Journal of Education and Learning (EduLearn)
Vol 20, No 4: November 2026

Bridging teacher talk time and multiple intelligences for deep learning

Pipit Muliyah (Universitas Negeri Yogyakarta)
Margana Margana (Universitas Negeri Yogyakarta)
Dyah Setyowati Ciptaningrum (Universitas Negeri Yogyakarta)
Megan Jinabe (Universitas Negeri Yogyakarta)
Desi Wijayanti Ma'rufah (Universitas Islam Negeri Prof. K.H. Saifuddin Zuhri Purwokerto)
Muhammad Danial (Universitas Negeri Yogyakarta)



Article Info

Publish Date
01 Nov 2026

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.

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Journal Info

Abbrev

EduLearn

Publisher

Subject

Humanities Education Library & Information Science Social Sciences Other

Description

Journal of Education and Learning (EduLearn) ISSN: 2089-9823, e-ISSN 2302-9277 is a multi-disciplinary, peer-refereed open-access international journal which has been established for the dissemination of state-of-the-art knowledge in the field of education, teaching, development, instruction, ...