International Journal of Educational Management and Innovation

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

2025-11-16T12:41:37+00:00

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

2026-02-21T04:23:59+00:00

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.

Examining The Impact of The ALLR Learning Cycle on Undergraduate Students’ Conceptual Understanding in General Chemistry: A Pre-Experimental Study

2025-11-16T11:42:51+00:00

Background. Understanding solution concepts in general chemistry remains challenging for undergraduate students due to their abstract and procedural complexity. This study investigates the effectiveness of the ALLR (Activity-based–Lesson–Learn–Reflection) approach in enhancing students’ conceptual understanding.

Methods. A pre-experimental one-group pretest–posttest design was conducted with 29 first-semester Science Education students at an Indonesian university. Conceptual understanding was measured using a validated 20-item multiple-choice test covering four indicators: concept restatement, identification of examples and non-examples, procedural application, and problem solving.
Results. The findings indicate a substantial improvement in conceptual understanding, with mean scores increasing from 52.93 to 80.52 and the overall achievement level rising from moderate (53%) to very good (81%). The highest gain was observed in problem-solving performance (58% to 89%), with an N-gain value of 0.59, indicating moderate effectiveness.
Conclusion. This study provides empirical evidence for the ALLR approach as a coherent pedagogical framework that integrates experiential learning, conceptual consolidation, and structured reflection to support deep conceptual understanding in abstract chemistry topics. Despite limitations of the pre-experimental design and sample size, the findings suggest that ALLR holds pedagogical potential to improve conceptual understanding and problem-solving in general chemistry, particularly in science teacher education.

Reframing Technostress in Non-Formal Education: An AMO-Based Human Resource Management Model for Sustainable Digital Transformation

2026-04-29T07:24:46+00:00

Background. The rapid digitalization of education has intensified the integration of digital technologies into teaching and administrative processes, generating new organizational challenges related to technostress among educators. While existing studies predominantly emphasize individual psychological perspectives and coping mechanisms, a critical gap remains in understanding the organizational and human resource management (HRM) dimensions that shape technostress, particularly in non-formal education contexts, which are characterized by flexible structures and limited institutional support. Addressing this gap, this study aims to examine how technostress emerges as an organizational phenomenon and to develop an evidence-based HRM model grounded in the Ability–Motivation–Opportunity (AMO) framework to support sustainable digital transformation.

Methods. This study employed a qualitative multi-site case study design involving non-formal education institutions in Kendari City, Indonesia. Data were collected through in-depth interviews, observations, document analysis, and supporting quantitative indicators. Data analysis followed a multi-stage coding process (open, axial, and selective coding) combined with convergent mixed analysis to enhance analytical rigor and validity.

Results. The findings reveal that technostress is multidimensional, consisting of techno-overload, techno-complexity, techno-uncertainty, and techno-invasion. These dimensions are primarily shaped by organizational factors, including digital governance, institutional support systems, communication practices, and workload structures. Notably, organizational opportunity emerged as a key mediating mechanism influencing educators’ adaptation and teaching effectiveness. As a novel contribution, this study develops an AMO-based HRM intervention model and operational standard operating procedures (SOPs) that systematically link organizational factors to technostress mitigation and improvements in learning performance.

Conclusion. This study concludes that technostress in non-formal education is primarily shaped by organizational conditions rather than technology alone. The findings further reveal that technostress occurs at varying levels—predominantly low to moderate—indicating that digital stress is a graded and context-dependent phenomenon rather than an extreme condition. By integrating technostress theory with the Ability–Motivation–Opportunity (AMO) framework, this study offers a novel organizational perspective and develops practical HRM-based strategies for managing digital work environments. The results emphasize that sustainable digital transformation depends on aligning technological innovation with structured organizational support systems to enhance educator well-being and learning effectiveness.