Multimodal Technologies and Interaction

The digital era represents a paradigm shift in gifted education, moving at an accelerating pace away from traditional models toward flexible and personalized technology-based pathways. This study investigates the impact of a model implemented via the FutureX platform in Saudi Arabia on the autonomy and self-regulated learning (SRL) of 63 gifted high school students. Using a quasi-experimental design, the study integrated quantitative measures (paired t-tests) with phenomenological analysis of interviews. The quantitative results showed statistically significant improvements (p < 0.001) in the dimensions of autonomy and self-regulated learning, with large Cohen’s d effect sizes for planning (d = 1.05), monitoring (d = 1.05), and cognitive control (d = 1.30). These gains were supported by a pedagogical design intentionally embedded within the platform to scaffold self-regulation. These findings were reinforced by qualitative results, with 88% of gifted students reporting that the platform provided appropriately challenging content and promoted self-learning and goal-setting behaviors.

Skilled operation of forestry harvesters is essential for ensuring safety, efficiency, and sustainability in logging practices. However, conventional training methods are often prohibitively expensive and limited by access to specialized equipment. This study delivers one of the first user-centered validations of a low-cost, VR HMD-based forestry harvester simulator, directly addressing access and scalability barriers in training. With 26 participants, we quantify cognitive load, usability, user experience, and simulator sickness using established instruments. An increase in cognitive load was seen from baseline tutorial to each training module (NASA-TLX: ; rm-ANOVA, p < 0.001). Usability was ‘Good’ (with a mean SUS score: 76.63), hedonic UX ranked in the top decile (UEQ-S), and simulator sickness was moderate (mean SSQ score: 28.91), while task success remained high across all modules. These results indicate early-stage feasibility and usability of a low-cost VR HMD harvester simulator for student-focused introductory instruction, and they provide actionable design guidance (e.g., managing extraneous load, comfort safeguards) advancing evidence-based VR HMD-based training in the forest engineering and harvesting domain. Our findings validate the potential of VR-HMD as a tool for forestry education capable of addressing training accessibility gaps and enhancing learner motivation through immersive experiential learning.

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.