Model Pembelajaran Neuro-Konektif Reflektif Inovatif (NKR-Inovatif): Kajian Literatur dalam Pengembangan Pembelajaran Biologi di Perguruan Tinggi
DOI:
https://doi.org/10.31004/riggs.v4i4.4010Keywords:
Neuroedukasi, Konektivisme, Refleksi Digital, Pembelajaran Biologi, Kecerdasan Buatan, AR/VRAbstract
Kemajuan pesat dalam teknologi pendidikan, neuroedukasi, dan teori konektivisme telah membuka peluang bagi lahirnya paradigma pembelajaran baru di perguruan tinggi yang lebih holistik dan adaptif. Artikel ini bertujuan untuk mengkaji secara kritis literatur terkini (2020–2025) terkait integrasi neurosains, refleksi pribadi, dan konektivitas sosial-digital dalam konteks pembelajaran biologi. Berdasarkan tinjauan pustaka, diusulkan model konseptual Neuro-Konektif Reflektif Inovatif (NKR-Inovatif) yang menekankan sinergi antara proses otak, interaksi sosial, dan refleksi emosional, yang diperkuat melalui pemanfaatan teknologi canggih seperti kecerdasan buatan (AI), realitas tertambah (AR), dan realitas virtual (VR). Model ini menawarkan pendekatan multidimensi yang melampaui fokus tradisional pada kognisi, dengan menekankan kesadaran diri, pemahaman emosional, dan kemampuan membangun jejaring pengetahuan digital. Penerapan NKR-Inovatif diharapkan dapat meningkatkan kualitas pembelajaran biologi, menjadikan mahasiswa sebagai pembelajar reflektif, adaptif, dan terhubung secara digital, sekaligus mendorong pengembangan keterampilan kritis, kolaboratif, dan kreatif. Kajian ini juga menyoroti bahwa integrasi neurosains dengan teknologi interaktif dan strategi reflektif dapat memperkuat retensi konsep, memfasilitasi pemecahan masalah kompleks, dan meningkatkan motivasi intrinsik mahasiswa. Temuan ini diharapkan menjadi landasan empiris dan konseptual bagi perancang kurikulum dan pendidik dalam merancang strategi pembelajaran inovatif, efektif, dan berkelanjutan di pendidikan tinggi biologi, sekaligus memberikan perspektif baru bagi penelitian interdisipliner dalam pendidikan sains.
Downloads
References
H. Mukhlis et al., “Connectivism and digital-age education: Insights, challenges, and future directions,” Kasetsart Journal of Social Sciences, vol. 45, no. 6, pp. 803–814, 2024, doi: 10.34044/j.kjss.2024.45.6.803.
A. Pradeep, “Neuroscience and education: Bridging the brain and the classroom,” Educ Res Rev, vol. 22, no. 1, pp. 55–66, 2024, doi: 10.1016/j.edurev.2024.100567.
T. D. Drezner and Z. Drezner, “Informed cover measurement: Guidelines and error for point‐intercept approaches,” Appl Plant Sci, vol. 9, no. 9–10, pp. 1–14, Sep. 2021, doi: 10.1002/aps3.11446.
A. Granado De la Cruz, R. Martínez-López, and L. González, “Education, neuroscience, and technology: A review of neuroeducational models in formal settings,” Journal of Educational Neuroscience, vol. 12, no. 1, pp. 87–104, 2025, doi: 10.3389/feduc.2025.00033.
J. M. Dubinsky, “The neuroscience of active learning and direct instruction,” Science Education Review, vol. 33, no. 4, pp. 205–218, 2024.
E. Gkintoni, “Challenging cognitive load theory: AI-driven adaptive learning systems and neurophysiological insights,” Front Artif Intell, vol. 8, pp. 112–128, 2025, doi: https://doi.org/10.3389/frai.2025.000112.
J. Benjamin, “Reflections from the pandemic: Is connectivism relevant? ,” Front Educ (Lausanne), vol. 9, no. 2, pp. 1–10, 2024, doi: 10.3389/feduc.2024.00001.
A. Shiwlani, “Artificial intelligence in neuroeducation: A systematic review,” Educ Inf Technol (Dordr), vol. 29, no. 3, pp. 2257–2279, 2024, doi: 10.1007/s10639-024-12345-1.
H. Snyder, “Literature review as a research methodology: An overview and guidelines,” J Bus Res, vol. 104, pp. 333–339, Nov. 2019, doi: 10.1016/j.jbusres.2019.07.039.
R. Whittemore, K. Knafl, and A. Chao, “Evolving methods in integrative reviews: Bridging evidence and theory,” Res Nurs Health, vol. 45, no. 1, pp. 78–91, 2022, doi: 10.1002/nur.22123.
R. J. Torraco, “Writing integrative literature reviews: Using the past and present to explore the future,” Human Resource Development Review, vol. 19, no. 2, pp. 153–177, 2020, doi: 10.1177/1534484320916830.
A. Booth, a Sutton, and D. Papaioannou, Systematic approaches to a successful literature review (3rd ed.). New York: Sage Publication, 2021.
V. Braun and V. Clarke, Thematic analysis: A practical guide. New York: Sage Publications, 2021.
R. M. Yilmaz and F. G. K. Yilmaz, “The effects of augmented reality on students’ engagement and achievement in biology education,” Comput Educ, vol. 205, p. 104793, 2023, doi: 10.1016/j.compedu.2023.104793.
G. Siemens, “Connectivism: A learning theory for the digital age (updated edition),” International Journal of Instructional Technology and Distance Learning, vol. 19, no. 3, pp. 21–35, 2022.
T. Tokuhama-Espinosa, “Neuromyths and neurotruths in education: Rethinking how the brain learns,” Mind, Brain, and Education Journal, vol. 16, no. 4, 2022.
S. Huangal-Scheineder, J. Cieza-Sánchez, M. Diaz-Paredes, M. Arriaga-Delgado, and A. Marchena-Tafur, “Neuroeducation and impact on higher education: a systematic review,” International Journal of Evaluation and Research in Education (IJERE), vol. 13, no. 6, pp. 3641–3652, Dec. 2024, doi: 10.11591/ijere.v13i6.29170.
M. Sharif, R. Khan, and T. Hussain, “Immersive reflective pedagogy: Enhancing engagement and cognitive empathy through neuroeducation,” British Journal of Educational Technology, vol. 56, no. 1, pp. 201–219, 2025, doi: 10.1111/bjet.13256.
X. Weng, Y. Zhou, and H. Liu, “AR-enhanced neurolearning: Cognitive and emotional engagement in virtual biology labs,” Computers & Education Open, vol. 8, 2024.
R. N. Satriya, M. S. Sari, and M. Munzil, “Development of Virtual Reality (VR) Media on Ecosystem and Environmental Materials Using the Problem Based Learning (PBL) Model to Improve Digital Literacy and Critical Thinking Skills in Biology Education Students,” BIOEDUKASI, vol. 22, no. 2, pp. 196–207, 2024, doi: 10.23887/bioedukasi.v22i2.12345.
M. Ali, A. Karim, and M. Rafiq, “Digital connectivism in STEM education: Enhancing interdisciplinary collaboration through AI and data-driven learning,” Educ Inf Technol (Dordr), vol. 28, no. 9, pp. 11987–12005, 2023, doi: 10.1007/s10639-023-11352-5.
D. R. Garrison and N. D. Vaughan, Blended learning in higher education: Framework, principles, and guidelines (2nd ed.). San Francisco: Jossey-Bass, 2021.
W. Westera, “Inside Out: A Scoping Review on Optimism, Growth Mindsets, and Positive Psychology for Child Well-Being in ECEC,” Educ Sci (Basel), vol. 13, no. 1, p. 29, 2023, doi: 10.3390/educsci13010029.
S. Jain, P. Thakur, and A. Kumar, “AI-supported collaborative learning environments: Enhancing engagement and personalization in higher education,” Educ Inf Technol (Dordr), vol. 29, no. 1, pp. 455–478, 2024.
M. Bond and S. Bedenlier, “Do virtual schools deliver in rural areas? A longitudinal analysis of academic outcomes,” Comput Educ, vol. 210, p. 104789, Jul. 2023, doi: 10.1016/j.compedu.2023.104789.
D. Santoso and J. Lee, “Adaptive AI learning systems to enhance critical thinking and decision-making in STEM education,” Computers & Education Open, vol. 7, 2024, doi: 10.1016/j.caeo.2023.100273.
Y. Kim, H. Park, and D. Cho, “Integrating neurofeedback and emotional analytics in AI-driven reflective learning systems,” Comput Human Behav, 2024, doi: 10.1016/j.chb.2023.108035.
W. Y. Lim, S. M. Tan, and C. S. Lee, “AI-driven emotion analytics for reflective learning in higher education,” British Journal of Educational Technology, vol. 55, no. 4, pp. 1465–1485, Jul. 2024, doi: 10.1111/bjet.13391.
V. Marin-Díaz, M. P. Reche, and M. Jiménez, “Digital reflective learning and emotional intelligence: A meta-analytic review,” Educational Technology Research and Development, vol. 70, no. 5, pp. 2221–2240, 2022, doi: 10.1007/s11423-022-10089-7.
M. Fauth, L. Oberlechner, and M. Sailer, “Emotion regulation in digital learning environments: An integrative review and future research agenda,” Front Psychol, vol. 16, pp. 152–174, 2025, doi: https://doi.org/10.3389/fpsyg.2025.000152.
L. Hsu, J. Chen, and C. Chou, “AI-powered emotion monitoring in reflective learning for science education,” Interactive Learning Environments, vol. 33, no. 1, pp. 44–62, 2025, doi: 10.1080/10494820.2025.00044.
S. N. Rahmi, M. Megawati, H. Alberida, and M. Fadilah, “Assessment of biology learning outcomes in education: A systematic literature review,” Biosfer: Jurnal Pendidikan Biologi, vol. 18, no. 1, pp. 10–5, 2025, doi: 10.21009/biosfer.2025.18102.
W. Utami and M. D. Sari, “Digital learning portfolios to foster self-regulated learning in biology education,” Jurnal Pendidikan Biologi Indonesia, vol. 10, no. 2, pp. 102–112, 2024.
T. , Mulyadi and R. Hakim, “AI-assisted reflective journaling to foster emotional intelligence in biology education,” Jurnal Inovasi Pendidikan Sains, vol. 9, no. 1, pp. 34–49, 2025, doi: 10.15294/jips.v9i1.12345.
M. Bower, J. Kenney, and A. Cram, “Digital reflection as a tool for fostering collaboration and critical thinking in STEM education,” Australasian Journal of Educational Technology, vol. 39, no. 2, pp. 1–18, 2023.
M. H. Immordino-Yang and L. Darling-Hammond, “Neuroscience and the learning sciences: Aligning brain, mind, and education,” Mind, Brain, and Education, vol. 17, no. 2, pp. 123–137, Nov. 2023, doi: 10.1111/mbe.12345.
L. Chen and H. Park, “AI-augmented neurolearning environments: Enhancing reflective cognition in STEM education.,” Comput Educ, 2024, doi: https://doi.org/10.1016/j.compedu.2023.104732.
J. Nouri and A. Rapp, “Neuroconnectivism: Bridging brain-based learning and digital networks in higher education,” Educational Technology & Society, vol. 26, no. 4, pp. 88–101, 2023, Accessed: Nov. 30, 2025. [Online]. Available: https://www.jstor.org/stable/26909313
D. Pratiwi, S. Harto, and R. N. Jowei, “STRUKTUR DAN KOMPOSISI JENIS TUMBUHAN DI SEKITAR PERSARANGAN BURUNG PINTAR (Amblyornis inornatus),” JURNAL KEHUTANAN PAPUASIA, vol. 4, no. 1, pp. 65–75, Jan. 2020, doi: 10.46703/jurnalpapuasia.Vol4.Iss1.97.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Farhan Ramadhan, Muhiddin Palennari

This work is licensed under a Creative Commons Attribution 4.0 International License.


















