Edi Sunjayanto Masykuri, Edi Sunjayanto
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Reconstructing the Al-Islam and Kemuhammadiyahan Curriculum through Pedagogical Deep Learning Hermawan, Hermawan; Firdaus, Firdaus; Masykuri, Edi Sunjayanto
Jurnal Studi Islam dan Kemuhammadiyahan (JASIKA) Vol. 6 No. 2 (2026)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jasika.v6i2.255

Abstract

Al-Islam and Kemuhammadiyahan (AIK) learning in Muhammadiyah higher education often emphasizes cognitive mastery, while value internalization requires more reflective, contextual, and socially oriented learning. This study aimed to reconstruct the AIK curriculum through a pedagogical deep learning approach and examine its implementation in relation to student engagement, value internalization, and Muhammadiyah identity. The study employed Research and Development using Design-Based Research (DBR) through three iterative cycles involving 80 students in two AIK classes, two lecturers, and one university administrator at Universitas Muhammadiyah Purwokerto. The curriculum prototype was reviewed by two experts for theoretical alignment, pedagogical relevance, and feasibility, followed by revision and limited implementation over three weeks. Data were collected through observations, interviews, Focus Group Discussions, documentation, and questionnaires and analyzed thematically and descriptively. Student engagement increased across all indicators, including class discussion (45%–78%) and value reflection (38%–74%). Value-internalization indicators also increased, particularly reflection on Islamic values (41%–79%). Muhammadiyah identity increased in cognitive (85%–90%), affective (43%–77%), and social-behavior (46%–73%) dimensions. These findings provide context-specific descriptive evidence rather than causal proof.
BRITISH COUNCIL LEARNENGLISH KIDS AS ASYNCHRONOUS LEARNING TO IMPROVE YOUNG LEARNERS’ WRITING Lestari, Dian Dwi; Dewi, Puspa; Masykuri, Edi Sunjayanto
Premise: Journal of English Education and Applied Linguistics Vol. 15 No. 2 (2026): Premise Journal: e-ISSN 2442-482x, p-ISSN 2089-3345
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/pj.v15i2.16261

Abstract

To improve the English writing abilities of fifth-grade primary school students in Kebumen Regency, Indonesia, this study examines the efficacy of using the British Council for Kids application within a deep learning-based Mobile Assisted Language Learning (MALL) in asynchronous learning model. This study used a pre-experimental one-group pretest-posttest design using a quantitative methodology. A cluster sampling strategy was used to choose 74 kids as participants. A pre-test, two therapy sessions with activities from the British Council for Kids, independent practice, a post-test, and a perception questionnaire made up the four-week intervention. A Paired t-test and N-gain score computation using SPSS were used for statistical data analysis. The mean score increased significantly from 65.95 in the pre-test to 87.97 in the post-test. The mean score rose from 65.95 in the pre-test to 87.97 in the post-test, signifying a significant enhancement in students' writing proficiency. The N-gain analysis showed a mean score of 0.6371, indicating moderate efficacy. In conclusion, including the British Council for Kids into a MALL-based deep learning paradigm successfully improves writing abilities and cultivates a love of learning. To give young students more interesting and fulfilling educational experiences, the study promotes the use of MALL platforms in English classes. REFERENCES Agyeman, N. Y. B. (2024). Deep learning in high schools: Exploring pedagogical approaches for transformative education. Humanika, 24(2), 111–126. https://doi.org/10.21831/hum.v24i2.71350 Alhadiah, A. (2023). Undergraduate EFL learners’ use and acceptance of mobile-assisted language learning: A structural equation modeling approach. World Journal of English Language, 13(3), 253. https://doi.org/10.5430/wjel.v13n3p253 Alnujaidi, S. (2021). Adoption of mobile assisted language learning (MALL) in Saudi Arabian EFL classrooms. 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Building English Literacy Through Mall and Deep Learning: Challenges and Needs of Elementary School English Teachers Dewi, Puspa; Anjarini, Titi; Masykuri, Edi Sunjayanto
IJORER : International Journal of Recent Educational Research Vol. 7 No. 5 (2026): September
Publisher : Faculty of Teacher Training and Education Muhammadiyah University of Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46245/ijorer.v7i5.1489

Abstract

Objective: This study analyzes the challenges and needs of elementary school teachers in the southern coastal areas of Central Java and the Special Region of Yogyakarta in teaching English reading and writing, and identifies the need to develop a digital learning model based on Mobile Assisted Language Learning (MALL) with a deep learning approach. Method: This study employed a qualitative case study design to explore the challenges and needs of elementary school English teachers in implementing English reading and writing instruction in coastal communities. The study involved English teachers from Purworejo, Kebumen, and Kulon Progo as participants. Data were collected through questionnaires and semi-structured interviews to obtain an in-depth understanding of teachers’ experiences, challenges, and expectations regarding the implementation of a deep learning-based MALL model. Result: The results indicate that conventional methods are ineffective in fostering deep understanding and student interest. Key challenges faced by teachers include limited English language proficiency, lack of teaching experience, and minimal training on deep learning approaches. Furthermore, limited lesson time and issues such as student addiction to online games are also obstacles. The needs analysis indicates an urgent need for innovative digital learning models. The majority of teachers believe that MALL can improve students’ English literacy and see great potential in an adaptive system that can automatically adjust the difficulty level. Although school infrastructure is considered adequate, teachers still need further training and support for effective implementation. Novelty: This study concludes that the deep learning-based MALL model is a relevant solution to address existing challenges, with a focus on meaningful and enjoyable learning experiences.