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All Journal Jurnal Pedagogi dan Inovasi Pendidikan
Sulestry, Andi Indra
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Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Other

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Mental Acts Developed in Deep Learning: A Literature Review Mansyur, Mansyur; Firandhi, Vikram Yuda Octa; Sulestry, Andi Indra; Arianti, Isnani; Bahar, Bahar
Jurnal Pedagogi dan Inovasi Pendidikan Vol. 1 No. 2 (2025): Jurnal Pedagogi dan Inovasi Pendidikan Volume 1 Number 2
Publisher : Jurnal Pedagogi dan Inovasi Pendidikan

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Deep learning refers to an educational approach that prioritizes conceptual comprehension and the development of higher order thinking skills, as opposed to surface learning which emphasizes memorization of facts. In this context, mental acts as described by Harel serve as crucial internal cognitive processes, including comparing, relating, generalizing, and abstracting, which support the meaningful construction of knowledge. This study applies a systematic review of literature, drawing on sources from international journals, nationally accredited journals, academic books, and conference proceedings. The data were examined through thematic analysis to identify the forms of mental acts, the instructional strategies that facilitate their emergence, and their influence on deep learning. The review reveals that while mental acts play an important role in fostering critical, creative, and metacognitive thinking, much of the existing research still concentrates on instructional strategies, with limited attention to affective and metacognitive dimensions. This article contributes a conceptual synthesis that situates mental acts as the central element of deep learning and proposes an integrated framework to strengthen educational practices for the twenty first century.
Developing Pedagogical Innovation: AI-Based Deep Learning Training in Elementary Education Yulita; Sukristin, Sukristin; Sabaryati, Johri; Akbar, Ady; Sulestry, Andi Indra
Jurnal Pedagogi dan Inovasi Pendidikan Vol. 1 No. 3 (2025): Jurnal Pedagogi dan Inovasi Pendidikan (Vol.1 No. 3 2025)
Publisher : Jurnal Pedagogi dan Inovasi Pendidikan

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Teacher readiness in addressing the challenges of 21st-century education requires a strong understanding of Deep Learning approaches as well as the ability to utilize artificial intelligence technology to enhance instructional quality. This community service program was designed to broaden teachers’ knowledge of the concepts and implementation of Deep Learning, which include meaningful, mindful and reflective, and joyful learning, while simultaneously equipping them with practical skills in the use of digital technology, particularly ChatGPT, as a learning support tool. The training was conducted on 27–28 October 2025 at SD IT Ar Rasyid Makassar with 25 participating teachers. The training methods included material delivery, group discussions, hands-on practice, case studies, and continued mentoring after the face-to-face sessions. Evaluation was carried out through pretests and post-tests, observations of participant engagement, and assessments of learning design outputs developed during the program. The evaluation results indicate improvements in teachers’ understanding of Deep Learning principles, the strengthening of 21st-century competencies, and enhanced ability to design context-based learning with artificial intelligence integration. An increase in the average score from 67.25 to 84.10 demonstrates that this program was effective in enhancing teachers’ capacity to implement more interactive, innovative, and learner-relevant instruction in the digital era. Therefore, this training provides a significant contribution to supporting learning transformation in schools.
Jigsaw Cooperative Learning and Its Impact on Students’ Motivation in Mathematics Education Wibowo, Ari; Haruna, Nana Harlina; Sulestry, Andi Indra; Salido, Achmad
Jurnal Pedagogi dan Inovasi Pendidikan Vol. 1 No. 3 (2025): Jurnal Pedagogi dan Inovasi Pendidikan (Vol.1 No. 3 2025)
Publisher : Jurnal Pedagogi dan Inovasi Pendidikan

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This study aimed to examine the effect of the jigsaw cooperative learning model on students’ motivation in mathematics learning. A quantitative approach with a pre-experimental design was employed. The population consisted of eighth-grade students, from which one class of 41 students was selected using purposive sampling. Data were collected using a mathematics learning motivation questionnaire. Descriptive statistics were used to describe students’ motivation levels, while inferential statistics using a t-test were applied to test the research hypothesis. The results showed that students’ motivation in mathematics learning before and after the implementation of the jigsaw cooperative learning model was generally at a moderate level. However, the implementation of the jigsaw model resulted in an increase of 80.48% in overall students’ motivation and a 96% increase across motivation indicators. The t-test results indicated that the calculated t-value (5.6774) exceeded the critical t-value (2.02), demonstrating a statistically significant effect of the jigsaw cooperative learning model on students’ motivation in mathematics learning. These findings suggest that the jigsaw cooperative learning model is an effective instructional strategy for enhancing students’ motivation in mathematics.
Co-Authors Akbar, Ady Ari Wibowo Arianti, Isnani Bahar Bahar, Bahar Firandhi, Vikram Yuda Octa Haruna, Nana Harlina Johri Sabaryati, Johri Mansyur Mansyur Salido, Achmad Sukristin Sukristin, Sukristin Yulita