Improving the Motivation, Learning Engagement, and Learning Outcomes of Grade X Economics Students at MA Al Iman Magelang through the Jigsaw-Type Deep Learning Model - Yusi Radita; Esti Setiawati; Victor Novianto (Literasi: Jurnal Pendidikan Guru Indonesia, 2026)
This study aimed to improve the learning motivation, learning engagement, and economics learning outcomes of Grade X students at MA Al Iman Magelang through the implementation of the Jigsaw-type Deep Learning instructional model. The study employed a Classroom Action Research (CAR) design consisting of three stages: the pre-cycle, Cycle I, and Cycle II. Each cycle comprised four phases: planning, action, observation, and reflection. The research participants were 20 Grade X students of MA Al Iman Magelang during the 2025/2026 academic year. Data were collected through classroom observations, documentation, and achievement tests, and were analyzed using descriptive quantitative techniques based on percentages. The findings revealed continuous improvement across all observed aspects. Students' learning motivation in the high and very high categories increased from 0% in the pre-cycle to 40% in Cycle I, and further to 85% in Cycle II. Learning engagement in the high and very high categories improved from 0% in the pre-cycle to 55% in Cycle I, reaching 90% in Cycle II. Likewise, students' learning outcomes improved substantially, with the percentage of students achieving mastery increasing from 15% in the pre-cycle to 70% in Cycle I, and finally reaching 100% in Cycle II. These findings indicate that implementing the Jigsaw-type Deep Learning model effectively enhances students' learning motivation, classroom engagement, and economics learning outcomes.