AHFE Open AccessTraining, Education, and Learning Sciences
Editors: Salman Nazir
Topics: Training, Education, and Learning Sciences
ISBN: 979-8-950676-07-9
DOI: 10.54941/ahfe1007250
Table of Contents
Enhancing Material Literacy Through Hands-On Workshops in Educational Material Libraries
Materials are foundational to every tangible design project. However, traditional product and industrial design education programs remain largely theory- or software-based, which can limit the development of students’ practical, experiential skills in materials. Although hundreds of material libraries worldwide support education, many still function primarily as consultative archives rather than as active learning environments. Since their emergence in the late 1990s, material libraries have provided organised collections of material samples for designers, professionals, and educators, yet their educational potential is often underutilised. This study examines how material libraries can evolve from static repositories into dynamic commons that support hands-on workshops and knowledge exchange. This paper explores how integrating design workshops and material engagement within an educational materials library can enhance material literacy and experiential learning in design education. By activating the materials library as a space where theoretical knowledge intersects with practical experience, this research proposes a replicable model for enriching design pedagogy.
Narmin Gasimova, Sofia Soledad Duarte Poblete, Silvia Ferraris, Valentina Rognoli
Open Access
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Conference Proceedings
Instructors’ Perspectives on AI in Maritime Simulator Training: A Qualitative Study
Simulator-based training has long been a cornerstone of maritime education and training, where human instructors play a central role in designing and implementing effective training strategies. However, as technological innovation advances, artificial intelligence (AI) is becoming increasingly embedded across maritime operations and learning environments, with emerging applications ranging from collision avoidance, forecasting and predictive analytics to adaptive learning. These developments raise important questions about the role of human instructors in simulator-based training with AI. In this context, this study aims to explore maritime instructors’ perceptions of AI integration in simulator-based training and develops a conceptual framework centred on perceived usefulness, psychological safety, and social embeddedness. Accordingly, we aim to answer the following research questions: (1) How do instructors perceive their professional identity with AI-integrated simulator training? (2) What boundaries do instructors envision regarding AI uses in simulator-based training? and (3) What factors facilitate the use of AI into simulator-based training in future? To address these research questions, we conducted qualitative semi-structured interviews with twelve experts in simulator-based training. Data was analysed using thematic analysis approach, grounded in instructors’ anticipatory perceptions of the use of AI in their professional training practice. The data analysis reveals that AI has potential to alleviate instructor’s workload in designing, implementing and assessing instructional practice. However, our informants consistently position AI as a form of pedagogical scaffolding rather than a replacement for human expertise. Human instructors perceived their role as indispensable, especially in highly ambiguous training contexts. Particularly, their roles remain central to effective pedagogy when it comes to observation, stimulating reflective thinking and developing interpersonal relationship with learners. Our analysis also suggests that the future of simulator training with AI appears to be shaped by a triadic interplay of perceived usefulness, psychological safety and social embeddedness. Whether AI should be integrated into simulator-based training remains contingent upon the maturity of the technology and the demonstrable value it can provide. Given the opacity of AI systems, often referred to as “black boxes”, it is imperative to foreground ethical awareness about the potential and limitations of AI use. Additionally, informants believe that as AI becomes increasingly integrated into everyday professional life. Hence, it is important to develop informed strategies that maximise its pedagogical utility while safeguarding the human factors in professional training practice.
Thi Diem My Ta, Salman Nazir, Per Haavardtun, Leif Inge Magnussen
Open Access
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Conference Proceedings
Methodological Validation of Environmental Embedding and Cognitive Absorption for AR Instructional Communication in Chinese Motif Design Learning
Augmented reality is used to disseminate cultural heritage. However, its application in teaching traditional Chinese motif remains underexplored within communication and media studies. There is limited evidence regarding augmented reality’s influence on learning through cognitive absorption in higher education art and design. Therefore, this study employs an explanatory sequential mixed methods design, integrating situated cognition theory, cognitive absorption theory, and student engagement theory for methodological validation. The quantitative phase included 34 art and design students from universities in Nanchang, Jiangxi Province, China, who had nearly six months of experience learning traditional motif with augmented reality assistance. An adapted Chinese version of the scale was used to measure the relationship between environmental embedding, the five dimensions of cognitive absorption (enjoyment, curiosity, control, temporal dissociation, and focused immersion), and learning experience, with reliability, validity, and correlation analyses conducted. In the qualitative phase, four experts assessed the interview outline’s validity, followed by pre-interviews with four samples to optimize questions. Results showed good internal consistency and supported subsequent formal research. Related results showed a significant positive correlation between environmental embedding and curiosity and learning experience, with focused immersion showing the highest correlation, while the correlation between sense of control and learning experience was weaker. Interviews suggested augmented reality’s “seeable but difficult to control” experience gap may lower control scores. These findings preliminarily support the study’s proposed communication path, indicating control may fail under low-interaction augmented reality. This study proposes revising formal research to eliminate low-interaction augmented reality stimuli, using manipulable interactive materials to examine the control dimensions mediating role.
Yuwen Zou, Wardatul Hayat Adnan, Nurul Hijja Mazlan, Chang Liu
Open Access
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Conference Proceedings
AI Empowers Design Education: Integrated Model of Prompt Teaching and Originality Cultivation in University Design Majors
With the in-depth penetration of artificial intelligence technology in the field of design, AI design tools such as Midjourney have become important auxiliary creative means for students majoring in design in universities. However, there is a significant disconnect in the application of AI in current university design teaching: students generally face pain points such as inaccurate prompt design, lack of systematic guidance in the creative process, and insufficient homogenization and originality of works. The traditional teaching model is difficult to meet the demand for cultivating design talents in the AI era. Against this background, this paper focuses on the teaching reform of AI application in university design majors, aiming to solve the practical problems and lack of originality in AI-assisted design, and explores a new integrated teaching model of prompt teaching and originality cultivation.The theoretical significance of this study lies in constructing a teaching framework for the in-depth integration of design education and AI technology under the background of AI empowerment, enriching the interdisciplinary research achievements in the field of design education, and providing theoretical reference for the teaching reform of design majors in the AI era. The research results can provide direct reference for the AI teaching practice of university design majors, help design education adapt to the development trend of the industry, and improve the quality of talent training.
Weiling Deng, Yulin Zhao, Yanhao Cai, Jinghuan Xu, Jinpeng Chen
Open Access
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Interdisciplinary Pathways and Pedagogical Models Integrating Artificial Intelligence and Design
With the rapid advancement of artificial intelligence, design education paradigms are in urgent need of a systematic transformation. This study employs a multi-case research methodology to conduct an in-depth analysis of the practical experiences of six world-leading design institutions at the intersection of AI and design. Based on a comparative analysis, this paper constructs a pedagogical framework consisting of five dimensions: curriculum restructuring, interdisciplinary synergy, optimization of teaching and learning modes, the definition of AI ethics and creative boundaries, and infrastructure support. This framework not only identifies innovative paradigms in contemporary design education but also provides actionable strategic pathways for curriculum reform and resource allocation in higher education. Ultimately, this research aims to facilitate the cultivation of design talent that meets the evolving demands of the intelligent era.
Dongfang Yang, Xuejun Tang, Bingjing Chen, Zhaoqun Niu
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Shaping a pro-development orientation & proactivity as intentions corresponding to the process of self-education in a career in the globalizing world
The multidimensionality and complexity of contemporary social configurations contribute to difficulties in capturing and clearly defining the factors determining changes in the social system and in theoretically describing the social dimension of human existence. This context also raises questions about the place of (self-)education in relation to careers, as a space for career planning, development, and monitoring. A new perspective on postmodern social structure is emerging, fostering a narrative focus on the nature of the social world - the interdependence between the new quality of global sociocultural relations and the individual dispositions of individuals.It seems important to emphasize that one of the particularly important factors that influences the condition of modern man is broadly understood (self-)education, the aim of which is to shape a proactive and pro-development orientation.Adaptation to an amorphous environment occurs through the practice of learning a new context in the world of "boundaryless careers" in which one participates, plans, and develops one's career, contributing to its transformation and inducing desired changes. The degree of influence on the current situation (including the career situation) or the social environment (including the organizational environment) is individualized and depends on the subject's propensity to take active steps that indirectly trigger these changes in the environment. Contemporary studies on the quality of the career domain should consider its broadly understood pro-development and proactive dimension, which essentially refers to the level of what we broadly call lifelong (self-)education.
Agnieszka Cybal-Michalska
Open Access
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From Tutor to Co-Instructor: AI–Human Instructor Roles in Maritime Simulator Training and Assessment
Artificial intelligence (AI) has become increasingly prevalent across diverse domains, including maritime operations, where its potential to enhance training and assessment is gradually recognised. AI-enabled adaptive learning platforms can tailor simulator training to learners’ performance, delivering dynamic feedback loops that enhance continuous improvement. Such platforms enhance engagement, knowledge retention, and competency development benefits particularly relevant to complex maritime tasks including cargo handling, route optimisation, and machinery maintenance. While previous research demonstrates AI’s potential for adaptive learning and assessment, the pedagogical role of AI relative to human instructors remains unclear in maritime education and training. We conducted twelve semi-structured interviews with experienced practitioners in simulator-based training and assessment in the maritime domain. The interviews were transcribed and thematically analysed. The findings of our research demonstrated (1) instructors’ perceptions of possibilities and concerns of integrating AI into simulator-based maritime, (2) the relational dynamics between AI and human instructors and (3) types of AI-integrated simulator training. We highlight the AI affordances across simulator-based training continuum, in the preparatory, scenario and debriefing, post-simulation phases. Additionally, we propose three types of AI-integrated simulator training: AI supported, AI augmented and AI instructed. Although AI has potential to alleviate instructor’s workload in designing, implementing and assessing instructional practice, AI remains scaffolding rather than a replacement of human instructors in facilitating professional training.
Thi Diem My Ta, Salman Nazir, Per Haavardtun, Leif Inge Magnussen
Open Access
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Internal-external parameters’ balance during cognitive performance as measured individual adaptive “norm” for learning/training
The paper aims to analysis of relationship between internal and external factors influencing subjects’ cognitive test performance and development of the technique to build possible adaptive individual “norm” to the cognitive test performance. The study confirms our hypothesis that human cognitive performance, at least, with simple and repetitive tasks (that are a part of learning process), can be optimized for assessment and prediction of the productive indicators in normal (without time pressure) and under conditions of limited time for task performance using multiple regression models, if to use indices of both physiological support and space-related factors. Subjective psychological indices can be applied as well, but mostly in relation to young people rather than to adults. We believe that such models describe balance during cognitive performance as measured individual adaptive “norm”, where the latter can be associated with average productivity over time intervals measured in weeks.
Oleksandr Burov, Evgeniy Lavrov, Svitlana Lytvynova, Olga Pinchuk, Oleksii Tkachenko, Natalia Kovalenko, Svitlana Agadzhanova, Yana Chibiryak, Olena Pinchuk
Open Access
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A Bridge too Far: Low Literacy and Cybersecurity Materials
Accessibility is emerging as the third dimension of cybersecurity design, addressing the growing concern that dependence on digital services is creating disparities in vulnerable populations. While many factors influence the effectiveness of cybersecurity materials, most materials providing security advice are written at a high school or college level. This means over 30% of the United States adult population would struggle to understand them. To explore how the gap between standard materials and the average reading level might be bridged, we contextualized guidelines for low-literacy design in the cybersecurity domain. Three main considerations – text characteristics, focused content, and graphic design – were used to redesign text-based cybersecurity materials. A mixed factorial design was used to evaluate the effectiveness of the redesigned materials for university students at higher and lower literacy levels. The study found that participants with lower literacy levels scored lower on cybersecurity knowledge tests and tended to rate all cybersecurity materials (standard and redesigned for low literacy) less favorably than participants with higher literacy levels. Surprisingly, although materials were redesigned to objectively improve the communication of cybersecurity information, those materials did not impact post-test measures of cybersecurity knowledge and the materials were rated as less effective. These findings suggest that changes intended to simplify content may have unintended consequences, potentially limiting the design’s effectiveness.
Mary Still, Jeremiah Still, Hagar Baruch
Open Access
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Perceptions of Undesirable Software Development Tasks among Computer Science Students
Software development projects inevitably involve a mix of technical and non-technical tasks, not all of which are equally appealing to those who perform them. While prior research has extensively examined how professional software developers perceive and manage undesirable tasks, the academic context, particularly students’ experiences, remains largely underexplored. This proposed presentation addresses this gap by reporting preliminary findings from an exploratory study conducted at Østfold University College, focusing on how students perceive undesirable software development tasks, the factors contributing to such perceptions, the emotional impact of performing these tasks, and the strategies students employ to cope with them. Understanding these dimensions is significant, as negative experiences with certain tasks may affect students’ motivation, well-being, and learning outcomes, ultimately influencing their preparedness for professional practice.The study adopted a survey-based research approach to gather empirical data from students enrolled in IT-related programs, including computer science and software engineering. A total of 30 participants with prior experience in academic software development projects completed an online questionnaire. The survey design followed empirically validated guidelines to ensure clarity and reliability and consisted of both closed-ended Likert-scale questions and optional open-ended questions. The questionnaire examined four main areas: perceived task undesirability, factors contributing to task undesirability, emotional and psychological impact, and coping strategies. Quantitative data were analyzed using descriptive statistics, while open-ended responses were examined using thematic analysis to capture additional contextual insights.The results indicate that students perceive several common software development activities as undesirable, most notably back-end related tasks, bug fixing, and writing documentation. These tasks were also reported as being frequently encountered, suggesting a persistent source of frustration in academic projects. In contrast, collaborative activities such as working with others or attending meetings were generally perceived as less undesirable, highlighting a divergence from findings reported in professional contexts. Performing undesirable tasks was associated with negative emotional responses, including reduced motivation, frustration, boredom, and, in some cases, procrastination. Although extreme outcomes such as intentions to leave a course or group were relatively rare, the prevalence of demotivation underscores the potential long-term impact on student engagement.Several factors were found to intensify task undesirability, including unrealistic deadlines, insufficient communication regarding the importance or future relevance of tasks, and concerns about personal well-being. To cope with undesirable tasks, students most commonly relied on a “Just Do It” approach, alongside collaborative strategies such as working in pairs, seeking help, and maintaining communication within the group. In particular, collaboration-based strategies were perceived as particularly effective.Overall, the findings suggest that undesirable tasks are an integral part of students’ academic software development experience and have meaningful emotional and motivational consequences. The presentation argues that these insights offer opportunities for educators to design curricula and learning environments that better address human dispositions, mitigate negative impacts, and potentially make undesirable tasks more meaningful and engaging for students. The study highlights the potential of AI tools to support and mitigate undesirable software development tasks.
Omar Chaaban, Mary Sánchez-Gordón, Selina Demi
Open Access
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Manual Dexterity Required for Clothing Repairs: Assessing the Influence of Thread Fineness on Evaluation Outcomes
In pursuit of a sustainable society, there is a renewed scholarly interest in traditional garment repair techniques. As individuals progress through different stages of development, does their manual dexterity enhance enough to enable them to mend clothes effectively? In Japan, sewing skills are incorporated into the "Home Economics" curriculum in educational institutions. Nonetheless, there are ongoing concerns regarding insufficient proficiency in these skills, which are attributed to a reduction in instructional hours and limited practical opportunities in daily life. This study explores the current state of manual dexterity in hand sewing and assesses the influence of thread fineness on evaluation outcomes. The study evaluated hand-sewn samples produced by 142 junior high school students, who utilized two types of cotton threads with varying fineness: #20(Ne7) and #30(Ne10), with the latter being more commonly employed. The results indicated no significant difficulties in performing basic stitches. However, concerning the presence of loops in the starting knot, the probability of loop formation was significantly lower for #20 than for #30. The odds ratio with #20 as the reference was 2.5 (95%CI:1.3–4.9). This finding was attributed to #30 being more prone to bending than #20 because of the moment of inertia of the area, leading to the formation of twists and tangles at various points along the thread. Based on the results obtained, it was considered desirable to adopt #20 or thicker thread as the practice thread for a starting knot.
Mika Morishima, Mari Kameda, Mina Ushiro
Open Access
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An Empathy-to-Testing Workshop to Strengthen Human Factors Evaluation in Design Education
This paper reports an experiential workshop intervention embedded in an undergraduate human factors (HF) course for industrial design. The intervention followed an empathy-to-testing sequence. Before the workshop, students completed an empathy-oriented preparation activity by imitating age-related and disability-related constraints to sensitize them to embodied interaction barriers and everyday usability issues. During the workshop, students engaged in hands-on tasks that deliberately exposed usability and ergonomic failures, followed by guided reflection and rapid redesign. The workshop explicitly emphasized the “test phase” of the design process: students defined simple evaluation goals, selected observable criteria, and conducted basic tests of early concepts and discussion of core principles (affordances, feedback, mapping, constraints, and error prevention) to connect observations to theory.Effectiveness was evaluated using a mixed-methods approach focused on three indicators: a pre–post motivation questionnaire (learning motivation and self-efficacy), a post-workshop questionnaire on perceived usefulness and transfer intention, and a course exam assessing core HF knowledge. Results indicated increased motivation toward HF learning and strong perceived value of embodied simulation and testing-oriented practice for making abstract principles observable and actionable. Students reported greater confidence in identifying HF issues and justifying design decisions with evidence, while exam outcomes indicate that an experiential emphasis can coexist with theoretical consolidation. The study offers practical evidence for integrating feasible HF evaluation into early-stage design education.
Chun-ting Wu
Open Access
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Conference Proceedings
Eye-Tracking Analysis of Students’ Problem-Solving Behaviors for Learning Support in a Tutoring Context
Understanding students’ visual engagement during problem solving can provide insight into learning strategies beyond performance outcomes. This study explores gaze-based indicators of learning behavior in a real-world tutoring context using non-intrusive, webcam-based eye tracking. Junior high school students solved computer-based multiple-choice questions while gaze data were synchronized with problem-solving logs. We propose a simple analytical framework based on areas of interest representing question statements, answer choices, and non-task regions, and compute descriptive gaze metrics capturing attention allocation, comparison behavior, and exploration patterns. Group-level analysis based on task accuracy suggests that higher-performing students tend to exhibit more frequent transitions between questions and answer choices and more diverse gaze movements, while time-based measures show limited differentiation. These findings indicate that qualitative gaze patterns can provide complementary insight for supporting tutoring instruction and reflective learning support in everyday educational settings.
Kento Yamao, Noriaki Kuwahara
Open Access
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Designing an AI-Supported Intercultural Educational Methodology for Native Maize Communities in Oaxaca
Indigenous rural communities preserve valuable biocultural knowledge associated with native maize conservation, agroecological practices, traditional gastronomy, cultural heritage, and community-based tourism. However, educational initiatives frequently address these dimensions separately, limiting their contribution to sustainable territorial development and knowledge transmission. This study presents the design of an Artificial Intelligence-supported intercultural educational methodology developed during Phase 1 of Project IH-2025-G-308 in indigenous communities of Tlaxiaco, Oaxaca, Mexico. The methodology was constructed through participatory action research and interdisciplinary process involving researchers, educators, agricultural specialists, and community stakeholders. Four interconnected educational dimensions were identified to structure the learning framework: environmental, agroecological, cultural, and economic. Based on these dimensions, four complementary diagnostic instruments were developed, including a semi-structured interview guide, a community observation protocol, a 20-item Likert-scale questionnaire, and a community participation registry. The resulting framework was organized into five learning subsystems: natural resource conservation, native maize and agroecological practices, cultural heritage and traditional knowledge, community-based tourism and regional entrepreneurship, and Artificial Intelligence-supported educational innovation. The methodology incorporates cross-sectional and longitudinal assessment strategies and establishes a structured pathway for transforming community knowledge into illustrated educational materials, bilingual audiovisual resources, training activities, and culturally adapted learning experiences. The proposed framework contributes to a human-centered and replicable methodology that integrates regional knowledge systems, participatory action research, intercultural education, and Artificial Intelligence to support biocultural heritage conservation, community learning, and sustainable rural development.
Diana Rubi Oropeza-tosca, Rodolfo Martinez Gutierrez, Omar Jimenez-marquez, Karina González-Izquierdo, Reiner Rincón-Rosales, Luis Alberto Manzano-Gómez, Clara Ivette Rincón-Molina, Victor Manuel Ruiz-Valdiviezo, José Juan Escalante-Fernández, Roger Notario-Priego, Pedro Ramón-Santiago, Irving Bruno López-Santos, Miguel Ángel Gómez-Jiménez, Gaudencio Lucas-bravo
Open Access
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Integrating Generative AI in Engineering Education: A Longitudinal Framework on Personality, Roles, and Perceptions
This study investigates how engineering students’ personality traits, perceived team roles, and AI literacy influence their perceptions of generative Artificial Intelligence (Gen-AI) tools in university education. Building on previous frameworks that link psychological and behavioral variables to technology adoption, a longitudinal design was adopted across two academic years (2023–24 and 2024–25) at the University of Udine. The same validated questionnaire was administered to undergraduate and graduate engineering students, combining the Big Five personality inventory, perceived team-role selection, and five multi-item scales measuring Attitude, Trust, Social Influence, Fairness & Ethics, and Usefulness toward Gen-AI. Descriptive and inferential analyses showed stable perceptions over time, with small yet meaningful increases in Attitude and AI Literacy (p < .05). The mediation analysis indicated that AI literacy acts as a mediator between Openness and perceived Usefulness, although the effect was small and non-significant. The results suggest that continued exposure to Gen-AI fosters both greater confidence and more critical awareness among engineering students. The study provides evidence of the structural reliability of the proposed Excel-based framework and offers practical guidance for integrating AI literacy modules into design-oriented engineering curricula.
Stefano Filippi, Emanuele Vaglio, Barbara Motyl
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GenAI and Search Tools in Design Education: Comparative Analysis of Student Creativity, Outcomes, and Experiences
This study investigated how different creativity-support tools shape the ideation processes and outcomes of industrial design students. Undergraduate participants (N=45) were divided into three conditions: (1) no tool, (2) image search using Pinterest, and (3) generative AI image generation using Midjourney. Their design outputs were subsequently evaluated by expert reviewers (N=10) across four dimensions: effectiveness, originality, usability, and feasibility. Findings indicate that search tools facilitated connections to real-world cases, enhancing the rationality and feasibility of concepts, yet also introduced risks of homogenization and imitation. Generative AI tools, by contrast, expanded divergent thinking and metaphorical expression, fostering originality but revealing limitations in controllability and practical applicability. Overall, this research contributes empirical evidence on the differentiated roles of search-based and generative tools in design ideation, and highlights the pedagogical value of integrating these tools complementarily in design education to balance novelty with practical feasibility.
Xue Xia, Shuting Jin, Bote Qi
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Evaluating Coloured Blob Tracking, CNN and Posture Detection computer vision models on latency and accuracy in the application of a virtual drum kit
Drumming is often inaccessible to beginners due to high costs, space constraints, and noise. While commercial "drumless" virtual systems exist, they rely on expensive hardware like VR goggles, infrared cameras, and motion-sensor drumsticks. These solutions remain costly and inconvenient, failing to address the core issue of accessibility. This paper proposes a low-cost computer vision (CV)-based virtual drum system that works on minimal hardware, such as a consumer laptop with a standard webcam.This study investigates the effectiveness of a range of computer vision techniques for real time drumstick and foot tracking, along with reliable event detection for a virtual drum kit. Four models were implemented using different combinations of established CV methods, including coloured blob tracking, Kalman filtering for motion prediction, dynamic region of interest (ROI) scaling, posture tracking using the MediaPipe pose estimation framework, and convolutional neural network (CNN) based drumstick detection using the YOLOv8 object detection model. All models were designed to track two drumsticks and two knees and detect the corresponding events. Each model was bound to identical hardware constraints. Performance evaluation in this study focuses on two primary metrics: accuracy, measured using precision, recall, and F1-score derived from false positives and false negatives produced during drumming sequences; and latency, measured as the temporal difference between the actual moment a drum hit occurs and when the system registers that event. These metrics were chosen because they directly impact the user experience in a real-time virtual musical instrument.
Kenneth Y T Lim, Joshua Ze Quan Lee
Open Access
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AI and Unplugged Creativity: Reimagining Accessible Intelligence through AI-Scaffolded Paper-Cutting for Marginalized Communities
Background: While generative AI holds transformative potential for creative education, it often exacerbates the digital divide for children in the Global South. Its 'screen-centered' paradigm reinforces algorithmic colonialism, where result-oriented outputs often marginalize local narratives and impose alien cultural frameworks, further isolating those in low-resource environments.Objective: This study proposes an unplugged, AI-scaffolded intervention paradigm to stimulate creativity and critical thinking among rural children in low-tech environments. Methods: Guided by the "3E" principles (Embedded, Embodied, Emergent), we developed an AI-integrated toolkit that transforms a single A3 paper into a creative "Zine" through non-electronic paper-cutting activities. A study was conducted with 40 students in rural China, using AI as a heuristic scaffold to provide cultural imagery through questioning rather than direct answers. Data were collected via coded artworks. Results: Findings indicate that: (1) AI-scaffolding significantly enhances narrative complexity and personalized creative expression; (2) Compared with "answer-oriented" outputs, AI’s guided intervention triggers more iterative thinking and reflective dialogue, fostering creative agency rather than technological dependence; and (3) highly embodied interactions increase creative autonomy and immersion. Conclusion: This research demonstrates a scalable, new inclusive design framework that activates local cognition through low-tech human-AI collaboration, providing a viable model for culturally adaptive intelligence in marginalized communities.
Jingjing Wang, Jiaxin Qin, Duoduo Zhang
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Applicability of Generative AI in Learning Systems for Assistive Technology Development Personnel Training
This study aims to develop effective personnel training methods for assistive technology development, which requires collaboration among members from multiple professional fields. We generated video materials and an interactive learning support tool using generative Artificial Intelligence (AI) and Retrieval-Augmented Generation (RAG), which draws on the same knowledge database. We conducted a questionnaire survey involving a trial of the prototype system to confirm its applicability. In the survey, 31 participants freely used a learning system prototype to view video materials and try out generative AI support tools. According to the survey results, 83.9% of participants watched all video materials, and 58.1% interacted with generative AI via text. Regarding the prototype try-out, the usefulness question received an average rating of 4.1 on a 5-point scale. The question of whether participants would like to use such an AI system in the future received an average rating of 4.0. The results suggested that our learning system was an acceptable way to acquire foundational knowledge.
Satori Hachisuka, Haojie Li, Yuko Nishiura, Tadamitsu Matsuda, Nobuhiko Haga, Misato Nihei
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Semantic Structure and Importance Extraction from Sequential Conversational Data via Dimensional Reduction
The analysis of spoken data from panel discussions, policy dialogues, and educational meetings has gained increasing importance in both academic research and professional practice. However, conventional approaches to Japanese conversation analysis have relied heavily on keyword matching or surface‑level text similarity, making it difficult to capture deeper semantic relationships, topic transitions, and latent discourse structures. In addition, Japanese natural language processing pipelines often rely on environment-sensitive morphological analyzers, which hinder reproducibility and large-scale processing. To address these limitations, this study proposes a robust and semantically enriched framework for conversation understanding based on a composite distributed representation. The proposed method integrates three layers of linguistic information: (1) contextual sentence embeddings generated by a multilingual transformer model, (2) word embeddings obtained from fastText, and (3) co‑occurrence vectors that capture lexical association patterns within the conversation. Sudachi is employed for Japanese text preprocessing to ensure stable and reproducible morphological analysis. By combining these components into a unified composite vector, the framework simultaneously represents global sentence‑level meaning and local lexical relationships. Using this representation, a directed graph is constructed that incorporates both temporal adjacency and semantic proximity between utterances, enabling the visualization of key conversational connections. To evaluate the effectiveness of the composite representation, dimensionality‑reduction algorithms are applied to examine whether semantically similar utterances naturally form coherent clusters in low‑dimensional space. The resulting clusters are assessed for consistency and interpretability, demonstrating that the proposed representation successfully captures meaningful conversational structure.
Takeshi Matsuda, Michio Sonoda
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The Importance of Integrating Personality as a Topic in Crew Resource Management Training
Current maritime Crew Resource Management (CRM) courses cover a wide range of relevant topics, such as communication and leadership style, but content specifically addressing individual differences and personality is not mandatory. This paper draws on personality profile data from 457 container ship officers to illustrate how general knowledge and insights about personality, traits, and individual profiles can be integrated into CRM courses to initiate meaningful discussions and reflections. We conclude that such integration will enrich CRM learning outcomes by deepening participants’ understanding of the relationships between personality, behaviour, and team dynamics. Moreover, it can enhance overall safety and performance by enabling officers to recognise and reflect on personality differences, thereby empowering them to influence their own working conditions and team performance.
Thomas Koester, Mariam Mastour
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Beyond Precarious Hustling: An AI-Oriented Curriculum Framework for Sustainable Creative Entrepreneurship in the Global South
Creative economies worldwide are recognized as vital engines for inclusive growth, job creation, and cultural innovation. Yet, in the Global South, creative entrepreneurs operate within ecosystems marked by persistent precarity: informal employment, limited access to capital, weak infrastructure, and educational systems misaligned with digital realities. While generative artificial intelligence (GenAI) presents transformative potential for creative production and entrepreneurship, its benefits risk exacerbating existing inequalities without intentional educational scaffolding. This paper synthesizes research from Ghana, alongside broader scholarship on creative work in emerging economies, to argue that the transition from precarious hustling to sustainable creative entrepreneurship requires a fundamental reimagining of education. We propose a globally relevant yet context-sensitive framework for an AI-oriented curriculum. This framework moves beyond technical skill acquisition to integrate critical GenAI literacy, humane-oriented entrepreneurial mindsets, and an understanding of the political economy of creative work. Designed for adaptability across diverse Southern contexts, the framework emphasizes glocalization—the fusion of global technological competencies with local cultural knowledge and economic conditions. It positions education not as a peripheral support, but as the central infrastructure needed to convert creative potential into dignified labour, resilient enterprises, and equitable participation in the global digital economy. The paper concludes with strategic implementation principles for educators, policymakers, and international development partners.
Mohammed Aminu Sanda, Mohammed-Nuru Sallama
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Technology-Enhanced Learning for Emergencies: Mapping the Impact of Simulator and VR Training
Technology-enhanced training using simulators and virtual reality (VR) has gained prominence in preparing professionals for emergencies in safety-critical domains. This systematic evidence mapping review synthesises 27 empirical studies published between 2016 and 2025, exploring how simulator-based, VR, and related modalities impact emergency preparedness outcomes. Studies were coded by modality, domain, scenario type, fidelity, target group, assessment approach, and outcome direction. The analysis reveals that training effectiveness depends more on the alignment between modality and training goals than on the technology itself. Several studies report positive short-term outcomes such as procedural performance and self-efficacy, but evidence of long-term behavioural transfer is limited. Team-level benefits emerge when scenarios are designed for interdependence, yet many VR systems remain structurally individual. Outcome measurement critically shapes conclusions: behavioural assessments yield stronger evidence than self-report alone. This review offers a structured evidence map and design-evaluation insights, guiding future research and practice in technology-enhanced emergency training toward goal-modality fit and performance-based evaluation.
Salman Nazir, James Badu, Natalia Andreassen, Rune Elvegard
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