The main objective of this research was to study the effects of instructional management models and nominal variables on the development of students’ creative thinking. The researchers used the research synthesis of 400 studies on the development of students' creative thinking by a meta-analysis of research according to Cohen. The meta-analysis results revealed that the average effect size of the instructional management model (d = 3.43; [3.10, 3.17]) was positive and had a very high effect size with statistical significance. The most significant influence on the creative thinking development model was creative development theory (d = 4.217; [3.32, 5.11]). In addition, effect sizes varied with the attribute variables of the research, particularly the attribute variable of the research on instruction with the highest effect consisted of research with the focus on language, at the primary level, applied Torrance's creativity theory, designed between one to six lesson plans. Moreover, there was less than one hour per plan, the instructional period including the experiment conducted more than 31 hours and there were four weeks of instruction. In addition, there were six steps for instruction, there had quiz as an assessment tool, number of exams varied between 30 and 39 questions, and knowledge sheets were used as instructional materials. In the context of the meta-analysis, the findings indicated that the teachers should apply creative development theory in developing the students’ creative thinking for more effective instructional management.

The proliferating field of writing education increasingly intersects with technological innovations, particularly generative artificial intelligence (GenAI) resources. Despite extensive research on automated writing evaluation systems, no empirical investigation has been reported so far on GenAI’s potential in cultivating intermedial writing skills within first language contexts. The present study explored the impact of ChatGPT as a writing assistant on university literature students’ intermedial writing proficiency. Employing a quasi-experimental design with a non-equivalent control group, researchers examined 52 undergraduate students’ essay writings over a 12-week intervention. Participants in the treatment group harnessed the conversational agent for iterative essay refinement, while the reference group followed traditional writing processes. Utilizing a comprehensive four-dimensional assessment rubric, researchers analyzed essays in terms of relevance, integration, specificity, and balance of intermedial references. Quantitative analyses revealed significant improvements in the AI-assisted group, particularly in relevance and insight facets. The findings add to the research on technology-empowered writing learning.