This educational position paper proposes a competence-based reference framework for corrosion protection in structural engineering. It organizes corrosion-related learning objectives across the structural life cycle, links them to the six cognitive processes of the revised Bloom taxonomy, and distinguishes Bachelor, Master, professional practice, and research pathways. The contribution is educational rather than a new corrosion mechanism or experimentally validated teaching intervention. Drawing on the professional expertise of the working group, the memorandum offers illustrative mappings for curriculum review, module design, and continuing education. Its proposed competence allocations and illustrative teaching examples have not yet been evaluated through systematic curriculum analysis, learner assessment, or implementation studies. The framework is intended to support locally adapted curriculum development and subsequent empirical evaluation.
Assessment policies contribute to the discussion of broad and perpetual societal change. Since the previous assessment policies were in place, the Nova Scotia provincial government has made a series of moves to centralize authority in the province, creating renewed interest in revisiting current local assessment policy in the public education system. As this case study illustrates, the new classroom assessment policies can be understood as a call for change not only in assessment practices but also in the kinds of knowledge and skills that are valued in classrooms and the ideals for young people within the policies. This kind of analytic work can help educators understand how assessment policies and practices help to shape future kinds of citizens. The theoretical framework of identity constitution in poststructuralism directed the aims of this study. The analysis identifies an ideal subject position, the service worker, who is vested in future employment and is positioned between the tensions of liberation and subjugation. The analysis helps educators think through the effects of their assessment practices in their classrooms, especially in regard to issues concerning the constitution of young people’s identities within and beyond our schools in a time of centralization and economic priorities.
Language and literacy difficulties may be risk indicators for mental health problems and low academic performance among students in higher education. We examined the prevalence of these difficulties and their associations with mental health and academic performance in 52,139 students participating in the Students’ Health and Wellbeing Study (SHOT2022). Difficulties were assessed using the new Language and Literacy Scale (LLS), mental health using the Hopkins Symptom Checklist (HSCL-25), and academic performance by grade point average. We examined the preliminary psychometric properties of the LLS and associations with mental health and academic performance, adjusting for relevant background factors. Factor analyses supported a two-factor structure reflecting reading and writing difficulties, and language difficulties. Under the primary difficulty definition, about one in five students reported both types of difficulty. Students with language or literacy difficulties had more mental health problems and poorer academic performance than peers with no or low difficulties. In fully adjusted models, students with both types of difficulty had 2.51 to 3.25 times the risk of scoring above the HSCL-25 cut-off. The LLS showed preliminary psychometric support, but further validation against established and objective measures is needed.
While research increasingly aims to understand the lived experiences of neurodivergent language learners, the focus remains on individual neurodivergent groups despite high rates of co-occurrence. This study aims to understand, through a case study, the experiences of a multiply neurodivergent language learner. Interpretative phenomenological analysis revealed three themes: the ripple effect of late diagnosis, navigating the unique facets of neurodivergent functioning for learning, and experiences of learning in a range of conditions. Late diagnosis of neurodivergence led to the participant’s development of a conflicted sense of self and post-traumatic stress disorder, while eventually obtaining a diagnosis facilitated understanding of her unique profile to optimise language learning. Multiply neurodivergent cognitive, sensory, and social functioning presented unique strengths and challenges, while emotional functioning was more embedded and variable across her experiences. The perceived relationship between the participant’s various neurodivergent ways of functioning was also important to her own sense-making of her experiences. Finally, experiences of a range of learning conditions provided insights into the most pertinent factors in the learning environment. These themes reveal important considerations for supporting all neurodivergent language learners, diagnosed and undiagnosed. They also highlight the role of information in sense-making, cognitive load, foreign language anxiety, and learner autonomy.
The complexity of abstract concepts in Science, Technology, Engineering, and Mathematics (STEM) has encouraged educators to adopt innovative instructional approaches. Advances in artificial intelligence have accelerated the development of AI-powered immersive technologies (AIPIT) for STEM education, yet evidence of their effectiveness remains fragmented. This study addressed that gap through a multi-method investigation combining a systematic literature review and bibliometric analysis. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 17 eligible studies were selected after screening records from Scopus, ERIC, EBSCOhost, and Google Scholar. Extracted data were analysed using descriptive statistics, while bibliometric analysis examined the broader unscreened literature. Findings indicate that AIPIT research is an emerging field, with the United States and China leading publication output. Nine studies reported improved learner comprehension, eight identified increased engagement, and two demonstrated gains in academic achievement and timely feedback. Pedagogically, 42.2% of the studies adopted self-directed learning, while 29.4% employed inquiry-based learning, highlighting strong alignment between AI-driven immersive technologies and established STEM teaching approaches. The evidence suggests that AI-enhanced immersive learning environments improve students’ understanding, engagement, and academic performance. The study recommends expanding infrastructure and professional development to support effective AIPIT integration into STEM teaching, particularly for complex concepts.
