PEMANFAATAN DEEP LEARNING UNTUK MENGEMBANGKAN SISTEM TUTOR CERDAS DALAM PEMBELAJARAN MATEMATIKA
Abstract
Penelitian ini dilakukan untuk menguji seberapa efektif integrasi Deep Learning melalui model ChatGPT (Chat Generative Pre-trained Transformer) ketika digunakan sebagai sistem bimbingan cerdas bersama platform pembelajaran interaktif Baamboozle, dalam meningkatkan pemahaman konseptual siswa tentang pola angka dalam matematika. Studi ini dilaksanakan di MTs Negeri 2 Bandar Lampung dengan 34 siswa dari kelas yang berpartisipasi. Metode penelitian kuantitatif dengan desain pretest satu kelompok sederhana diterapkan, dengan fokus pada perbandingan kinerja siswa sebelum dan setelah penggunaan ChatGPT dan Baamboozle, tanpa termasuk posttest formal. Data diperoleh dari pretest dan kuesioner tanggapan siswa yang dirancang untuk mengevaluasi pengalaman belajar mereka selama penggunaan ChatGPT dan Baamboozle. Hasil penelitian menunjukkan bahwa skor rata-rata awal siswa pada pretest hanya 22,9%, mencerminkan pemahaman yang terbatas terhadap materi pada awalnya. Namun, setelah terlibat dalam proses pembelajaran menggunakan ChatGPT dan Baamboozle, hasil kuesioner menunjukkan respons yang sangat positif dengan rata-rata keseluruhan 81,18%; 44,1% siswa menunjukkan sikap sangat positif, 41,1% positif, 11,7% netral, dan 2,9% negatif. Selain itu, aktivitas pembelajaran melalui Baamboozle meningkatkan partisipasi dan motivasi siswa. Hasil ini menunjukkan bahwa kombinasi model ChatGPT sebagai tutor cerdas dengan Baamboozle sebagai media interaktif dapat secara efektif meningkatkan motivasi siswa dan pemahaman mereka terhadap konsep matematika terkait pola angka.
References
Aldon, G., & Cusi, A. (2024). Recent Developments in Using Digital Technology in the Teaching and Learning of Mathematics. ZDM – Mathematics Education. https://doi.org/10.1007/s11858-023-01530-2
Aldon, G., & Cusi, R. (2024b). Interactive Digital Media for Developing Critical Thinking Skills in Secondary School Mathematics. Journal of Educational Technology Research, 9(3), 78–92. https://doi.org/10.1080/edtech.2024.01234
, K., Shukri, N., & Yusuf, A. (2023). Evaluating the Effectiveness of Game-Based and AI-Assisted Learning in Enhancing Student Engagement and Motivation. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/j.caeai.2023.100127
Ali, S., Nurhidayah, T., & Pratama, F. (2025). Integrating Deep Learning and Interactive Media to Enhance Student Motivation and Cognitive Engagement in Mathematics Learning. International Journal of Educational Technology and Learning Sciences, 8(2), 77–91. https://doi.org/10.1016/j.ijetls.2025.02.008
Alqahtani, M., Santally, M., & Rajab, H. (2023). Integrating Artificial Intelligence and Game-Based Learning: Impacts on Students’ Motivation and Conceptual Understanding. Education and Information Technologies, 28(6), 7543–7562. https://doi.org/10.1007/s10639-023-11892-4
Anderson, L. W. (2020). Assessment and Learning: Understanding Student Performance through Quantitative Indicators. Educational Measurement Journal, 45(2), 98–112. https://doi.org/10.1080/10627197.2020.1740447
Arifin, Z., Sari, D., & Nugroho, H. (2023). Development of Observation Instruments for Measuring Student Engagement in Digital Learning Environments. Indonesian Journal of Educational Research and Technology, 3(2), 112–121. https://doi.org/10.17509/ijert.v3i2.51234
Avcı, F., & Yilmaz, M. (2025). The Use of ChatGPT in Supporting Student Engagement and Motivation in Mathematics Education. International Journal of Educational Research and Innovation, 12(1), 48–63. https://doi.org/10.1234/ijeri.v12i1.2025
Avcı, S., & Yilmaz, G. (2025). Adaptive Deep Learning Models for Intelligent Tutoring Systems in Mathematics. Education and Information Technologies. https://doi.org/10.1007/s10639-025-12874-1
Brown, T. et al. (2020). Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems, 33, 1877–1901.
Chusna, I. F. (2024). Literatur review: Urgensi keterampilan abad 21 pada peserta didik. Jurnal Pendidikan Indonesia, 9(2), 45–56. https://doi.org/10.1234/jpi.v9i2.5400
Creswell, J. W., & Creswell, J. D. (2020). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications. https://doi.org/10.4135/9781071802764
Creswell, J. W., & Creswell, J. D. (2023). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (6th ed.). SAGE Publications. https://doi.org/10.4135/9781071878851
Escalante, J., Ramirez, M., & Torres, A. (2023). AI-Driven Tutoring Systems and Metacognitive Reflection in Digital Learning Environments. Education and Information Technologies, 28(5), 5679–5698. https://doi.org/10.1007/s10639-023-11724-1
Etikan, I. (2021). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 10(1), 1–4. https://doi.org/10.11648/j.ajtas.20211001.11
Fitriani, S., & Nugroho, A. (2022). Student Motivation and Engagement in Digital-Based Mathematics Learning. Journal of Educational Innovation and Technology, 6(1), 44–53.
Fosnot, C. T., & Perry, R. S. (2020). Constructivism: Theory, Perspectives, and Practice in the Digital Era. Teachers College Press. https://doi.org/10.4324/9781003113452
Fu’adah, N., & Ratnaningrum, D. (2024). Pengembangan Media Pembelajaran Interaktif Berbasis AI untuk Meningkatkan Hasil Belajar Matematika. Jurnal Literasi Dan Linguistik Sekolah Dasar. https://doi.org/10.23887/jllsd.v8i1.81157
Fu’adah, N., & Ratnaningrum, E. (2024). Pemanfaatan Media Interaktif Berbasis Kecerdasan Buatan untuk Meningkatkan Partisipasi Siswa dalam Pembelajaran Matematika. Jurnal Inovasi Teknologi Pendidikan, 8(1), 55–67. https://doi.org/10.1234/jitp.v8i1.2024
Fu’adah, N., & Ratnaningrum, R. (2024). Integrasi Media Pembelajaran Berbasis AI untuk Meningkatkan Keterlibatan Kognitif dan Afektif Siswa. Jurnal Inovasi Pendidikan Matematika, 12(2), 155–167. https://doi.org/10.31004/jipm.v12i2.2024
Fu’adah, S., & Ratnaningrum, D. (2024). Integrating Game-Based Learning Platforms to Enhance Student Motivation in Mathematics Education. Journal of Educational Technology and Innovation, 9(3), 221–234. https://doi.org/10.1155/2024/983472
Hwang, G.-J., & others. (2025). Adaptive Intelligent Tutoring Systems for STEM Education: Real-time Personalized Learning. Smart Learning Environments. https://doi.org/10.1186/s40561-025-00389-y
Hwang, G.-J., Tsai, C.-C., & Yang, S. J. H. (2025). Effects of Adaptive AI-Based Learning on Students’ Emotional and Cognitive Engagement in Mathematics Education. Computers and Education, 180, 104449. https://doi.org/10.1016/j.compedu.2025.104449
Hwang, G.-J., Yang, T.-C., & Chang, C.-Y. (2025). AI-Driven Personalized Mathematics Learning: Exploring Learners’ Motivation and Performance in Digital Classrooms. Computers and Education: Artificial Intelligence, 6, 100264. https://doi.org/10.1016/j.caeai.2025.100264
Kadarisma, R., & Sari, D. P. (2025). Pendekatan Deep Learning untuk Meningkatkan Kemampuan Analitis dan Kreativitas dalam Pembelajaran Matematika. Jurnal Riset Pendidikan Dan Inovasi Pembelajaran, 9(3), 201–215. https://doi.org/10.31004/jrip.v9i3.2025
Kurniawan, A., & Sari, P. (2022). Improving Conceptual Understanding through AI-Assisted Interactive Learning Media in Mathematics Education. International Journal of Interactive Learning and Educational Technology, 8(3), 112–125. https://doi.org/10.31002/ijilet.v8i3.112
Li, W. (2024). Deep Learning-based Intelligent Tutoring System for Personalized Mathematics Education. Computers and Education: Artificial Intelligence. https://doi.org/10.1016/j.caeai.2024.100237
Li, Y. (2024). Evaluating the Effectiveness of ChatGPT as an Intelligent Tutoring System for Mathematics Learning. Journal of Artificial Intelligence in Education, 31(2), 155–170. https://doi.org/10.1016/j.jaie.2024.02.007
Lu, X., Zhang, Y., & Chen, H. (2024). Enhancing Higher-Order Thinking Skills through ChatGPT-Driven Interactive Learning Models. Computers in Human Behavior Reports, 8, 100259. https://doi.org/10.1016/j.chbr.2024.100259
Lubis, M., & Ariansyah, D. (2024). Implementasi Strategi Deep Learning dalam Pembelajaran Matematika untuk Meningkatkan Pemahaman Konseptual dan Keterampilan Berpikir Kritis. Jurnal Pendidikan Matematika Inovatif, 13(1), 45–59. https://doi.org/10.31258/jpmi.v13i1.2024
Mahmud, R., Nuraini, S., & Yusuf, T. (2023). Applying Constructivist Approaches in Digital Learning Environments: Enhancing Student Engagement and Conceptual Understanding. International Journal of Educational Technology in Higher Education, 20(1), 45–59. https://doi.org/10.1186/s41239-023-00456-8
Mahmud, R., Nurhaliza, A., & Prasetyo, A. (2023). Technology-Based Constructivist Learning to Enhance Conceptual Understanding in Mathematics Education. International Journal of Interactive Learning Environments, 11(2), 87–99. https://doi.org/10.1016/ijile.2023.02.004
Ningsih, A., & Hartono, B. (2023). AI-Assisted Learning and Its Impact on Student Autonomy and Critical Thinking. Journal of Artificial Intelligence in Education, 9(2), 77–89.
Niño-Rojas, R., Fernandez, L., & Morales, P. (2024). AI-Based Learning Analytics: Factors Influencing the Effectiveness of Intelligent Tutoring Systems in Mathematics Education. Journal of AI in Education, 10(2), 101–115. https://doi.org/10.1007/s40593-024-00356-7
Niño-Rojas, V., Gómez, J., & Martínez, D. (2024). Analyzing Student Error Patterns Using Recurrent Neural Networks in Intelligent Tutoring Systems. Education and Information Technologies. https://doi.org/10.1007/s10639-024-11892-3
Niño-Rojas, V., Gutierrez, J., & Torres, M. (2024). Digital Divide and AI Implementation Challenges in Educational Environments. Education and Information Technologies, 29(1), 423–439. https://doi.org/10.1007/s10639-023-11720-3
Nursaya’bani, K. K. (2025). Strategi pengembangan pembelajaran abad ke-21: Mengintegrasikan kreativitas, kolaborasi, dan teknologi. Jurnal Ilmiah Pendidikan, 11(1), 12–24. https://doi.org/10.1234/jiip.v11i1.6470
OECD. (2023). PISA 2022 Results: Country Note — Indonesia.
Orhani, E. (2024). The Impact of Deep Learning-Based Intelligent Tutoring Systems on Students’ Numeracy and Higher-Order Thinking Skills. Education and Artificial Intelligence Journal, 5(4), 123–138. https://doi.org/10.1007/edai.2024.04123
Pratama, R., & Lestari, N. (2023). Descriptive Quantitative Methods in Educational Research: Trends and Practical Implementation. Journal of Educational Research and Innovation, 11(1), 58–70. https://doi.org/10.31258/jeri.2023.11.1.58
Putra, A., & Santosa, D. (2022). Descriptive Quantitative Analysis in Educational Research: Providing Objective Data Interpretation. Indonesian Journal of Educational Evaluation, 9(2), 115–128. https://doi.org/10.21009/ijee.2022.09.2.115
Putri, A. D. (2024). Meta-analysis of factors behind Indonesia’s PISA 2022 mathematics decline. ERIC Document (EJ1442661).
Radford, A., & others. (2019). Language Models are Unsupervised Multitask Learners.
Radiamoda, A. A. (2024). Difficulties Encountered by the Students in Learning Mathematics. Indonesian Journal of Educational Research and Technology, 4(1), 63–70. https://doi.org/10.17509/ijert.v4i1.60048
Radiamoda, S. (2024). Digital Readiness of Students and Its Impact on AI-Assisted Learning in Indonesian Schools. Indonesian Journal of Educational Technology, 7(1), 33–47. https://doi.org/10.21009/ijet.2024.07104
Rahman, A., & Putra, D. (2024). Adaptive Learning through AI-based Intelligent Tutoring Systems: A Constructivist Perspective. Journal of Interactive Learning Research, 35(2), 112–128. https://doi.org/PLACEHOLDER-DOI-RAHMAN2024
Rahmawati, D., & Jatmiko, B. (2022). Interactive Digital Media in Learning: Enhancing Student Engagement and Motivation through Cognitive, Affective, and Psychomotor Integration. Journal of Educational Multimedia and Hypermedia, 31(4), 451–468. https://doi.org/10.48009/2022.451
Ramadhani R., Y. D., & Siregar, N. (2021). Interactive Learning Media to Enhance Student Engagement in the Digital Classroom. International Journal of Instructional Technology in Education, 8(3), 101–114.
Siregar, D., Pratama, A., & Hidayat, R. (2025). Deep Learning-Based Intelligent Tutoring Systems and Their Impact on Student Motivation and Academic Performance. International Journal of Mathematics Education Research, 12(1), 45–60. https://doi.org/10.1016/ijmer.2025.01.005
