As agricultural science and technology undergo a rapid, interdisciplinary transformation, the industry faces a critical challenge: an aging workforce that often maintains traditional perspectives. To meet the growing demands of a global society, it is essential to prepare a new generation of producers capable of navigating swift shifts in agricultural practices. Modern advancements increasingly rely on a fusion of agricultural, chemical, environmental, industrial, and mechanical engineering—disciplines deeply rooted in chemistry, physics, and mathematics. However, the interconnectivity of these fields is frequently under-communicated to aspiring students.

A cohort-based undergraduate research program provided students with rich STEM learning experiences on topics such as mass and energy balances, heat and mass transfer phenomena, environmental sciences, and engineering related to wastewater treatment and environmental remediation. The generation of scientific data and inquiry in groups have offered diverse perspectives and allowed students to work across scales. The problem-solving approach is strengthened by the participation and teamwork of interdisciplinary teams in more realistic research. By designing a dynamic, cohort-based summer undergraduate research experience, these programs provided enriching activities that occur along the active learning continuum.

This presentation examines the challenges and opportunities in developing a workforce capable of managing sustainable agricultural landscapes. We highlight three research and education programs funded by USDA-NIFA that provided high school, community college, and undergraduate students with hands-on opportunities to explore the diverse scientific and management disciplines shaping the industry. The focus will be on the learning experiences of STEM topics of the participants and the implications of educational activities on student learning experiences. The presentation will showcase student perceptions before and after participation, demonstrating how experiential learning can successfully shift viewpoints toward a more technological and sustainable future. These ongoing efforts provide vital insights into the educational frameworks necessary to complete the transition to a modern agricultural workforce.

Artificial Intelligence (AI) is transforming contemporary education by redefining the roles of teachers, learners, and institutions. This theoretical article conceptualizes the evolving position of AI in teaching and learning through the metaphor of “from chair to chairperson,” signifying AI’s progression from a peripheral instructional aid to a central orchestrator of pedagogical, assessment, and governance processes. Anchored in constructivist theory, connectivism, activity theory, and the diffusion of innovation framework, this paper critically examines how AI reshapes curriculum design, instructional strategies, learning personalization, and academic decision-making.

The article proposes conceptual models that illustrate AI’s role in mediating interactions among teachers, learners, content, and institutional systems. It highlights how AI-supported analytics and adaptive systems enhance teacher agency by enabling data-informed instructional planning, while simultaneously fostering learner autonomy through personalized, self-regulated learning pathways. In assessments, AI is positioned as a transformative force enabling formative, continuous, and competency-based evaluation practices beyond traditional examination-centric models.

At the institutional level, the study explores AI’s emerging leadership functions in academic governance, including resource optimization, quality assurance, and strategic planning. While recognizing AI’s potential to improve efficiency and equity, the paper critically addresses ethical and practical challenges such as algorithmic bias, data privacy, digital divides, and the need for professional readiness among educators and administrators.

The article concludes by outlining the future trajectories of AI as an academic “chairperson,” emphasizing hyper-personalized learning ecosystems, emotionally responsive AI systems, and semi-autonomous digital classrooms. It offers strategic recommendations for responsible AI integration, advocating for a human-centered, ethically grounded approach that positions educators as co-leaders rather than passive recipients of AI-driven change. This work contributes to theoretical discourse by reframing AI not merely as technology, but as an evolving leadership actor within educational ecosystems.

Introduction

In STEM education, learners often face intricate problem-solving challenges that require significant mental effort. A continual obstacle to achievement is restricted mathematical fluency, which burdens working memory with fundamental computations and limits involvement in advanced reasoning. This research presents the Max Math Challenge, a digital gamified tool aimed at automating basic arithmetic abilities and minimizing cognitive strain, allowing students to concentrate on higher-level STEM concepts.

Methodology

A 10-day pilot study was conducted using a single-group pre–post intervention design with 10 primary school students (all aged 8 years). Participants were recruited from a local educational setting based on their participation in the standard arithmetic curriculum. The intervention consisted of daily 20-minute sessions focusing on core arithmetic tasks (addition, subtraction, and multiplication). The technology-enhanced learning (TEL) environment integrated adjustable difficulty algorithms, real-time feedback, and gamification components such as progress badges and level-unlocking. Performance was assessed by comparing baseline metrics to post-intervention results regarding Response Latency and Accuracy Rates.

Results

Initial results show significant improvements in computational fluency. Average response latency was reduced by 60.7%, while accuracy improved by 22% during the intervention period. Qualitative observations also indicate a decrease in math anxiety, with learners expressing increased confidence and willingness to participate in engineering and technology-related tasks. The emergence of automaticity seems to liberate cognitive resources, facilitating a more fluid transition into intricate STEM problem-solving.

Conclusion

The Max Math Challenge emphasizes that digital transformation in education goes beyond merely digitizing material; it requires enhancing the cognitive framework of learning. By boosting basic fluency among young learners through a research-backed and flexible TEL method, the application promotes fair involvement in STEM pathways from an early age. These results highlight the promise of gamified micro-practice tools in boosting learner resilience and equipping students for the mental challenges of contemporary STEM education.

Many learners are unable to access higher education (HE) annually due to not meeting the minimum entry requirements for mainstream programmes. This persistent challenge reflects deep inequities in the education system and calls for transformative approaches that move beyond academic remediation. The Extended Curriculum Programme (ECP) has emerged as a strategic intervention aimed at widening participation, promoting inclusivity, and fostering academic success among students, particularly those from historically disadvantaged backgrounds. This paper explores how inclusive teaching practices, curriculum responsiveness, and student-centred pedagogies within the ECP help level the academic playing field in South African HE while nurturing social and economic resilience among graduates. Drawing on theoretical insights and reflective experience as an educator, it highlights the transformative role of ECPs in providing access and sustained academic support to underprepared students who might otherwise be excluded from mainstream academic pathways. Through contextualised pedagogy, mentorship, and holistic support systems that extend beyond academic assistance to include social integration and confidence building, ECPs cultivate graduates who are academically capable, socially conscious, and economically resilient. The paper underscores the importance of embedding Education for Sustainable Development (ESD) principles within ECP curricula and advocates for innovative pedagogical approaches, such as Universal Design for Learning (UDL) and participatory methods, to foster sustainability competencies and enhance engagement. Ultimately, it argues that true sustainability in South African HE must prioritise human development and inclusive teaching practices that transform structural inequalities into opportunities for collective growth and empowerment. Strengthening inclusivity within ECPs can bridge systemic gaps, advance institutional transformation, and support the broader goals of equitable and sustainable higher education.

Introduction

Much of the cognitive work involved in writing, including planning, pausing, revising, and restructuring ideas, often leaves little visible evidence once a document is completed. At the same time, the rapid emergence of generative AI has created new challenges for writing instruction, with many institutions turning to automated AI detection systems despite concerns about their reliability and fairness. This study introduces an approach in which generative AI supports student reflection on the writing process, helping students examine and explain their planning strategies, revision decisions, and development of ideas.

Methods

Writing process reports derived from digital revision histories capture indicators such as drafting timelines, revision patterns, editing bursts, and pauses in composing activity. These indicators can be visualized to provide an empirical representation of how a document develops over time. Building on this representation, the present study developed a structured set of reflection prompts to guide students in interpreting their writing process reports. In the freely accessible online writing process visualization platform Process Feedback (www.processfeedback.org), we implemented a “Copy for AI” feature that allows students or teachers to copy the writing process data and visualizations along with a structured reflection prompt. This copied content can then be pasted into any generative AI tool for interaction and reflective conversations.

Results

The proposed approach and implementation in the Process Feedback platform demonstrate the technical feasibility of systematically transforming writing process indicators into actionable reflection prompts that guide students in examining their composing activity. Preliminary deployment shows how generative AI can effectively translate complex process data into personalized conversations focused on reflection and learning.

Conclusions

By positioning AI as a reflection partner, this approach promotes metacognition and transparency. It provides a scalable, open-access alternative to AI detection, helping students engage more deeply with writing as a process of learning.

This study examined functional approaches for applying work-based learning to Physics education in senior secondary schools in Kano State. A descriptive survey research design was adopted, and data were collected using a structured questionnaire administered to 400 secondary school students across SS I–SS III. Data were analyzed using frequency counts and percentages. The findings revealed that current Physics teaching practices are moderately engaging, with 75% of students indicating that Physics lessons are interesting, while 65% perceived Physics as more difficult than other science subjects. Although 70% reported that their teachers connect lessons to real-life applications, only 60% indicated regular exposure to practical or vocationally related experiments, and self-study habits remained low, with only 60% engaging in independent study. Results further showed that work-based learning significantly enhances students’ understanding, motivation, and interest in Physics. A total of 72.5% of respondents agreed that work-based learning helps them understand real-world applications of Physics, 72.5% reported increased interest through school workshops and projects, 65% acknowledged that industrial visits and internships improved their understanding, and 75% affirmed that hands-on experience improved their motivation to study Physics. Additionally, 65% confirmed that their schools organize career-related programs linked to Physics. The study also identified key functional approaches for effective integration of work-based learning into Physics education. A large majority supported school–industry collaboration (75%), inclusion of industrial field trips (70%), use of project-based learning (75%), integration of simulations and technological tools (70%), and provision of additional teacher training on work-based learning methods (72.5%). The study concludes that although traditional teaching methods still dominate Physics instruction, the adoption of structured work-based learning strategies can significantly improve students’ understanding, motivation, and career relevance knowledge of the subject. It is therefore recommended that stakeholders prioritize functional approaches like industry collaboration, practical-based instruction, and continuous teacher training.

This study aims to map the intellectual landscape of research on multiple representations in physics education by integrating a systematic literature review and bibliometric analysis. This study analyzed Scopus-indexed journal articles that explicitly discussed multiple representations in physics learning, using selection procedures in accordance with the PRISMA 2020 guidelines. Bibliometric analysis was conducted using the Biblioshiny package and VOSviewer to identify publication trends, key actors, patterns of scientific collaboration, and the thematic structure of the research. The results show that publication output has grown significantly since 2016 and entered a phase of rapid expansion, though conceptual maturity has not yet been reached. Indonesia led in publication volume (86 articles), while the Netherlands and Germany demonstrated the highest citation impact (MeanTC: 125.5 and 32.8, respectively), revealing a notable gap between productivity and scientific influence across countries. At the institutional and author levels, contributions remain concentrated within specific groups, reflecting a fragmented research community. Keyword co-occurrence analysis identified multiple representations as the central conceptual node, strongly linked to conceptual understanding, students, physics education, and educational computing, with a discernible thematic shift from classical pedagogical studies toward digital learning ecosystems integrating augmented reality, simulation-based learning, and high-order thinking skills. Thematic evolution analysis revealed three research phases: a conceptual phase (2005–2017), an integrative phase (2018–2020), and an innovation-oriented phase (2021–2025) emphasizing research and development and representational fluency. Future research directions include AI-based adaptive learning, AR/VR-integrated multirepresentational environments, and the development of R&D-based MR learning ecosystems aligned with 21st-century competencies. These findings offer a comprehensive and data-driven overview of the global dynamics of multiple representations research and serve as a strategic conceptual basis for formulating a more targeted future research agenda in physics education.

Introduction: In the African setting, inclusive education is now a priority to enable access and participation on an equal basis for all learners, including those with autism spectrum disorder (ASD). The successful inclusion of learners with autism within mainstream classes across Sub-Saharan Africa is still highly contentious, although policies support this movement as part of global initiatives, namely the Sustainable Development Goals and the Salamanca Statement. Many teachers are unaware of ASD.

Methods: A systematic review was conducted to identify evidence-based approaches for supporting pupils with autism in typical Sub-Saharan African classrooms. PubMed, ERIC, Scopus and Web of Science were selected as the databases to search the literature from 2010 to 2025. And lastly, empirical studies on teacher-facilitated interventions and instructional or support mechanisms for students with ASD in inclusive settings within Africa were an essential part of the inclusion criteria. Studies conducted outside Africa or with results that do not pertain to classrooms were excluded. This study adhered to the PRISMA guidelines.

Findings: Research studies indicate that many teachers in Africa lack understanding of ASD, and their training for behavioural support does not teach any strategies for supporting these learners in learning. In addition, many barriers impede inclusion initiatives, such as overcrowded classrooms. Some low-cost ways to support students with ASD are the following strategies: visual supports, creating structured routines for students' daily activities, creating an individualised instructional plan, and using peers to support other students who have ASD, along with providing positive behaviour support. The academic, social and emotional inclusion of students with ASD depends on the collaborative efforts of parents, teachers and the community.

Conclusion: This systematic review identifies substantial teacher preparation, expertise, and resource gaps when working with students with autism and suggests evidence-based strategies to implement.

The integration of digital technologies in the sphere of higher education has increasingly been associated with enhanced learning outcomes and access to academic resources. This paper aims to explore the relationship between the utilization of educational software tools and academic performance among university students in Uzbekistan. The structured questionnaire was used to obtain data on students' approaches to learning, their levels of engagement in digital technologies, and their perceptions of academic performance in different fields. The results show that students who use software tools to learn tend to have deeper levels of understanding of their academic materials, efficiency in their coursework, and independence in their learning processes compared to their counterparts. This is also supported by statistical data showing a significant positive correlation between the use of technology-rich learning environments and academic performance. Additionally, the utilization of digital technologies is also associated with the development of cognitive skills, technical skills, and problem-solving skills that are increasingly essential in professional career readiness in the modern workforce. This underscores the critical importance of integrating digital competencies and software-based learning strategies in the curriculum in the sphere of higher education to promote innovative learning environments that are fully congruent with the demands of the knowledge economy.

Educational Escape Rooms (EERs) have emerged as an innovative game-based learning strategy within Mathematics Didactics courses in undergraduate and master’s degrees in Education. This systematic review synthesizes empirical evidence on the pedagogical impact, methodological characteristics, and research quality of studies examining EER implementations in higher education contexts between 2016 and 2026. A total of 21 peer-reviewed studies were analyzed following structured selection criteria. The review focused on three core dimensions: (1) motivational and affective outcomes, (2) development of mathematical reasoning and didactic competencies, and (3) methodological rigor and research design quality.

Findings consistently indicate that EERs significantly enhance student motivation, engagement, and satisfaction in teacher education programs related to mathematics. Positive emotional activation, increased immersion, and perceived enjoyment were recurrently reported across quantitative and mixed-methods studies. From a cognitive perspective, EERs demonstrated potential to strengthen logical-mathematical reasoning, problem-solving skills, collaborative learning, and the ability to design innovative teaching strategies for mathematics classrooms. In both undergraduate and postgraduate teacher education, escape rooms were associated with improved conceptual understanding and greater awareness of active methodologies applicable to school contexts.

However, methodological analysis revealed variability in research design quality. While most studies employed quasi-experimental or descriptive approaches, fewer incorporated control groups or longitudinal measurements. Risk of bias and limited sample sizes were common limitations. Despite this, overall methodological quality ranged from moderate to high when assessed through standardized appraisal frameworks.

The evidence suggests that Educational Escape Rooms constitute a promising active-learning methodology in Mathematics Didactics within teacher education programs. Nevertheless, further rigorous experimental research is needed to consolidate causal evidence and determine long-term impacts on professional teaching competence.