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All Journal Journal Neosantara Hybrid Learning International Journal of Educational Narratives
Rudy Surbakti
STMIK Kristen Neumann

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BRAIN-BASED LEARNING STRATEGIES FOR PERSONALIZED HYBRID EDUCATION Raul Gomez; Clara Mendes; Rudy Surbakti
Journal Neosantara Hybrid Learning Vol. 4 No. 3 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jnhl.v4i3.4233

Abstract

Personalized hybrid education offers flexible learning opportunities, yet technological adaptation alone often fails to address differences in attention, memory, cognitive load, prior knowledge, and self-regulation that shape individual learning. This study examined the effectiveness of evidence-informed brain-based learning strategies within personalized hybrid education and developed an adaptive framework for cognitively responsive instruction. A quasi-experimental mixed-methods design compared students receiving brain-informed personalized hybrid instruction with those experiencing conventional hybrid learning. The intervention integrated prior-knowledge activation, retrieval practice, spaced learning, cognitive-load management, adaptive scaffolding, formative feedback, and metacognitive reflection across physical and digital environments. Findings indicated stronger academic achievement, knowledge retention, cognitive engagement, motivation, and self-regulated learning among students receiving personalized instruction, accompanied by more manageable cognitive demands. Learning analytics and qualitative evidence further demonstrated that effective personalization required dynamic adjustments based on learner readiness, performance, progress, and support needs rather than fixed learning-style classifications. The study concludes that brain-informed personalization is most effective when grounded in credible learning science and implemented through continuous cycles of diagnosis, adaptation, retrieval, feedback, monitoring, and recalibration. The proposed framework advances personalized hybrid education by integrating cognitive responsiveness, pedagogical orchestration, and adaptive support while avoiding unsupported neuromyth-based instructional assumptions in contemporary educational practice.
Cognitive Load Theory: Implications for Instructional Design in Digital Classrooms Rudy Surbakti; Satria Evans Umboh; Ming Pong; Sokha Dara
International Journal of Educational Narratives Vol. 2 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijen.v2i6.1659

Abstract

The rapid integration of digital tools in education has transformed classroom environments, creating new opportunities and challenges for instructional design. One key area of focus is the management of cognitive load, which refers to the mental effort required to process information during learning. Cognitive Load Theory (CLT) offers insights into how instructional materials can be optimized to improve learning outcomes. In digital classrooms, the effective design of instructional content becomes even more critical due to the increased multimedia elements and potential for cognitive overload. This study aims to explore the implications of Cognitive Load Theory (CLT) for instructional design in digital classrooms. It examines how digital tools, such as multimedia content and interactive activities, impact learners’ cognitive load and suggests strategies for reducing extraneous cognitive load to enhance learning efficiency and effectiveness. A mixed-methods approach was used, combining quantitative surveys to assess students’ cognitive load during digital learning activities and qualitative interviews with instructors to understand their perspectives on instructional design challenges. The study was conducted across several digital learning environments in higher education. The findings indicate that digital learning environments often lead to high cognitive load, particularly when multimedia content is poorly integrated. However, using principles from CLT, such as segmenting information and reducing unnecessary complexity, can significantly lower cognitive load and improve student learning outcomes. Both students and instructors reported that well-designed digital content led to better engagement and more efficient learning. The study concludes that applying Cognitive Load Theory to instructional design in digital classrooms can enhance learning by minimizing cognitive overload. Educators should be mindful of cognitive load when creating digital learning experiences to improve student performance and engagement.
Co-Authors Clara Mendes Ming Pong Raul Gomez Satria Evans Umboh Sokha Dara