Background/purpose. In science learning, critical thinking skills are essential indicators for delivering deep learning. In doing so, teaching alone is not enough to make students acquire the skills. Therefore, teachers need media such as e-comics for use in their classrooms. In this study, we examine the use of ChatGPT 4.0 as a tool for automatically generating visual representations from prompts to bring out the essence of critical thinking skills.

Materials/methods. This study used Design and Development Research (DDR), including needs analysis, design, and development, and expert validation. The instruments were a questionnaire and a validation rubric. The data were analyzed descriptively, considering the number of questionnaire items selected. A validation rubric is used to gain expert judgment over the quality of the e-comic developed using ChatGPT.

Results. The findings indicate that “Cells” (67%) and “Pollution” (65%) were perceived as the most difficult topics. The developed e-comic was rated highly valid in terms of content, while minor improvements were suggested for media aspects such as engagement and visual consistency. The study also resulted in an AI-Prompted Comic Design Framework consisting of five stages, namely, need analysis, narrative design, prompt engineering, AI-based visual generation, and expert validation.

Conclusion. The study demonstrates that ChatGPT can be effectively used to develop structured, visually consistent e-comics for science learning. The proposed framework provides practical guidance for integrating AI into instructional media design to support students’ critical thinking. However, the effectiveness of the e-comic in improving learning outcomes requires further investigation in future studies.

Intrinsic Motivation and School Climate as Predictors of Teacher Performance in Rural Indonesian Schools

Herli Herli, Sudarwan Danim, Asti Putri Kartiwi; Azizatul Khairi — Tue, 21 Apr 2026 00:00:00 +0000

Background/purpose. Teacher performance is a critical determinant of educational quality, yet it remains challenged by declining motivation and suboptimal work environments, particularly in developing countries.

Materials/methods. This study examined the influence of intrinsic motivation and school climate on teacher performance among 72 public junior high school teachers in Empat Lawang District, South Sumatra, Indonesia, using a quantitative cross-sectional survey design. Data were collected through validated questionnaires (intrinsic motivation: α = .960; school climate: α = .866; teacher performance: α = .938) and analyzed using Pearson correlation and multiple regression.

Results. Both predictors demonstrated strong positive correlations with teacher performance (intrinsic motivation: r = .907; school climate: r = .826; p < .001). Simple regression revealed that intrinsic motivation accounted for 82.3% of the variance in performance (R² = .823), while school climate accounted for 68.1% of the variance (R² = .681). Multiple regression indicated that both variables jointly explained 84.2% of the variance (R² = .842, F = 183.326, p < .001), with intrinsic motivation emerging as the dominant predictor (β = .707) relative to school climate (β = .243).

Conclusion. These findings suggest that improving teacher effectiveness in resource-constrained rural settings requires prioritizing professional autonomy and competency development alongside a supportive organizational climate.

International Journal of Educational Management and Innovation

From Prompt to Pedagogy: Designing AI-Generated Science Comics Through ChatGPT to Employ Critical Thinking Skills

Intrinsic Motivation and School Climate as Predictors of Teacher Performance in Rural Indonesian Schools