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Journal of Digital Learning and Distance Education
Published by Radinka Jaya Utama Publisher
ISSN : -     EISSN : 29646685     DOI : http://doi.org/10.56778/jdlde
Core Subject : Humanities, Science, Education, Social,
Humanities Computer Science & IT Languange, Linguistic, Communication & Media Social Sciences Other
The Journal of Digital Learning and Distance Education (JDLDE) aims to provide space for teachers, postgraduate students, Ph.D. candidates, lecturers, and researchers in publishing their work or research results. Journal of Digital Learning and Distance Education (JDLDE) publishes research results with focus and scope: information technology, digital learning, distance education, mobile learning, web-based learning, educational technology, e-learning, blended learning, digital classrooms, virtual learning, and all research aspects in digital learning, and education.
Arjuna Subject : Umum - Umum
Articles 220 Documents
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Predicting and Preventing Academic Misconduct Using Behavioral Analytics: An Ethical Framework for Fair Detection and Human Oversight Oise, Godfrey
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 7 (2025): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i7.594

Abstract

This study introduces the Ethical Behavioral Analytics Framework (EBAF), a fairness-driven and explainable artificial intelligence system designed to predict and prevent academic misconduct. The framework integrates behavioral analytics, deep learning (LSTM), and human oversight to ensure ethical transparency and accountability in academic integrity management. By combining behavioral indicators such as submission timing, editing duration, and engagement regularity with textual features, EBAF identifies deviations from normal learning behavior that may indicate misconduct. Using a dataset of student behavioral and performance data sourced from Kaggle, the model achieved an overall accuracy of 85%, effectively distinguishing between authentic and plagiarized submissions while maintaining minimal bias. The incorporation of explainable AI tools, including SHAP and LIME, provided interpretable reasoning behind predictions, allowing educators to understand and validate model decisions. A human-in-the-loop mechanism further ensured that automated outputs were reviewed contextually, promoting fairness, accountability, and trust. The findings demonstrate that ethical and explainable AI can coexist with high predictive performance, advancing the responsible application of machine learning in education. By embedding fairness auditing, transparency, and human oversight, EBAF transforms academic misconduct detection from a punitive process into a preventive and educational approach. This work contributes to both research and practice by aligning computational intelligence with ethical accountability. Future research will expand the framework across diverse academic environments, incorporating multimodal behavioral data and adaptive feedback systems to enhance fairness, interpretability, and scalability in AI-based academic integrity solutions.
This or That? Perception of Filipino Generation Z and Generation Alpha in Using Common Emojis: Semantics and Typology Tamaño, Lexxus Dominic
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 7 (2025): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i7.600

Abstract

Emojis have become integral to digital communication, functioning as visual cues that convey emotion, intent, and social meaning beyond literal text. Guided by Semiotic Theory, this research investigates generational differences in how Filipino Generation Z and Generation Alpha perceive and classify common emojis in terms of semantics and typology. A convergent parallel mixed methods design was employed, involving surveys and structured interviews with 16 students equally distributed between the two generations. Quantitative results from the Chi-Square Test of Independence indicated a statistically significant generational difference in emoji usage (χ² = 26.74, p < 0.05). Qualitative thematic analysis revealed that Gen Z frequently interprets emojis symbolically or sarcastically utilizing them to signal passive-aggression, express exaggerated humor, or convey disapproval. In contrast, Gen Alpha tends to assign more literal and emotionally transparent meanings to the same icons. Despite the limited sample size restricting broad generalizability, the findings demonstrate distinct generational patterns in digital expression. These differences suggest potential sources of miscommunication in online and educational environments. The study recommends the development of a digital literacy toolkit to foster generational awareness and promote clearer, more empathetic emoji-mediated communication.
Teaching Strategy Theory for Effective Classroom Setting Mallillin, Leovigildo Lito
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 7 (2025): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i7.608

Abstract

This study investigates the impact of various teaching strategy theories on establishing an effective classroom environment, specifically focusing on seven key dimensions: visualization, cooperative learning, inquiry-based instruction, differentiation, classroom technology, behavior management, and professional development. Adopting a descriptive quantitative research design, the study surveyed 150 respondents to evaluate the efficacy of these strategies. The results indicate that deliberate practice and the strategic enhancement of teaching methods significantly bolster the learning process. Specifically, the findings highlight that effective strategies foster student self-esteem and confidence by encouraging active verbal engagement and responsiveness to peer ideas. Furthermore, the data supports the integration of inquiry-based instruction as a vital approach to achieving learning objectives and provides teachers with high-impact tools for lesson delivery. The study also emphasizes the necessity of incorporating classroom technology and digital media to actively engage students, alongside behavior management techniques that transform classroom activities into engaging and stimulating experiences. Finally, the results demonstrate the value of professional development and reflective practice, enabling educators to adapt to modern educational trends and competencies. Correlation analysis reveals a significant relationship between the application of teaching strategy theories and the overall effectiveness of the classroom setting as perceived by the respondents.
Digital Intelligence (DQ): Demands and Challenges in the Educational System Mallillin, Leovigildo Lito; Sammy Q. DOLBA
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 8 (2026): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i8.610

Abstract

This study investigates the integration of Digital Intelligence (DQ) within the modern educational system, identifying it as both a critical demand and a significant challenge. The research explores four key dimensions: the demands and challenges of DQ, the conceptual definition and competencies of DQ, institutional preparation, and the practical integration of DQ in learning environments. Adopting a qualitative research design, the study conducted in-depth analysis through the participation of thirty (30) purposefully selected respondents. Results indicate that the demands of DQ require the embedding of digital literacy, digital creativity, and digital safety into curriculum tools and resources. DQ is defined as a holistic set of social, emotional, and cognitive abilities that empower both lecturers and students to navigate the digital world responsibly. Regarding preparation, the study highlights the necessity of institutional readiness, particularly in strengthening Information and Communication Technology (ICT) curriculum policies and digital literacy programs. However, the integration process reveals a critical "digital inequality," characterized by outdated software, inconsistent internet connectivity, and unequal access to devices, which threatens to leave certain students behind. The study concludes that while DQ is essential for pedagogical advancement, addressing infrastructure disparities is a prerequisite for its successful implementation.
an Analytical Study of Augmented and Virtual Reality in Online Learning: Exploring Technological Advancements and Pedagogical Impacts MITHUN R; Archana M; Kulkarni, Maltesh S; Varsha T R
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 7 (2025): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i7.614

Abstract

This research presents an analytical study on the integration of Augmented Reality (AR) and Virtual Reality (VR) in online learning, focusing on recent technological advances and their pedagogical implications. The study explores how immersive technologies transform digital education by enhancing student engagement, conceptual understanding, and experiential learning. Utilizing a descriptive quantitative research design, data were collected through a targeted survey of 12 participants, including students and educators experienced in AR and VR environments. The findings indicate that while awareness and adoption of AR and VR are increasing, a significant portion of learners remains unfamiliar with these tools or lacks access due to high costs and infrastructure barriers. Nevertheless, a majority of respondents reached a consensus that AR and VR significantly improves engagement and comprehension compared to traditional online instruction. The study identifies key technological enablers such as affordable hardware, mobile accessibility, AI integration, and cloud computing that have facilitated broader adoption. However, challenges persist, particularly regarding limited access to high-end devices and a lack of longitudinal empirical research on long-term learning efficacy. The study concludes that AR and VR possesses the power to transform online education, provided that institutions prioritize investments in faculty training, specialized content development, and inclusive access strategies.
Comprehensive Guided Inquiry Learning Model through Digital Concepts for Aquaculture Students: A Review Megahati S, Ruth Rize Paas; Yuliana, Liza
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 7 (2025): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i7.627

Abstract

The abstract nature of the topics is easily understood while learning chemistry through guided inquiry. This article employs the A Review (SLR) technique to review eleven papers released between 2018 and 2023 that deal with teaching chemistry using various guided inquiry models. Three online article databases—ERIC, Scopus, and Google Scholar—were used to retrieve articles methodically. The information in this review will be helpful to educators and researchers who work in chemical education in understanding guided inquiry models, how they impact chemical learning outcomes, and how to apply them to improve students' comprehension of chemistry. The review's conclusions show how various guided inquiry strategies immerse students in a problem, offer them an investigation to work through and provide guidance on how to solve the problem. Guided inquiry models influence chemistry learning outcomes by enhancing metacognition, concept understanding, critical thinking skills, science process skills, learning outcomes, creative thinking abilities, and reducing misconceptions. Many learning models or strategies, including guided inquiry, guided inquiry-based on blended learning, guided inquiry-based on the flipped classroom, guided inquiry model integrated with STEM, and guided inquiry and task hierarchy analysis model in cooperative learning strategy, have also used different chemistry learning models.
Integrating the Audio-oral Method and Wordwall Gamification in Teaching Arabic Speaking and Grammar: A Case Study at The New College, Chennai Dr K M A AHAMED ZUBAIR
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 8 (2026): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i8.630

Abstract

This study investigates the integration of two pedagogical approaches-the Audio-Oral Method and Wordwall game-based learning-in teaching Arabic speaking skills and grammar at the Department of Arabic, The New College, Chennai. Employing a qualitative case study design, data were collected through classroom observations, interviews with instructors and students, and analysis of instructional materials. The study involved 30 undergraduate students divided into two proficiency-based groups. Findings reveal that the Audio-Oral Method effectively enhances pronunciation and dialogue practice through repetition and translation, while Wordwall serves as an engaging formative assessment tool that increases student motivation, vocabulary retention, and collaborative learning. However, challenges include the lack of an immersive Arabic language environment, local language interference, monotonous teaching practices, and unequal student participation in gamified activities. The study concludes that blended use of these methods can significantly improve Arabic language acquisition if supported by structured planning, diversified teaching strategies, and equitable classroom engagement techniques.
Evaluating In-Service Education: Teacher Effectiveness and Attitude Changes among Odisha Elementary Teachers Dash, Suchitra; Sahoo, Kulamani
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 8 (2026): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i8.632

Abstract

This study investigates the role of in-service education programmes in enhancing teacher effectiveness and shaping attitudes toward the teaching profession among elementary teachers in Odisha, India. Employing a quasi-experimental pre-test/post-test design with a control group, the study compared two groups of elementary teachers (trained group, n = 30, control group, n = 30). Data were collected using the Teacher Effectiveness Scale (TES) and the Attitude toward Profession Inventory (ATPI), both validated and reliable instruments. The results revealed that the trained group demonstrated significant improvements in teacher effectiveness (p<.05), particularly in planning, classroom management, and student assessment subdomains, with medium-to-large effect sizes (Cohen’s d = 0.45–0.70). Additionally, teacher attitudes toward the profession improved moderately, with gains in job satisfaction and professional commitment. The findings underscore the value of in-service education as a mechanism for enhancing instructional quality and strengthening professional identity. The study concludes by highlighting implications for policy, practice, and future research to ensure sustained quality in elementary education.
Artificial Intelligence in Research Translation in Higher Education: Applied Potentials for University Students Alalaq, Ahmed Shaker
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 8 (2026): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i8.637

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in research translation within higher education, shifting the paradigm from basic automation to intelligent systems capable of semantic understanding and contextual adaptation. This study explores the applied potentials of AI-driven tools, such as natural language processing (NLP) and deep learning, in facilitating research translation for university students. Unlike traditional machine translation, contemporary AI models understand cognitive structures and cultural nuances, generating outputs consistent with the target language's linguistic context. This paper analyzes how these technologies enhance cross-border academic communication and facilitate access to global knowledge by accelerating multilingual content production and reducing costs. Furthermore, it examines the collaborative human-machine review mechanism as a key factor in improving translation quality. The findings suggest that integrating AI into higher education research practices not only optimizes technical efficiency but also broadens the horizons for studying translation as a complex cognitive process. This study provides insights into how university students can leverage these advancements to bridge linguistic gaps in global academic discourse.
The Integration of Generative AI in Distance Education on Learning Effectiveness and Academic Integrity: A Systematic Review Maiti, Abhik
JOURNAL OF DIGITAL LEARNING AND DISTANCE EDUCATION Vol. 4 No. 8 (2026): Journal of Digital Learning and Distance Education (JDLDE)
Publisher : RADINKA JAYA UTAMA PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56778/jdlde.v4i8.660

Abstract

The integration of Artificial Intelligence (AI) and Big Data has fundamentally transformed distance learning into a highly personalized and data-driven experience. However, this transition poses major obstacles to maintaining academic integrity and rigorous standards in Open and Distance Learning (ODL) environments. The objective of this study is to formulate a strategic roadmap that aligns AI-driven learning optimization with academic rigor. This research employs a qualitative descriptive method through a systematic literature review (SLR) and thematic analysis. Data were synthesized from high-impact academic publications and case studies published between 2023 and 2025, concentrating on strategic implementations in global ODL institutions. The findings identify four critical thematic pillars: faculty training, ethical governance, individualized learning, and assessment redesign. The study reveals that a "human-centric AI" model is vital, where AI serves as an augmentative tool rather than a replacement for human judgment. Institutions must transition toward authentic, process-oriented assessments and robust ethical frameworks to ensure that technological efficiency does not compromise higher-order thinking skills. In practice, this research provides policymakers with a blueprint for creating inclusive and transparent educational ecosystems.

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