J-PE: Jurnal Pendidikan

Artificial Intelligence Readiness and Digital Transformation in Islamic Secondary Education

2026-06-20T12:59:27+00:00

Artificial Intelligence (AI) is increasingly recognized as a catalyst for educational innovation and digital transformation. Despite its growing adoption in educational settings, empirical evidence regarding AI readiness among teachers in Islamic secondary schools remains limited. This study investigates teachers’ readiness, utilization patterns, opportunities, and challenges associated with AI integration at MA Darunnajah Trenggalek, Indonesia. An explanatory sequential mixed-method design was employed, involving 42 teachers in a quantitative survey and 10 teachers in semi-structured interviews. Data were analyzed using descriptive statistics, multiple regression analysis, and thematic analysis. The findings indicate that teachers demonstrate a moderate-to-high level of AI readiness, with technological readiness achieving the highest score (M = 4.11), followed by pedagogical readiness (M = 3.89), ethical readiness (M = 3.74), and institutional readiness (M = 3.56). ChatGPT (92.8%), Canva AI (81.0%), and Gamma AI (66.7%) emerged as the most frequently utilized AI applications for lesson planning, content development, and assessment preparation. Digital literacy (β = 0.52), participation in AI-related training (β = 0.38), and leadership support (β = 0.29) significantly predicted AI readiness, collectively explaining 62.4% of the variance. Teachers perceived AI as a valuable instructional assistant capable of enhancing efficiency, creativity, and student engagement. Challenges were associated with limited professional development opportunities, ethical concerns regarding academic integrity, infrastructure constraints, and the absence of comprehensive institutional policies. Drawing on the Technology Acceptance Model, Artificial Intelligence in Education, and Digital Transformation Theory, this study proposes an AI Readiness Framework for Islamic Schools that integrates digital literacy, ethical awareness, leadership support, professional development, and institutional governance. The findings highlight that sustainable AI integration requires simultaneous investment in teacher competencies, ethical guidance, and organizational transformation to support innovation in Islamic secondary education.

Artificial Intelligence Assisted Learning in Primary Education: Examining Its Impact on Critical Literacy, Learning Engagement and 21st Century Skills Development

2026-06-21T01:30:36+00:00

Artificial Intelligence (AI) has emerged as a transformative force in education, offering innovative opportunities to enhance learning experiences, promote personalized instruction, and develop future-ready competencies. Despite the growing integration of AI technologies in educational settings, empirical evidence regarding their effectiveness in primary education, particularly in rural and semi-rural contexts, remains limited. This study investigates the impact of AI-assisted learning on critical literacy, learning engagement, and 21st-century skills among elementary school students in Trenggalek Regency, Indonesia. Employing a mixed-method quasi-experimental design, the study involved 128 fifth-grade students from four public elementary schools: SD Negeri 1 Surodakan, SD Negeri 2 Baruharjo, SD Negeri Sumbergayam, and SD Negeri 1 Kedung Lurah. The intervention was implemented over twelve weeks and integrated ChatGPT-assisted inquiry learning, AI-supported reading activities, adaptive quizzes, AI-generated project tasks, and automated feedback systems. Quantitative data were collected through critical literacy tests and student engagement questionnaires, while qualitative data were obtained through classroom observations and semi-structured interviews. Statistical analyses included descriptive statistics, independent-sample t-tests, and effect size calculations, whereas qualitative data were analyzed using thematic analysis. The results revealed that students exposed to AI-assisted learning achieved significantly higher critical literacy scores (M = 82.40) than students receiving conventional instruction (M = 71.60), with a large effect size (d = 1.76). Furthermore, AI-assisted learning significantly improved behavioral, emotional, and cognitive engagement, while also fostering digital literacy, critical thinking, creativity, communication, collaboration, and problem-solving skills. Qualitative findings indicated increased learning motivation, personalized support, and enhanced inquiry behaviors. These findings suggest that AI-assisted learning represents an effective pedagogical innovation capable of strengthening literacy development, student engagement, and future-oriented competencies in primary education, particularly within rural educational contexts undergoing digital transformation.

Artificial Intelligence Driven Educational Transformation: A Systematic Literature Review of Learning Innovation, Teacher Professional Development and Digital Transformation in K–12 Education (2020–2026)

2026-06-21T03:35:18+00:00

Artificial Intelligence (AI) has emerged as a transformative force in contemporary education, reshaping teaching, learning, assessment, and institutional management practices. The rapid advancement of generative AI technologies, intelligent tutoring systems, adaptive learning platforms, and learning analytics has accelerated digital transformation across educational settings, creating new opportunities for instructional innovation and educational improvement. Despite increasing adoption, evidence regarding the broader impact of AI on learning innovation, teacher professional development, and institutional transformation remains fragmented. This study aims to systematically synthesize current research on AI implementation in K–12 education through a Systematic Literature Review (SLR) guided by the PRISMA 2020 framework. Literature published between 2020 and 2026 was retrieved from Scopus, Web of Science, ScienceDirect, and SpringerLink databases using predefined inclusion and exclusion criteria. From 487 identified records, 42 studies met the eligibility requirements and were analyzed through thematic analysis. The findings reveal four dominant themes characterizing AI adoption in education: AI-supported personalized learning, AI-assisted assessment and feedback, teacher professional development and AI literacy, and AI-driven educational transformation. The review indicates that AI contributes significantly to individualized learning pathways, real-time feedback, learning analytics, instructional innovation, and data-informed decision-making. Teacher capacity emerged as the most influential factor affecting successful implementation, highlighting the importance of AI literacy, digital pedagogy, ethical awareness, and continuous professional development. The review also identifies major challenges, including teacher readiness, digital inequality, ethical concerns, data privacy, and policy gaps. Based on the synthesis, this study proposes the Artificial Intelligence Educational Transformation Framework (AI-ETF), which integrates governance, technological infrastructure, teacher capacity, and pedagogical innovation as key dimensions of sustainable AI implementation. The findings provide theoretical, practical, and policy implications for advancing responsible and effective AI integration in K–12 education.

Artificial Intelligence In Education For Improving Student Learning Engagement In Higher Education

2026-06-21T08:03:51+00:00

The development of artificial intelligence (AI) has created significant changes in many sectors, including higher education. AI technologies enable new approaches in teaching and learning through personalized instruction, adaptive feedback, and interactive digital environments. This study examines the contribution of artificial intelligence to improving student learning engagement in higher education. The research applies a qualitative literature review method by examining recent academic publications related to AI integration in educational settings. The analysis indicates that AI supports student engagement through adaptive learning systems, intelligent tutoring systems, automated feedback, and learning analytics. These technologies assist students in accessing learning materials that match their learning pace and provide immediate responses to learning activities. AI-based platforms also create opportunities for interactive and collaborative learning. Several challenges remain related to ethical considerations, data privacy, technological infrastructure, and digital literacy within institutions. The study shows that artificial intelligence can strengthen student learning engagement when supported by effective pedagogical strategies and institutional readiness.

Curriculum Innovation And Instructional Design For Future Oriented Education Systems

2026-06-21T08:09:06+00:00

Education systems are undergoing rapid transformation influenced by technological advancement, global connectivity, and shifting societal expectations. Traditional curriculum structures centered on knowledge transmission no longer fully address the competencies required in contemporary societies. This article examines the relationship between curriculum innovation and instructional design in shaping future oriented education systems. A qualitative literature based approach was employed through the analysis of scholarly articles, policy reports, and theoretical frameworks related to curriculum reform, digital pedagogy, and learner centered education. The review identifies several principles that characterize contemporary curriculum innovation, including competency based learning, interdisciplinary integration, learner agency, and technology enhanced learning environments. Instructional design functions as a mediating mechanism that translates curriculum vision into structured learning experiences through project based learning, digital learning environments, and authentic assessment practices. The study highlights that education systems capable of integrating innovative curriculum frameworks with strategic instructional design are better prepared to cultivate adaptable learners who can respond to complex and rapidly changing global contexts.