Journal of Hypermedia & Technology-Enhanced Learning

Problem-Based Jobsheets for PLC Practicum with a Pick and Place Trainer Kit and FPWIN Pro 7

Elfitra Rahma Fionandes — 2026-06-30

Vocational secondary schools (SMK) tasked with producing industry-ready graduates frequently lack structured, validated instructional materials for complex automation equipment. This study reports the design, development, and validation of a Problem-Based Learning (PBL) Jobsheet Module for the Panasonic PLC-based Pick and Place Trainer Kit, programmed through FPWIN Pro 7. Following a Research and Development (R&D) approach using the Four-D (4D) model, limited to the Develop phase, five progressive jobsheets were constructed and evaluated for validity by subject-matter and instructional media experts, and for practicality by one vocational teacher and ten Grade XI Industrial Automation students at SMK Pembangunan Teknologi Robotik UNP, Padang, Indonesia. Expert validation yielded a composite score of 91.67% (Very Valid), comprising 89.58% for content validity and 93.75% for media validity. Practicality testing returned an overall mean of 93.6% (Very Practical), with teacher and student ratings of 93.8% and 93.5%, respectively. Qualitative feedback indicated that the PBL problem scenarios reduced cognitive load, enhanced procedural independence, and improved learners' confidence in troubleshooting electro-pneumatic systems. These findings confirm that integrating authentic industrial problem scenarios into structured jobsheet modules produces highly valid and practical teaching materials aligned with Industry 4.0 competency demands, while also providing a replicable design framework for vocational automation educators.

Digital Educational Technologies in Gifted STEAM Education: A Qualitative Case Study of Teachers’ Perceptions and Practices in a Mixed-Ability Learning Context

Emmanouil D. Milakis — 2026-06-30

This qualitative case study examines how teachers perceive and implement digital educational technologies in Gifted STEAM Education within a mixed-ability learning context involving gifted and non-gifted students. The study was situated in an annual professional development program on Gifted STEAM Education and involved six purposively selected teachers with experience in STEM/STEAM Education and/or Gifted Education. Data were collected through semi-structured interviews, mini focus groups, overt observation, field notes, and textual documents, and were analyzed using thematic analysis. The findings show that teachers viewed digital technologies not as neutral technical resources, but as pedagogical mediators that could shape inquiry, differentiation, participation, and creative production. Meaningful technology integration required explicit digital-skill goals, structured guidance, and formative monitoring. Digital tools supported Gifted STEAM learning when they were connected to interdisciplinary inquiry, design activities, multimedia production, creative expression, and differentiated forms of participation. Equity was understood as a multidimensional concern involving device access, meaningful participation, differentiated support, role distribution, ethical use, data protection, and equivalent non-digital pathways. Implementation, however, was limited by inadequate infrastructure, outdated equipment, software incompatibility, unstable internet access, time pressure, unequal access, and institutional ambiguity. The study contributes to the literature by clarifying how digital technologies can support inclusive differentiation, interdisciplinary integration, and ethical digital practice in Gifted STEAM Education. The findings should be interpreted in light of the small sample, the specific professional development context, the non-formal educational setting, and the limited transferability of a single qualitative case study.

Mapping Three and a Half Decades of AI and Education Literature: Trends, Gaps, and Future Directions

Constance de Saint Laurent — 2026-06-30

Research on artificial intelligence (AI) in education has expanded at unprecedented speed, yet its development remains fragmented, hype-driven, and unevenly distributed across disciplines and regions. This paper presents one of the most comprehensive mappings to date, analysing 16,564 publications (1990–2025) identified through Web of Science and refined to 4,626 core contributions using a hybrid method that combined computational topic modelling, AI-assisted filtering, and human validation. To complement this macro-level mapping, we conducted a qualitative overview of the most cited papers in each major research topic, providing interpretive depth on how influential works have shaped debates on adoption, engagement, personalisation, chatbots, evaluation, risks, monitoring, reviews, and teaching AI. The findings reveal exponential growth since 2020, with major surges during the COVID-19 pandemic and following the release of ChatGPT, but also enduring fragmentation, declining evaluation studies, and a saturation of attitudinal surveys. Promising areas such as personalisation, teaching AI, and engagement have lost visibility despite their long-term importance, while risks and ethical issues remain underexplored and poorly connected to technical research. Citation patterns further show systemic imbalances, with education papers disproportionately cited and engineering outputs under-recognised. We conclude with recommendations to strengthen interdisciplinarity, address neglected areas, include historical perspectives, and address systemic challenges in order to foster a more cumulative, integrative, and critical field.