DESIGNING AI-BASED GAMIFICATION TO ENHANCE ELEMENTARY SCHOOL STUDENTS’ MOTIVATION, READING COMPREHENSION AND PROBLEM SOLVING SKILLS

Abstract

This study aims to design and examine an AI based gamification model for elementary school English learning, particularly to support students motivation, reading comprehension, and problem solving skills. The study used a mixed methods approach with a Design and Development Research orientation supported by the ADDIE model. AI tools were used under teacher control to design short reading texts, crossword tasks, word and picture puzzles, storybooks, missions, quests, feedback, vocabulary support, and decision making activities. The model was implemented in an experimental class, while a control class received conventional instruction. Students motivation was examined descriptively through observation sheets based on Ryan and Deci Self Determination Theory and supported by interviews, whereas reading comprehension and problem solving were examined through pretests, posttests, analytic rubrics, and SPSS analysis. In this simulated reporting model involving 30 students in each class, the experimental class obtained a motivation observation score of 84.86 in the very high category, while the control class obtained 75.42 in the high category. Reading comprehension scores were 81.93 and 70.80, and problem solving scores were 78.33 and 69.37 for the experimental and control classes respectively. SPSS analysis showed significance values of .000 for reading comprehension and problem solving. The study concludes that teacher mediated AI based gamification can become pedagogically meaningful when it is age appropriate, ethically reviewed, and aligned with clear learning outcomes.