Recently, as low-cost microcontrollers such as those developed by Arduino and Raspberry Pi have become widely available, the term maker education has emerged as a hot topic in education. Teachers are increasingly using low-cost microcontrollers in their classes, but conducting a class that focuses on using a microcontroller may cause difficulties or problems, for the learner or for the instructor. To solve these problems, it was necessary to design a teaching and learning model for the use of low-cost microcontrollers to be applied at school sites. Accordingly, this study aimed to develop a teaching and learning model for using low-cost microcontrollers. As a result of this study, the author proposes a teaching and learning model that consists of six stages: topic selection, exploration of implementation methods, experimentation, production of teaching and learning materials, implementing lesson plans, and improvement. According to this procedure, teaching and learning materials were created and applied for the subject matter of a middle school unit on “Making Arduino Automobile.” The model developed in this study may provide a guideline for teachers who want to apply low-cost microcontrollers in their classes.

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.