cover
Contact Name
Harun Joko Prayitno
Contact Email
harun.prayitno@ums.ac.id
Phone
+6282242301929
Journal Mail Official
jdl@ums.ac.id
Editorial Address
Jalan Ahmad Yani, Pabelan, Surakarta, Jawa Tengah 57169
Location
Kota surakarta,
Jawa tengah
INDONESIA
Journal of Deep Learning
ISSN : -     EISSN : 31107591     DOI : 10.23917/jdl
Core Subject : Education, Social,
The Journal of Deep Learning is dedicated to advancing research on deep learning as a methodological approach in education and AI-based technological development. We emphasize deep learning integrated with artificial intelligent (AI) that fosters meaningful, joyful, and mindful education—rooted in authentic, holistic learning experiences that support students’ spiritual, cognitive, social, and emotional development. 1.⁠ ⁠Fostering Mindful Education Practices We seek contributions that explore how deep learning methodologies can cultivate mindfulness in educational settings. This encompasses promoting self-awareness, reflective practices, metacognition, and emotional regulation to support holistic student development. 2.⁠ ⁠Deep Learning for Meaningful Education We invite articles that examine how deep learning methodologies such as inquiry-based learning, problem-based learning, and project-based learning support students in constructing meaningful knowledge. Studies may focus on developing students’ critical thinking, conceptual understanding, and ability to connect new knowledge with real-life contexts. 3.⁠ ⁠Promoting Joyful Learning Experiences We welcome research on how deep learning approaches can foster joy in learning by encouraging curiosity, creativity, and intrinsic motivation. This includes studies on creating engaging learning environments, designing stimulating learning activities, and supporting positive teacher-student interactions. 4.⁠ ⁠Integration of Technology in Deep Learning Pedagogy We encourage studies that examine how technology such as learning management systems, digital tools, and educational apps can be used to support deep learning methodologies. Submissions should highlight how technology enhances or challenges the implementation of deep, meaningful, joyful, and mindful learning. 5.⁠ ⁠Evaluation and Assessment of Deep Learning Outcomes We welcome research on effective evaluation and assessment strategies aligned with deep learning approaches. This includes authentic assessment, formative assessment, and performance-based tasks that capture students’ understanding, creativity, and reflective abilities.
Articles 3 Documents
Search results for , issue "vol. 2, no. 2, december 2026" : 3 Documents clear
Transformational Leadership, School Autonomy, and Deep Learning in Vocational Education: A Qualitative Case Study Nurahmad Fauzi; Bambang Sumardjoko; Sri Lahir; Suni Tuti; Adi Jufriansah; Bayu Wardhana; Iwan Junaedi; Ita Nuryana
Journal of Deep Learning Vol. 2, No. 2, December 2026
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v2i2.15528

Abstract

School autonomy is essential for enabling Vocational High Schools (SMKs) to respond to changing educational and labor-market demands. However, formal autonomy does not always translate into institutional flexibility and pedagogical innovation. This study analyzes principals’ transformational leadership strategies for strengthening school autonomy and creating conditions that support Deep Learning through meaningful, mindful, and joyful learning. A qualitative intrinsic case study design was employed, using semi-structured interviews, non-participant observations, and document analysis involving principals, vice principals, teachers, vocational program coordinators, and other relevant personnel. Data were analyzed using the interactive model of Miles, Huberman, and Saldaña. The findings reveal three interconnected strategies: (1) articulating an autonomy-oriented vision and reconstructing bureaucratic culture; (2) empowering teachers through participation, delegation, trust, and professional autonomy; and (3) expanding school autonomy through policy negotiation and external networking, particularly with education authorities and DUDI. These strategies created organizational conditions conducive to Deep Learning by supporting contextual and authentic learning, reflective engagement, and engaging and collaborative learning experiences. The study contributes to educational leadership scholarship by demonstrating how transformational leadership can translate formal school autonomy into organizational capacity that supports pedagogical transformation. Practically, the findings highlight distributed leadership, teacher empowerment, accountability, pedagogical flexibility, and strategic industry partnerships as important mechanisms for strengthening autonomous and responsive vocational education.
Contextual Media-Based Deep Learning in Elementary Education: A Qualitative Study of Meaningful and Joyful Learning through an Ecoenzyme Project Nela Rosita; Harun Joko Prayitno; Indri Indri; Khoirul Anwar; Fajar Riza Ul Haq; Suyanto Suyanto; Azmi Khusnani
Journal of Deep Learning Vol. 2, No. 2, December 2026
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v2i2.15578

Abstract

The implementation of Deep Learning in elementary education requires learning experiences that are meaningful, engaging, and relevant to students' daily lives. However, research on contextual media-based Deep Learning in elementary schools remains limited. This study aimed to explore the implementation of Deep Learning through contextual media using an ecoenzyme project in elementary education. A qualitative descriptive approach was employed at Elementary School Muhammadiyah Program Khusus Pracimantoro. Data were collected through observations, semi-structured interviews, and documentation, and analyzed using the interactive model of Miles et al. with methodological triangulation to ensure data credibility. The findings reveal that contextual media promote meaningful learning by connecting instructional content with authentic experiences, thereby enhancing students' conceptual understanding, critical thinking, and reflective learning. In addition, the ecoenzyme project fostered joyful learning by improving students' motivation, collaboration, communication, and environmental awareness. The study also demonstrates that effective Deep Learning can be implemented through simple contextual media without relying on sophisticated digital technologies. These findings contribute to the development of student-centered learning strategies and provide practical implications for implementing Deep Learning in elementary education.
Deep Learning as an Integrated Pedagogical Framework: Synthesizing Mindful, Meaningful, and Joyful Learning for Transformative Educational Experiences Eni Kurnianingsih; Harun Joko Prayitno; Abdul Mu’ti; Zakiyuddin Baidhawy; Adi Jufriansah
Journal of Deep Learning Vol. 2, No. 2, December 2026
Publisher : Universitas Muhammadiyah Surakarta in Collaboration with Kemdikdasmen RI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jdl.v2i2.16008

Abstract

The transformation of 21st-century education requires a shift from knowledge transmission toward learning approaches that emphasize deeper understanding, active engagement, and meaningful experiences. The deep learning approach has emerged as a pedagogical framework that integrates meaningful learning, mindful learning, and joyful learning to develop students’ cognitive, affective, and metacognitive dimensions. However, previous studies have often examined these dimensions separately, resulting in limited understanding of their integration within a comprehensive framework. This study aims to analyze the deep learning approach, identify its implementation patterns, challenges, and implications for improving educational quality. A descriptive qualitative approach was employed through literature synthesis, supported by teacher perceptions, classroom observations, and interviews. Data were analyzed using qualitative descriptive analysis and validated through technique triangulation. The findings reveal that deep learning effectively combines meaningful learning as a foundation for conceptual understanding, joyful learning as a driver of engagement, and mindful learning as a mechanism for reflection and metacognitive development. However, implementation remains dominated by meaningful and joyful learning, while mindful learning receives limited attention. This study highlights that the main challenge of deep learning lies in translating its principles into systematic reflective practices. The findings contribute to pedagogical development by emphasizing the importance of balanced integration among the three dimensions to create meaningful, enjoyable, and sustainable learning experiences.

Page 1 of 1 | Total Record : 3