Interactive Motivational Need Analysis for Mapping Digital Literacy Gaps and Learning Motivation in Islamic Religious Education

Ana Dwi Lestari; Sutiah Sutiah; M Zubad Nurul Yaqin; Falih Akmal Wicaksono

doi:10.61987/edsojou.v3i2.1987

Authors

Ana Dwi Lestari Universitas Islam Negeri Maulana Malik Ibrahim Malang
Sutiah Sutiah Universitas Islam Negeri Maulana Malik Ibrahim Malang
M Zubad Nurul Yaqin Universitas Islam Negeri Maulana Malik Ibrahim Malang
Falih Akmal Wicaksono Universitas Islam Negeri Maulana Malik Ibrahim Malang

DOI:

https://doi.org/10.61987/edsojou.v3i2.1987

Keywords:

ManyChat Chatbot, Interactive Motivational Need Analysis, ARCS Model, Islamic Cultural History, Learning Motivation

Abstract

Islamic Cultural History (SKI) learning in the digital era faces a motivation gap in which students’ high digital literacy is not accompanied by strong engagement in classroom learning. This study applied the Interactive Motivational Need Analysis (IMNA) framework to identify students’ motivational and technological needs and to formulate instructional parameters based on the ARCS model (Attention, Relevance, Confidence, Satisfaction) in the Independent Curriculum Phase E. The research represents the analysis stage of a Research and Development (R&D) study employing the ADDIE model. Thirty tenth-grade students of state Islamic high school participated in the study. Data were collected through ARCS-based motivation questionnaires, classroom observations, interviews, and a diagnostic pretest, then analyzed using descriptive statistics and qualitative data analysis. The findings revealed that students’ initial learning motivation was below the expected level, with an average score of 104.28 out of 160. The lowest scores were found in the Attention and Confidence dimensions. This condition was reflected in the low cognitive achievement, indicated by a pretest mean score of 32.22 on the Umayyad and Abbasid materials. Observation and interview results showed students’ preference for interactive digital environments over static text-based learning. The IMNA framework ultimately identified the need for adaptive and personalized learning media, leading to the recommendation of Conversational Scaffolding Learning through the “Ruang SKI” ManyChat chatbot to enhance learning motivation and engagement.

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