Bridging teacher talk time and multiple intelligences for deep learning

Pipit Muliyah, Margana Margana, Dyah Setyowati Ciptaningrum, Megan Jinabe, Desi Wijayanti Ma'rufah, Muhammad Danial

Abstract


This study investigates the systemic tension between the dominance of teacher talk time (TTT) and the urgent need for deep learning strategies tailored to students’ multiple intelligences (MI) within the context of teaching English to young learners (TEYL). Adopting a descriptive mixed-methods design with a concurrent triangulation strategy, this research was conducted across a representative developing region in Central Java, Indonesia, involving a stratified sample of 450 upper-primary students and 45 English teachers. Data were collected using the student learning profile inventory (SLPI), TTT observation trackers, and semi-structured interviews. The findings reveal a critical pedagogical dissonance: while 72% of students exhibit a clear dominance in bodily-kinesthetic and visual-spatial intelligences profiles that biologically necessitate active, multimodal engagement classroom interactions remain heavily monopolized by teachers, who occupy 75% of lesson duration with verbal instruction. This excessive TTT acts as a significant constraint to the implementation of differentiated instruction (DI), effectively trapping students in surface-level rote memorization and inhibiting the development of communicative competence. The study concludes that the successful implementation of student-centered curricula requires a fundamental deconstruction of the traditional “teacher-as-broadcaster” model. Reducing TTT is identified not merely as a classroom management technique, but as a prerequisite for creating the temporal and cognitive space necessary for MI-based differentiation and deep learning.

Keywords


Deep learning; Differentiated instruction; Multiple intelligences; Embodied cognition; Teacher talk time

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DOI: https://doi.org/10.11591/edulearn.v20i4.27098

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Journal of Education and Learning (EduLearn)
p-ISSN: 2089-9823; e-ISSN: 2302-9277
Published by Intelektual Pustaka Media Utama (IPMU) in collaboration with the Institute of Advanced Engineering and Science (IAES).

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