Aim/Purpose: Digital Well-Being Literacy is increasingly important in higher education, yet structured approaches that combine experiential, scenario-based, and role-playing learning remain limited. This study investigated the design and educational outcomes of an Experiential Scenario-Based Role-Playing Game (ES-RPG) framework addressing digital health, digital safety, digital literacy, and digital citizenship. Background: The framework integrates students’ identified learning needs with Experiential Learning Theory, Scenario-Based Learning, and role-playing activities. Authentic digital situations require learners to assume roles, make decisions, consider consequences, and reflect on their choices. Methodology: A three-phase design was used. Phase 1 identified Digital Well-Being Literacy needs among 598 undergraduates using the Priority Needs Index Modified. Phase 2 developed the ES-RPG framework and evaluated it with five experts. Phase 3 involved 70 undergraduates from two intact classes in a quasi-experimental pretest–posttest control-group design (n = 35 per group). Digital Well-Being Literacy was assessed using a validated 30-item test, and learning engagement was measured across behavioral, emotional, and cognitive dimensions. Contribution: The framework integrates needs assessment, experiential learning, scenario-based learning, and role-playing into a single instructional design. It translates identified learning priorities into authentic scenarios structured around role adoption, decision-making, and consequences, incorporating reflection throughout the experiential learning process. Findings: The highest-priority needs were mental and emotional well-being, healthy technology use, privacy management, digital stress awareness, and online responsibility. Expert evaluation indicated high suitability for both the framework (M = 4.56) and its learning activities (M = 4.52). After controlling for pretest scores, the experimental group had higher posttest Digital Well-Being Literacy than the control group, with a robust F(1, 67) = 13.93, p < .001, partial η² = .180, with an adjusted mean difference of 2.61 points (95% CI [1.21, 4.01]). The experimental group also reported higher learning engagement, with effect sizes ranging from d = 0.66 to 1.65. Recommendations for Practitioners: The ES-RPG framework provides a structured way to translate Digital Well-Being Literacy content into authentic activities involving decision-making, consequences, and reflection. Recommendation for Researchers: Further research should examine the contribution of individual framework components and replicate the intervention across multiple classes and institutional settings. Impact on Society: Digital Well-Being Literacy encompasses health, safety, critical use of digital information, and responsible participation in digital environments. Contextualized learning experiences may help higher education address these areas more systematically. Future Research: Longer interventions, delayed posttests, active comparison conditions, and behavioral measures of engagement are needed to examine the durability and generalizability of the findings.
Aim/Purpose: This systematic review synthesises 69 primary studies (2020–2025) to map how contemporary automatic question generation (AQG) research operationalises cognitive control, quality validation, and language inclusivity, and to identify where the field still needs to make progress. Background: While large language models (LLMs) have resolved the fluency challenge in automatic question generation (AQG), they have not resolved the harder pedagogical challenge. The field must now shift from “fluent question generation” to “pedagogically valid question generation,” creating assessments that strictly align with cognitive frameworks such as Bloom’s Taxonomy and possess verifiable docimological quality. Methodology: A systematic literature review (SLR) was conducted across Scopus, IEEE Xplore, and SpringerLink, filtering 775 initial records to 69 primary studies (2020–2025) using PRISMA-guided inclusion/exclusion and quality assessment criteria. Contribution: Unlike prior AQG reviews that address technical performance or single pedagogical dimensions in isolation, this review is the first to systematically integrate three concerns: (1) Bloom-aligned cognitive control, (2) pedagogical validation beyond automated metrics, and (3) language inclusivity. By synthesising these pillars, the study provides a taxonomy of control methods, establishes expert evaluation as the validation reference standard, highlights the low-resource language gap (e.g., Indonesian), and proposes a Pedagogical Alignment Framework. Findings: The review reveals a clear architectural divide between prompt-based flexibility and fine-tuning precision. The data show that 88.4% of the studies addressed cognitive control and that all 69 studies (100%) applied some form of quality validation beyond n-gram metrics. However, only 24.6% did so with full docimological rigour. In addition, 87.0% of the studies focused exclusively on English-language contexts. The review also establishes that automated metrics such as BLEU and ROUGE are inadequate for measuring pedagogical quality. Recommendations for Practitioners: To ensure docimological quality, practitioners must mandate subject matter expert (SME) validation. Furthermore, institutional deployment should strategically align the AI architecture with the learning goal: choosing parameter-efficient fine-tuning (PEFT) for strict cognitive compliance (e.g., high-stakes exams) or LLM prompting for flexible, exploratory tasks. Recommendation for Researchers: Researchers and developers are encouraged to focus on creating datasets for non-English and low-resource languages to address equity gaps in educational technology. Impact on Society: By addressing the cognitive and validation challenges in AQG, this review promotes the development of more reliable, pedagogically sound, and equitable AI-supported assessment tools for diverse learner populations. Future Research: Future research should focus on empirically validating the proposed Pedagogical Alignment Framework, developing automated assessors to relieve the validation bottleneck, and expanding AQG applications in culturally contextualised and low-resource languages.
Aim/Purpose: This study addresses the persistent challenge in pharmacy education where English for Specific Purposes (ESP) instruction often prioritizes general communicative competence while overlooking the discipline-specific vocabulary mastery and syntactic accuracy required for interpreting and producing pharmaceutical texts. The study aims to develop and validate the Absyak Model of English Teaching Materials, designed to strengthen pharmacy students’ ability to understand and produce precise pharmaceutical discourse. Background: Pharmaceutical education increasingly requires students to engage with complex drug monographs, clinical guidelines, patient information leaflets, and research abstracts written in English. However, many ESP instructional materials lack systematic integration of pharmaceutical terminology, morphological awareness, and syntactic structures characteristic of scientific discourse. As a result, students frequently encounter difficulties in accurately interpreting pharmacological information and producing structured pharmaceutical texts. This study addresses this gap by designing a discipline-aligned instructional model that integrates lexical development and syntactic scaffolding through authentic pharmaceutical materials. Methodology: This study employed a Design-Based Research approach involving iterative cycles of prototype development, evaluation, and refinement. The research was conducted at a private university in East Java, Indonesia, involving 84 undergraduate pharmacy students enrolled in an English for Pharmacy course. Data were collected through multiple sources to ensure methodological triangulation. These included expert validation of instructional materials, pre- and post-assessments measuring pharmaceutical vocabulary mastery and syntactic accuracy, document analysis of students’ written pharmaceutical texts, and focus group interviews with purposively selected participants representing different proficiency levels. Quantitative data were analyzed to examine improvements in lexical and syntactic performance, while qualitative data were analyzed thematically to explore students’ learning experiences and perceptions of the instructional model. Contribution: This study contributes to the field of ESP by proposing a structured instructional model that systematically integrates vocabulary mastery and syntactic development within authentic pharmaceutical discourse. The Absyak Model advances ESP pedagogy by demonstrating how corpus-informed lexical instruction, syntactic scaffolding, and genre-based writing tasks can be combined to support professional language competence in pharmacy education. Its distinctive contribution lies in formalizing these elements as a single, replicable design (the six-stage A-B-S-Y-A-K sequence) refined through Design-Based Research, offering instructional designers and ESP practitioners a transferable template for discipline-specific materials development and, more broadly, for technical and healthcare communication where lexical precision and syntactic accuracy carry professional and patient-safety consequences. Findings: The findings indicate that implementing the Absyak Model was associated with significant within-group gains in students’ mastery of pharmaceutical terminology and in their ability to apply syntactic structures appropriate to pharmaceutical texts. Students demonstrated improved competence in recognizing specialized vocabulary, interpreting contextual meanings, and applying morphological patterns commonly found in pharmacological discourse. In addition, learners showed enhanced accuracy in producing structured pharmaceutical summaries and explanations, particularly in the use of passive constructions, clause embedding, and nominalization. The iterative design process also revealed that contextual authenticity and disciplinary alignment of learning materials played a critical role in facilitating meaningful engagement with pharmaceutical texts. Nevertheless, variations in initial language proficiency influenced the pace of syntactic development, and some complex grammatical constructions required sustained instructional reinforcement. Because the study used a single-group pre-test/post-test design without a control condition, these results are presented as evidence of the development and feasibility of the materials and of immediate learning improvement, rather than as proof of comparative or sustained instructional effectiveness. Recommendations for Practitioners: Educators in pharmacy and other health-related programs are encouraged to incorporate corpus-informed vocabulary instruction, authentic pharmaceutical texts, and structured syntactic scaffolding into ESP curricula. Instructional materials should integrate repeated lexical exposure and guided writing tasks that gradually move from controlled practice toward independent production of pharmaceutical discourse. Recommendation for Researchers: Future research should explore the implementation of similar instructional models across different disciplinary contexts within health sciences education. Researchers are also encouraged to investigate the interaction between lexical development and syntactic competence in specialized academic writing using mixed-method approaches. Impact on Society: Strengthening pharmacy students’ ability to interpret and produce pharmaceutical texts accurately contributes to improved professional communication, safer dissemination of drug information, and enhanced collaboration within global healthcare environments. Future Research: Further studies should examine the long-term impact of the Absyak Model through longitudinal research designs and larger multi-institutional samples. Additional investigation may also focus on integrating digital corpus tools and automated linguistic analysis to support the sustained development of specialized academic language.
Aim/Purpose: This study investigates how integrating Internet of Things (IoT)-enabled Pocket Laboratories (PocketLabs) with the 5E instructional model can support active learning in undergraduate Control Systems education. Background: Traditional Control Systems laboratories face challenges related to cost, availability, and access to hands-on experimentation. Although PocketLabs and IoT technologies offer promising alternatives, their pedagogical integration within structured instructional frameworks remains underexplored. Methodology: An exploratory mixed-methods case study was conducted. A total of 55 undergraduate engineering students participated in the laboratory activities, and data from a perception survey were collected from 40 of these students. The quantitative survey data were analyzed using descriptive statistics, while the qualitative responses were examined through thematic analysis. Contribution: This study examines the pedagogical integration of IoT-enabled PocketLabs within a 5E instructional framework and presents a low-cost learning environment for in-person, remote, and hybrid Control Systems education. Findings: Students reported positive perceptions of the learning environment. One hundred percent of survey respondents either agreed or strongly agreed that it supported their understanding of control concepts. Qualitative analysis identified five themes related to learning support, engagement, teamwork, self-regulated learning, and opportunities for improvement. Recommendations for Practitioners: Engineering educators may consider combining portable experimental platforms, real-time visualization tools, and structured instructional frameworks to support active learning and increase access to hands-on laboratory experiences. Recommendation for Researchers: Future studies should employ larger, more diverse samples, comparative research designs, and direct assessments of learning outcomes to evaluate further the educational effects of IoT-enabled PocketLabs and 5E-based instructional approaches. Impact on Society: The proposed approach may expand access to practical engineering education by reducing infrastructure constraints and supporting flexible learning opportunities. Future Research: Future research should employ longitudinal and comparative designs and explore adaptive learning, intelligent feedback, and learning analytics within IoT-enabled laboratory environments.
Aim/Purpose: This study examines lecturers’ perceptions of Generative Artificial Intelligence (GenAI) in higher education and how these perceptions vary with demographic characteristics, namely gender, age and teaching experience. It further investigates how such perceptions relate to lecturers’ frequency of GenAI use and stage of adoption, identifying the opportunities and challenges lecturers associate with the integration of GenAI in educational practice. Background: The rapid emergence of GenAI has introduced new possibilities and challenges for higher education, yet empirical research examining lecturers’ perspectives, particularly within diverse contexts, remains limited. While existing studies have largely focused on students’ use of GenAI or technical adoption models, less attention has been given to lecturers’ perceptions, demographic influences, and the ethical and pedagogical implications of GenAI integration Methodology: A mixed-methods research design was employed. Quantitative data were collected through an online survey administered to 98 lecturers from different higher education institutions spanning a range of disciplines (55% male, 45% female; 44% aged 25-45, 30% aged 46-55, 26% aged 56+). Qualitative data were gathered through semi-structured interviews with a purposive subsample of ten lecturers. Quantitative analyses included independent-samples t-tests, one-way ANOVA, and Spearman rank-order correlations, while qualitative data were analyzed using Braun and Clarke’s six-phase thematic analysis. Contribution: Theoretically, the study extends technology-adoption research by integrating the Technology Acceptance Model with an interpretive technology-in-practice perspective, suggesting that lecturers’ perceptions of GenAI are socially situated and systematically shaped by gender, age, and teaching experience, and that these perceptions in turn are strongly associated with frequency of use and depth of adoption. Practically, the findings highlight the need for differentiated professional development, updated ethical guidelines, and redesigned assessment practices that foster critical AI literacy, supporting responsible and sustainable GenAI integration in higher education. Findings: Quantitative findings revealed significant demographic differences in lecturers’ perceptions. Female lecturers reported more positive perceptions than male lecturers on several pedagogical dimensions. A clear age-related gradient emerged, with lecturers aged 25-45 expressing the most favorable perceptions and those aged 56+ the least. Strong positive correlations were observed between perceptions and frequency of GenAI use, between perceptions and stage of adoption (rs = 0.67, p< 0.01) and between frequency of use and stage of adoption (rs= 0.74, p<0.01). Also, the thematic analysis of interview data identified three opportunity themes. These included: empowering lecturers in teaching and time management, enhancing pedagogical practices and student learning and improving accessibility to information and knowledge creation, alongside three challenging themes involving ethical and academic integrity concerns, technological limitations and dependency and threats to professional identity. Recommendations for Practitioners: Institutions should implement differentiated professional development and update ethical governance frameworks, with particular emphasis on redesigning assessment to foster critical GenAI literacy and authentic engagement. Recommendation for Researchers: Further studies should investigate how GenAI evolves from a technological tool into a sustained technology-in-practice within higher education systems. Impact on Society: The study underscores the importance of responsible GenAI integration to safeguard educational quality, equity, and human-centered academic values. Future Research: Future research should incorporate a larger, cross-cultural sample to explore how differing institutional, national, and policy environments moderate GenAI acceptance. Furthermore, while this investigation indicates an association between positive perceptions and the frequency of GenAI use, a step for subsequent studies is to empirically validate the longitudinal relationship between initial positive attitudes and the deep, sustained integration of GenAI into core curricula and assessment practices.
