TY  - JOUR
UR  - https://e-journal.undikma.ac.id/index.php/pedagogy/article/view/19158
IS  - 2
SP  - 779
N2  - This  study  aims  to  explore  how  Deep Learning  (DL)  contributes  to meaningful   learning   in   response   to   the   increasing   demand   for   ethical, transparent,  and  student-centered  applications  of  Artificial  Intelligence  (AI)  in education.  The  study  employs  a  bibliometric  analysis  of  110  Scopus-indexed publications  published  between  2015  and  2025,  using  Biblioshiny  in  the  R Bibliometrix  package  to  identify  research  trends,  key  contributors,  institutional productivity, and thematic developments. The analysis encompasses publication trends,   citation   patterns,   author   and   country   productivity,   collaboration networks,  and  keyword  co-occurrence.  The  findings  indicate  that,  although  the majority  of  studies  originate  from  computer  science  and  engineering,  there  has been  a  growing  shift  toward  education  and  the  social  sciences,  reflecting  an increasingly  interdisciplinary  orientation,  particularly  after  2020.  Emerging themes  such  as  explainable  AI,  adaptive  learning,  and  ethical  AI  suggest  a transition  from  technology-driven  innovation  toward  pedagogy-oriented  and ethically  grounded  practices.  Keyword  co-occurrence  analysis  reveals  three dominant  thematic  clusters:  (1)  explainable  AI  in  pedagogy,  (2)  adaptive learning systems, and (3) ethical and human-centered AI in education. This shift reflects a  broader movementtoward human-centered AI that enhances learning relevance,  personalization,  and  engagement.  Overall,  the  integration  of  DL  in education   is   evolving   beyond   technical   efficiency   to   support   meaningful, ethical, and learner-centered educational experiences.
A1  - Salsabila, Nurul Mawadah
A1  - lismawati, lismawati
VL  - 13
TI  - Mapping the Landscape of Deep Learning in Meaningful Principles: A Decade-Long Bibliometric Review (2015?2025)
AV  - public
Y1  - 2026/04/20/
EP  - 789
JF  - Mapping the Landscape of Deep Learning in Meaningful Principles: A Decade-Long Bibliometric Review (2015?2025)
ID  - repository53009
ER  -