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Enhancing Online Learning Experiences through Personalization Utilizing Recommendation Algorithms Caroline; Oroh, Oliviane; Pada, Damir
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 3 (2023): DECEMBER 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i3.1852

Abstract

This research investigates the implementation and impact of personalized learning systems underpinned by advanced recommendation algorithms in the realm of online education. The study encompasses a diverse group of participants from various educational backgrounds and explores their interactions with the personalized learning platform. The key findings of this research are noteworthy. Participants who had access to the personalized learning environment exhibited a substantial increase in engagement, satisfaction, and learning outcomes compared to those in the control group. This signifies the transformative potential of personalized learning in online education. The research emphasizes the critical role of personalization in enhancing learner engagement and satisfaction. It highlights how learners actively engaged with the system, making use of personalized recommendations to tailor their learning experiences. Moreover, the study sheds light on the positive impact of personalization on learning outcomes, indicating that learners achieved higher academic performance when their learning experiences were customized to their needs and preferences. In addition to its benefits for learners, the research underscores the advantages of personalized learning for instructors. The system provided instructors with valuable insights into each learner's progress and challenges, enabling more targeted and effective support. While the study demonstrates the effectiveness of personalized learning, it acknowledges certain limitations, including a relatively limited sample size and short duration. Future research endeavors could involve larger and more diverse samples and extend the study duration to gain a more comprehensive understanding of the long-term effects of personalized learning. In conclusion, this research contributes to the growing body of literature on personalized learning in online education. It provides compelling evidence that personalized learning, facilitated by sophisticated recommendation algorithms, can significantly enhance the online learning experience. The findings offer insights for educators and institutions looking to integrate personalized learning features into their online platforms to improve learner engagement, satisfaction, and learning outcomes.
Deep Learning Implementation Strategies in Indonesia National Curriculum: A Culturally Responsive Framework for Pinrang Regency Pada, Damir; S, Jumadi
International Journal Education and Computer Studies (IJECS) Vol. 5 No. 3 (2025): NOVEMBER
Publisher : Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijecs.v5i3.5508

Abstract

This research develops implementation strategies for Deep Learning approaches within Indonesia's National Curriculum specifically adapted for Pinrang Regency's educational settings. The study employs descriptive qualitative methodology through document analysis and literature review to create strategic frameworks addressing regional educational challenges while honoring Buginese cultural heritage. Five primary strategic domains emerged: conceptual foundation development integrating "sipakainge" and "sipakatau" values; national curriculum adaptation through low-tech high-impact approaches; practical school-level implementation utilizing local phenomena and collaborative "assitulung-tulungeng" patterns; educator capacity building via district-based learning communities; and evaluation systems with situational indicators for sustainability. The research demonstrates that Deep Learning principles can be successfully adapted to diverse local conditions while maintaining pedagogical rigor through systematic integration of cultural wisdom, economic potential, and available resources. The strategic framework creates authentic learning experiences engaging students meaningfully while building 21st-century skills through community partnerships, intergenerational learning, and cultural documentation projects. Findings reveal that effective educational reform requires adaptive strategies responding to local conditions rather than standardized approaches, emphasizing pedagogical creativity over technological sophistication. The framework provides practical guidance for educational leaders implementing culturally responsive Deep Learning approaches, offering replication potential across Indonesian regions through systematic balancing of national standards with local distinctiveness. Success measurement encompasses not only academic outcomes but also cultural identity strengthening, community cohesion enhancement, and students' sense of place development within local and global communities.