Search Results (549)

As universities expand their e-learning systems, it becomes increasingly important to understand how the use of information and communication technologies (ICTs) changes the skills needed for effective formative assessment. This study uses the principles of human–computer interaction (HCI) to create a framework for examining how digital tools, interfaces, and modes of interaction influence the way teachers assess students in higher education. The research relies on the information provided by 115 Mohammed V University teachers, who filled out a competency-based assessment grid regarding online assessment practices. The results remain exploratory and context-dependent and do not make claims of statistical representativeness beyond the studied institutional context. The findings attest to the virtues of digital technology in improving methodological and techno-pedagogical skills, without excluding the existence of serious shortcomings in semio-ethical and evaluative skills. It is certainly useful to leverage feedback to correct imperfections in evaluation practices and make them more responsive to digital interfaces. It is becoming imperative to rethink professional skills as the regulatory halo of the online formative assessment system, in order to evaluate a more synergistic framework that can give better visibility to virtual classrooms. Full article

Examinations are central to higher education, yet students consistently describe them as detrimental to well-being. Drawing on self-determination theory (SDT), we conducted three studies to examine whether multiple-choice examinations could be redesigned to satisfy students’ basic psychological needs (BPNs) and support well-being. In Study 1 (n = 400), we developed and validated the Basic Psychological Need Satisfaction and Frustration Scale for Classroom Assessment (BPNSF-CA). Using bifactor exploratory structural equation modeling (bifactor ESEM), results supported a well-defined single global need fulfillment factor (G-factor) alongside six specific factors (autonomy support/frustration, competence support/frustration, relatedness support/frustration) as well as evidence of validity. In Study 2 (n = 387), we conducted a randomized experiment with three versions of a multiple-choice exam serving as the independent variable (flawed items, high-quality items, and high-quality + need-supportive features). Results showed that high-quality items improved performance, while only the addition of need-supportive features satisfied BPNs with differential patterns for the single G-factor and S-factors. In Study 3 (n = 101), we applied the intervention in a real classroom and tested the mediational role of BPN satisfaction. Results showed that redesigned exams (high-quality + need-supportive features) significantly enhanced perceptions of fairness and success via BPNs. We conclude with a discussion of all three studies, including implications and limitations. Full article

We present WM-Classroom v1.0, a pedagogical multi-species agent-based model (ABM) designed for educational purposes in predator–prey–harvest systems. The model embeds a predator, two prey breeds, and human harvesters on a homogeneous 50 × 50 grid with weekly time steps, implementing random movement, abstract energetics, prey consumption, reproduction, legal harvest with species-specific cut-offs and seasons, optional predator control, and a poaching switch. After basic technical checks (energetic calibration, prey composition, herbivore viability), we explore the consistency of the model under illustrative scenarios including no hunting, single-prey harvest, hunter-density and season-length gradients, predator removal, and poaching. In the no-hunting baseline (n = 100), mean end-of-run abundances were 22 deer, 159 boar, and 45 wolves, with limited extinction events. Deer-only harvest often drove deer to very low end-of-run counts (mean 1–16) with extinctions in 2–7/10 replicates across cut-offs, whereas boar-only harvest showed higher persistence (mean 11–74) and boar extinctions occurred only at the lowest cut-off (3/10). Increasing hunter numbers or season length depressed prey and could indirectly reduce wolves via prey depletion. Legal predator control reduced predators as designed, while poaching had little effect under the implemented rules. Because interaction and prey-choice rules are simplified for transparency, outcomes should be interpreted as conditional on model assumptions. WM-Classroom v1.0 provides a didactic sandbox for courses, professional training, and outreach, with extensions (habitat heterogeneity, age/sex structure, probabilistic diet/kill success, and calibration/validation) outlined for future versions. Full article

This study analyzes the ICT infrastructure in teaching practice centers from the perspective of students enrolled in early childhood and primary education degree programs at a Spanish university during the 2024–2025 academic year. A quantitative, cross-sectional design was employed. A questionnaire was distributed to all first- to fourth-year students via the university platform, with a sample of 556 participants. The data collection instrument consisted of an ad hoc adaptation and extension of the validated EdSocEval_V2 questionnaire, ensuring factorial validity. It was used to examine the availability of technological resources for communication and digital management, together with personal and contextual variables to support data classification. Results indicate high availability of basic digital resources, including projectors, Wi-Fi, interactive whiteboards, printers, alongside limited access to robotics, digital tablets, and classrooms of the future. High homogeneity was observed in communication and digital management resources, such as websites, virtual learning environments and corporate email. MANOVA analyses revealed that students perceive ICT infrastructure to be more integrated at higher levels of primary education, with no significant differences based on school ownership. Binary logistic regressions showed that school ownership predicts the availability of certain ICT resources, with private schools exhibiting lower network presence. Full article

Immersive technologies such as Desktop Virtual Reality (DVR), Immersive Rooms (IR), and fully immersive Virtual Reality (VR) are transforming K-12 education by enabling experiential, multisensory, and participatory learning. Yet their pedagogical impact depends not only on hardware fidelity but on the interplay between technological affordances, instructional design, and learner characteristics. Guided by the Cognitive Affective Model of Immersive Learning (CAMIL), this mixed-methods study examined how these factors jointly shape affordances, challenges, students perceived learning, and self-assessment in authentic classroom contexts. Data were collected from 31 teachers and 252 students across 21 schools using teacher interviews, classroom observations, and student questionnaires. Findings revealed that agency and presence emerged as central affordances but also as potential challenges, depending on lesson design and cognitive load. DVR consistently supported higher perceived learning and stronger links between engagement and self-assessment, while IR showed the weakest outcomes and VR displayed trade-offs between immersion and control. The study proposes a revised CAMIL framework that integrates social co-presence, learner characteristics, and perceived learning as essential components for understanding immersive learning in schools. These results highlight that effective immersion arises from pedagogical orchestration, not technological intensity alone. Full article

Higher education instructors may include interdisciplinary subjects in the classroom to encourage diverse yet balanced learning. Agriculture is a challenging subject of study that includes elements of art, engineering, and science. Although it is important to know if teachers in higher education incorporate agriculture in their lectures, it is more useful to comprehend the attitudes or opinions that are expressed. The purpose of this study was to determine whether higher education instructors mention agriculture in simulated discussion prompt generation and, if so, indicate the responses of positive, negative, and neutral sentiment towards agriculture. An electronic survey asked teaching faculty from multiple land-grant institutions to respond to a randomized prompt related to their declared area of interest. Qualitative methodologies included open response coding, and reliable and validated thematic coding served as the primary analysis. The study reports that 25 of the 59 responses included comments about agriculture and 72.0% of the responses were neutral. The rest painted agriculture in positive (8.0%) or negative (20.0%) interpretations. The results of the study reveal the challenges that teachers face in making interdisciplinary leaps, including agriculture in the classroom, without risking the spread of inaccurate information. Additional research should be conducted to understand the impacts of loaded language on students’ perceptions of agriculture using the results produced by the current study. Full article

This classroom-based case study examines how an AI-mediated Socratic dialogue, implemented through ChatGPT, can support students’ engagement and perceived learning in undergraduate thermodynamics. Conducted in a first-year engineering physics course at a private university in northern Mexico, the activity invited small student groups to interact with structured prompts designed to promote inquiry, collaboration, and reflective reasoning about the adiabatic process. Rather than functioning as a source of answers, ChatGPT was intentionally positioned as a mediating scaffold for Socratic questioning, prompting students to articulate, examine, and refine their reasoning. A mixed-methods approach was employed, combining a 10-item Likert-scale survey with construct-level statistical analysis of two focal dimensions: perception of learning and engagement, including an exploratory comparison by gender. Results indicated consistently high levels of perceived learning and engagement across the cohort, with average scores above 4.5 out of 5. At the construct level, no statistically significant gender differences were observed, although a single item revealed higher perceived learning among female students. Overall, the findings suggest that the educational value of ChatGPT in this context emerged from its integration within a Socratic, inquiry-oriented pedagogical design, rather than from the technology alone. These results contribute to ongoing discussions on the responsible and pedagogically grounded integration of generative AI in physics education and align with Sustainable Development Goal 4 (Quality Education). Full article

In the aftermath of the COVID-19 pandemic, instructors in higher education have reported a decline in foundational reading habits, particularly in STEM courses where dense, technical texts are common. This study examines a low-barrier instructional intervention that used generative AI (GenAI) to support pre-class preparation in two upper-division biology courses. Weekly AI-generated audio overviews—“podcasts”—were paired with timed, textbook-based online quizzes. These tools were not intended to replace reading, but to scaffold engagement, reduce preparation anxiety, and promote early familiarity with course content. We analyzed student engagement, perceptions, and performance using pre/post surveys, quiz scores, and exam outcomes. Students reported that the podcasts helped manage time constraints, improved their readiness for lecture, and increased their motivation to read. Those who consistently completed the quizzes performed significantly better on closed-book, in-class exams and earned higher final course grades. Our findings suggest that GenAI tools, when integrated intentionally, can reintroduce structured learning behaviors in post-pandemic classrooms. By meeting students where they are—without compromising cognitive rigor—audio-based scaffolds may offer inclusive, scalable strategies for improving academic performance and reengaging students with scientific content in an increasingly attention-fragmented educational landscape. Full article

(1) Background: Information and Communication Technology (ICT) integration in secondary education remains a critical challenge despite substantial investments in teacher training and infrastructure. This study investigated ICT certification levels, implementation patterns, and barriers among Greek secondary school teachers to understand the disconnect between policy aspirations and classroom realities. (2) Methods: A quantitative cross-sectional survey design was employed with 108 secondary teachers (61.1% female; mean age 47.3 years; 70.4% with >10 years’ experience) in the Prefecture of Ilia, Greece (response rate: 87.7%). Participants were permanent secondary school teachers employed in public schools during the 2021–2022 academic year; substitute teachers and private school staff were excluded. A three-section structured questionnaire was developed through literature review, expert validation (n = 3), and pilot testing (n = 10). Section A assessed demographics (5 items), Section B measured perceived barriers using a 7-item Likert scale, and Section C assessed implementation practices using a 10-item frequency scale (Cronbach’s α = 0.942). Data were analyzed using descriptive statistics, Mann–Whitney U tests, Kruskal–Wallis tests, and correlation analyses. (3) Results: While 74.1% of teachers held Level A certification, only 25.9% achieved Level B, with overall implementation remaining moderate (M = 2.92/5.00). Leadership support deficiency emerged as the primary barrier (76.9%), followed by inadequate technical support (74.1%). Younger teachers (24–35 years) demonstrated significantly higher ICT implementation than their older colleagues (56+ years), and teachers with less experience showed greater implementation frequency than veteran teachers—a finding that paradoxically challenges the “digital natives” assumption, given the barriers they face. Teachers preferred flexible Internet resources to formal educational software, indicating strategic adaptation to institutional constraints. Key limitations include convenience sampling, cross-sectional design, self-reported measures, and regional specificity. (4) Conclusions: The certification–implementation gap reveals that individual competencies cannot overcome unsupportive institutional environments. Effective ICT integration requires systemic transformation, encompassing leadership development, technical support, and structural reforms beyond traditional teacher training approaches. Full article

Teachers’ language assessment literacy (LAL) encompasses the knowledge and competencies required to design and implement assessment practices that support learning. Although prior research has documented general trends in LAL development, less is known about how individual teachers, particularly student teachers, interpret, appropriate, and negotiate formative assessment (FA) task design within the context of initial teacher education (ITE). Adopting an in-depth qualitative case study approach, this study examines how a single student teacher in a Chinese initial teacher education developed her cognition and classroom practice related to FA tasks across a teaching methodology course and a practicum. Drawing on thematic analysis of semi-structure interviews, lesson plans, classroom observations, stimulated recall interviews, and reflective journals, the study traces developmental changes and the contextual factors shaping the student teacher’s LAL in relation to FA tasks. Findings show that the sustained engagement with FA task design supported more sophisticated understandings of FA, including (1) an increased recognition of the pedagogical necessity of incorporating authentic FA tasks into lesson planning, (2) a growing aspiration to implement FA-oriented instruction that promotes higher-order thinking, (3) an enhanced awareness of the empowering role of FA tasks in fostering students’ self-regulated learning, and (4) a more nuanced understanding of the challenges inherent in implementing FA practices. Meanwhile, the case illustrates how pre-existing assessment conceptions, school culture norms, and limited targeted mentoring can constrain LAL development in relation to FA. By providing a fine-grained account of developmental processes, this study offers insights into how ITE can mediate student teachers’ engagement with FA task design. The findings have implications for teacher education programs in other similar educational contexts, particularly regarding the integration of FA task design into assessment courses and the provision of sustained, context-sensitive support during teaching practicum. Full article

The rapid adoption of generative artificial intelligence (AI) in higher education has intensified a pedagogical dilemma: while AI tools can increase immediate classroom engagement, they do not necessarily foster the self-regulated learning (SRL) capacities required for ethical and reflective professional practice, particularly in human-service fields. In this two-time-point, pre-post cohort-level (repeated cross-sectional) evaluation, we examined a six-week AI-integrated curriculum incorporating explicit SRL scaffolding among social work undergraduates at a Taiwanese university (pre-test N = 37; post-test N = 35). Because the surveys were administered anonymously and individual responses could not be linked across time, pre-post comparisons were conducted at the cohort level using independent samples. The participating students completed the AI-Enhanced Learning Attitude Scale (AILAS); this is a 30-item instrument grounded in the Technology Acceptance Model, Attitude Theory and SRL frameworks, assessing six dimensions of AI-related learning attitudes. Prior pilot evidence suggested an engagement regulation gap, characterized by relatively strong learning process engagement but weaker learning planning and learning habits. Accordingly, the curriculum incorporated weekly goal-setting activities, structured reflection tasks, peer accountability mechanisms, explicit instructor modeling of SRL strategies and simple progress tracking tools. The conducted psychometric analyses demonstrated excellent internal consistency for the total scale at the post-test stage (Cronbach’s α = 0.95). The independent-samples t-tests indicated that, at the post-test stage, the cohorts reported higher mean scores across most dimensions, with the largest cohort-level differences in Learning Habits (Cohen’s d = 0.75, p = 0.003) and Learning Process (Cohen’s d = 0.79, p = 0.002). After Bonferroni adjustment, improvements in the Learning Desire, Learning Habits and Learning Process dimensions and the Overall Attitude scores remained statistically robust. In contrast, the Learning Planning dimension demonstrated only marginal improvement (d = 0.46, p = 0.064), suggesting that higher-order planning skills may require longer or more sustained instructional support. No statistically significant gender differences were identified at the post-test stage. Taken together, the findings presented in this study offer preliminary, design-consistent evidence that SRL-oriented pedagogical scaffolding, rather than AI technology itself, may help narrow the engagement regulation gap, while the consolidation of autonomous planning capacities remains an ongoing instructional challenge. Full article

Learning to teach represents a complex process of professional and personal transformation that involves constructing new professional identities, negotiating prior experiences, and engaging with the epistemologies of teaching. For both first- and second-career entrants, ITE is not only a pathway into employment but a significant phase of identity (re)formation and learning within the higher education context. Understanding the needs and challenges that pre-service teachers articulate during this phase therefore provides critical insight into how teacher education functions as a space of learning and belonging. Despite this, empirical research addressing this issue remains limited. Accordingly, the present study sought to address this gap by exploring the differences in the needs and challenges of first- and second-career pre-service teachers. Analysis of qualitative data collected from 123 Australian first- and second-career pre-service teachers revealed that both groups identified a strong need for more authentic, practice-based learning and sustained mentorship to bridge the persistent gap between theory and classroom practice. Despite shared concerns around behaviour management, assessment, and wellbeing, second-career entrants emphasised challenges related to transferring prior professional identities, navigating school cultures, and balancing study with family and financial responsibilities. These findings highlight the importance of differentiated, career-responsive approaches in initial teacher education that recognise diverse life experiences as central to professional learning and teacher identity formation. Full article

Large Language Models (LLMs) are increasingly used in higher education, but their pedagogical role in fields like cybersecurity remains under-investigated. This research explores integrating LLMs into a university cybersecurity course using a designed pedagogical approach based on active learning, problem-based learning (PBL), and computational thinking (CT). Instead of viewing LLMs as definitive sources of knowledge, the framework sees them as cognitive tools that support reasoning, clarify ideas, and assist technical problem-solving while maintaining human judgment and verification. The study uses a qualitative, practice-based case study over three semesters. It features four activities focusing on understanding concepts, installing and configuring tools, automating procedures, and clarifying terminology, all incorporating LLM use in individual and group work. Data collection involved classroom observations, team reflections, and iterative improvements guided by action research. Results show that LLMs can provide valuable, customized support when students actively engage in refining, validating, and solving problems through iteration. LLMs are especially helpful for clarifying concepts and explaining procedures during moments of doubt or failure. Still, common issues like incomplete instructions, mismatched context, and occasional errors highlight the importance of verifying LLM outputs with trusted sources. Interestingly, these limitations often act as teaching opportunities, encouraging critical thinking crucial in cybersecurity. Ultimately, this study offers empirical evidence of human–AI collaboration in education, demonstrating how LLMs can enrich active learning. Full article

Higher education continues to encounter the challenge of redesigning writing pedagogy beyond the rapid adoption of emerging technologies. This challenge is particularly evident in English writing courses, which play a role in developing students’ writing and research skills in universities across the United Arab Emirates (UAE). While generative artificial intelligence (GenAI) tools offer practical affordances for writing instruction, their growing use has also raised concerns about academic integrity, authenticity, and critical engagement. Although early discourse has focused on the risks and potential of GenAI, there remains a clear dearth of frameworks to guide instructors in designing meaningful and engaging writing assignments. This paper introduces Ai-RACE, an adaptable pedagogical framework for designing purposeful and innovative writing tasks. Grounded in classroom-based insights, principles of writing pedagogy, constructivist and multimodal learning theories, Ai-RACE conceptualises assignment design around five interconnected components: AI integration, Relevance, Authenticity, the 4Cs, and Engagement. Employing a design-focused qualitative approach, the study uses instructional practices and student reflections to examine the implementation of Ai-RACE in writing contexts. Although situated within a specific institutional context, the study offers transferable guidelines for designing writing assignments across international higher education settings. By positioning Ai-RACE as a design heuristic, the study demonstrates its potential in supporting engagement, critical thinking, writing skills and ethical use of AI, and highlights the importance of rethinking writing pedagogy and the professional development in AI- influenced contexts. Full article

Although conventional lectures can provide a wide range of information to a large group of people, maintaining attention and ensuring knowledge transfer can be a challenge. Therefore, it is important to look for new, engaging, and effective approaches. This pilot feasibility study explores the effectiveness of virtual reality (VR) in increasing student engagement and knowledge transfer during lectures in the field of supply chain logistics and inventory selection systems. An educational VR game was developed through the systematic design of application logic, the creation of 3D assets, the construction of virtual scenes, and the implementation of gameplay. The application simulates three inventory picking methods: conventional selection, Pick by Light, and Pick by Vision systems. A total of 22 master’s students participated in the pilot study. They tested three different versions of the VR game, compared the time they needed to complete it, and participated in a guided discussion and questionnaire. The preliminary student reports indicated that students felt more engaged in the learning process and reported a perceived higher engagement with inventory picking systems compared to the traditional lecture format. On the other hand, participants mentioned concerns about nausea and the unavailability of VR headsets. The pilot results indicate that VR shows potential as an educational tool for teaching industrial logistics because it transforms the typical classroom environment into a more active and playful one, leading to a more natural understanding of the subject. Full article