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All Journal Kognitif: Jurnal Riset HOTS Pendidikan Matematika
Satya Santika
Mathematics Education Study Program, Faculty of Teacher Training and Education, Universitas Siliwangi
Computer Science & IT Education Library & Information Science Mathematics Social Sciences Other

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Development of the "Pangkatani" Scratch-Assisted Interactive Multimedia for Learning Exponents Ahmad Akbar; Satya Santika; Mega Nur Prabawati
Kognitif: Jurnal Riset HOTS Pendidikan Matematika Vol. 6 No. 3 (2026): July - September 2026
Publisher : Education and Talent Development Center Indonesia (ETDC Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51574/kognitif.v6i3.3481

Abstract

Interactive multimedia has become a strategic need in mathematics teaching in the digital era, particularly for exponents, a topic still taught in conventional and abstract ways. This study developed and tested the feasibility of "Pangkatani," a Scratch-assisted interactive multimedia that integrates the local wisdom of cassava farming to give the concept of exponents a concrete context for ninth-grade students at SMPN 3 Sukahening. What makes Pangkatani distinctive is the way it combines visualization, interactive simulation, and culturally grounded gamification, which together are expected to raise student engagement, motivation, and conceptual understanding. The study used a Research and Development (R&D) approach with the ADDIE model and involved 19 students in a limited trial. The instruments were validation questionnaires for a media expert and a material expert, together with a student response questionnaire, analyzed through descriptive quantitative methods and supported by qualitative narrative. Media expert validation (90.77%) and material expert validation (95.38%) both fell in the "highly feasible" category, while the overall student response of 81.58% reflected gains in motivation, understanding, and willingness to learn. The findings suggest that embedding local wisdom in Scratch-based digital multimedia can strengthen contextual, constructivist, and meaningful mathematics learning. The Pangkatani model is recommended as a reference for developing similar media in other schools and as a contribution to the literature on culturally based educational multimedia. Further research with a wider scope and a longitudinal design is advised to test long-term effectiveness and replication.
Application of a Deep Learning Approach to Mathematics Learning Outcomes in the Probability Unit for Ninth-Grade Students Fitria Andyasti Rahayu Pranata; Nani Ratnaningsih; Satya Santika
Kognitif: Jurnal Riset HOTS Pendidikan Matematika Vol. 6 No. 3 (2026): July - September 2026
Publisher : Education and Talent Development Center Indonesia (ETDC Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51574/kognitif.v6i3.5283

Abstract

This study aimed to determine whether the mathematics learning outcomes of ninth-grade students on probability material after the implementation of a deep learning approach had achieved the Minimum Mastery Criterion (MMC). The study was motivated by the importance of developing students’ conceptual understanding, critical thinking skills, and active participation in mathematics learning through meaningful and student-centered instruction. The deep learning approach was expected to help students develop higher-oerder thinking skills, particularly in applying, analyzing, and evaluating probability concepts. This research employed a pre-experimental method using a One-Shot Case Study design. The population of the study consisted of all ninth-grade students at SMP Negeri 8 Tasikmalaya. The sample was selected using the cluster random sampling technique, in which one class was randomly chosen as the research sample. The instrument used in this study was a mathematics learning outcomes test on probability material developed based on cognitive indicators, namely C3 (applying), C4 (analyzing), and C5 (evaluating). The test was designed to measure students’ understanding and problem-solving abilities related to probability topics. The data were analyzed using descriptive and inferential statistics techniques. Descriptive statistics were used to describe students’ mathematics learning outcomes, while inferential statistics were applied to test the research hypothesis. The hypothesis testing technique used in this study was the One-Sample t-Test to determine whether the average score of students’ learning outcomes had achieved the established MMC score of 80. The results showed that the average mathematics learning outcome score of the students was 73, which was below the established Minimum Mastery Criterion. Therefore, it can be concluded that the mathematics learning outcomes of ninth-grade students on probability material after the implementation of the deep learning approach had not yet achieved the Minimum Mastery Criterion.
Co-Authors Ahmad Akbar Fitria Andyasti Rahayu Pranata Mega Nur Prabawati Nani Ratnaningsih