Enhanced Learning Experience Research Articles

The future of nutrition education for health systems capacity building

Abstract In the ever-evolving landscape of global health, nutrition education plays a pivotal role in shaping the well-being of populations. The future of nutrition education encompasses a holistic understanding of health, considering not nutritional adequacy in health and disease, but also cultural, social, and environmental factors. Tomorrow’s health professionals must also be equipped to address the interconnectedness of nutrition with mental health, sustainability, and community dynamics. Nutrition education will increasingly involve collaboration across disciplines. Health professionals, educators, policymakers, and community leaders must work together to create a comprehensive ecosystem that fosters nutrition literacy. This collaboration extends beyond traditional healthcare settings to schools, workplaces, and local communities. Furthermore, digital transformation will also revolutionise nutrition education. Online platforms, mobile apps, and virtual simulations will enhance learning experiences whilst interactive modules, webinars, and gamified content will engage learners and facilitate continuous professional development. Moreover, telehealth and tele-nutrition will bridge geographical gaps, ensuring access to quality education globally. Cultural sensitivity in nutrition education is also needed across geo-demographic boundaries to appreciate diverse dietary practices, food taboos, and traditional knowledge. Nutrition education should also empower health professionals to advocate for policy change across food systems, promote sustainable practices, and address food insecurity and therefore understanding policy frameworks and participating in advocacy efforts will be key. Finally, embracing the future requires a commitment to lifelong learning to remain at the forefront of nutrition science and its cutting edge as the questions may remain the same but the answers vary significantly as we garner new evidence to navigate evolving global challenges.

AI chatbot: I want help, not the answer!

In recent years, the integration of artificial intelligence (AI) into educational settings has become a topic of great interest. As technology continues to evolve, educators and students are exploring how AI can enhance learning experiences. University of South-Eastern Norway (USN) and Kristiania University College (HK) are developing a web-based educational tool, DbPersist, where IT students can practice tasks within the database subject and receive automated feedback. The latest version now also offers students suggestions on how to utilize AI for learning while they are solving various database related tasks. In this study, we explore the students' experiences with getting automatically generated “prompts” for further use in their preferred AI tool, whenever they request assistance. Do they see the value in gaining experience in using prompts designed for learning? Do they believe it might help them using AI for learning purposes in other courses in their study? To answer these questions, we conducted surveys and interviews. Participants included bachelor students across various disciplines and multiple campuses at USN. The participants were all enrolled in database courses with learning goals involving the database query language SQL and ER modelling (drawing Entity-Relationship Diagrams). Early findings suggest that students appreciate the assistance provided by DbPersist’s AI prompts. They value the emphasis on AI-assisted learning and find the prompts useful for getting assistance in solving difficult tasks as opposed to getting complete answers. They also see the value in gaining experience in using AI chatbots using prompts designed for learning and understanding. As AI continues to shape education, tools like DbPersist offer exciting possibilities. DbPersist exemplifies how AI may be used to empower students, emphasizing learning and understanding alongside correctness.

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

"Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions," edited by Beth Buyserie and Travis N. Thurston, is a timely and essential addition to the ongoing dialogue about AI's role in education. This book thoroughly examines the opportunities and challenges that AI technologies bring to both traditional and online classroom environments. This comprehensive volume delves into the multifaceted impact of AI on educational practices, offering insights into how these technologies can enhance learning experiences and pedagogical strategies. The editors, Buyserie and Thurston, have curated a collection of essays and studies that highlight the transformative potential of AI in personalizing learning, automating administrative tasks, and providing real-time feedback to students.

Promises and challenges of generative artificial intelligence for human learning.

Generative artificial intelligence (GenAI) holds the potential to transform the delivery, cultivation and evaluation of human learning. Here the authors examine the integration of GenAI as a tool for human learning, addressing its promises and challenges from a holistic viewpoint that integrates insights from learning sciences, educational technology and human-computer interaction. GenAI promises to enhance learning experiences by scaling personalized support, diversifying learning materials, enabling timely feedback and innovating assessment methods. However, it also presents critical issues such as model imperfections, ethical dilemmas and the disruption of traditional assessments. Thus, cultivating AI literacy and adaptive skills is imperative for facilitating informed engagement with GenAI technologies. Rigorous research across learning contexts is essential to evaluate GenAI's effect on human cognition, metacognition and creativity. Humanity must learn with and about GenAI, ensuring that it becomes a powerful ally in the pursuit of knowledge and innovation, rather than a crutch that undermines our intellectual abilities.

Revolutionizing Computer Science Education: Integrating Blockchain for Enhanced Learning and Future Readiness

Abstract: This research investigates the transformative potential of incorporating blockchain technology into computer science education. In light of the rapid evolution of the digital landscape, traditional educational frameworks often fail to meet the demands of the industry, resulting in a significant skills gap among graduates. This paper analyzes how the integration of blockchain can revolutionize computer science curricula by enhancing learning experiences and equipping students to navigate future technological challenges. The study highlights the advantages of blockchain in educational contexts, including increased security and transparency of academic records, streamlined credentialing processes, and the establishment of decentralized learning platforms that promote collaboration and innovation. It presents case studies of institutions that have successfully implemented blockchain, along with strategies for educators to effectively integrate this technology into their pedagogical approaches. Additionally, the research addresses the challenges and limitations associated with blockchain integration, such as the requisite learning curve and infrastructure demands. The findings indicate that the incorporation of blockchain in computer science education can significantly boost student engagement, provide verifiable skill sets, and align academic outcomes more closely with industry requirements. This study contributes to the ongoing discourse on educational innovation and offers a strategic framework for institutions aiming to utilize blockchain technology in preparing students for the future job market.

Generative AI Applications in Architecture, Engineering, and Construction: Trends, Implications for Practice, Education & Imperatives for Upskilling—A Review

This study investigates the current landscape of generative AI and LLM applications in architecture, engineering, and construction (AEC), focusing on trends, practical implications, educational strategies, and imperatives for upskilling. Employing a six-stage systematic review sourced from Google Scholar, Scopus and Web of Science, 120 papers were analyzed to provide a comprehensive understanding of the role of these technologies in shaping the future of the AEC industry. By addressing these objectives, the research contributes to enhancing knowledge about the potential impacts of generative AI and LLMs on the AEC industry and provides insights into strategies for leveraging these technologies effectively. This study underscores the transformative impact of AI and advanced technologies on the AEC sector and education. By enhancing learning experiences and optimizing construction processes, AI fosters personalized education and efficient project management. The study’s significance lies in its identification of necessary skills and competencies for professionals, ensuring effective AI integration. Implications include the need for continuous professional development, formal education, and practical training to leverage AI’s potential fully. This paves the way for sustainable, intelligent infrastructure and accessible, adaptive learning environments, driving innovation and efficiency in both fields.

Integrating Biotechnology Virtual Labs into Online Education Platforms: Balancing Information Security and Enhanced Learning Experiences

Information and Communication Technology (ICT)-enabled virtual labs to offer an online educational experience utilizing computer-based teaching resources (scenes, simulations, and remote-trigger activities) to enhance the active studying experience. This article discusses a project established to improve university and college instruction, which is evolving into a sophisticated training setting for addressing the geographical, social, and financial obstacles in the interdisciplinary domain of science learning, particularly in India. A pedagogical assessment was conducted through seminars and online comments to examine the function of biotechnology simulations in the contemporary school system, involving various student and instructor groups from many Indian institutions. This chapter discusses the utilization of biotechnology virtual laboratories in biotechnology to enhance teaching and learning processes through user involvement and how these technologies successfully mitigate the challenges of laboratory schooling, particularly in remote regions. The findings from user feedback evaluation indicate that online laboratories are advisable to incorporate into blended classes in giant classrooms to improve self-sufficient instruction and enhance virtual laboratory education in isolated and financially disadvantaged institutions.

The efficacy of augmented reality in small group instruction for children with autism spectrum disorders: a study on observational learning

Objectives Observational learning and augmented reality (AR) are crucial in enhancing learning experiences for children with autism spectrum disorder (ASD), fostering engagement and skill acquisition. The current study aimed to determine the effects of AR technology delivered to them in small group instructional arrangements (SGIA), such as the acquisition of targeted occupation and non-targeted information about the tasks of occupations by children with ASD. The study also aimed to determine the acquisition levels of other children in the group regarding the targeted occupations and non-targeted information about the tasks of the occupations through observational learning. Methods Three males aged between 45–59 months took part in the study. The study was designed with a multiple baseline across participants. Results The findings revealed that the AR intervention delivered in SGIA was effective in teaching occupation and non-targeted information to children with ASD, as well as in maintaining and generalizing the learning by the children to different contexts. Children acquired the occupation and non-targeted information about occupations that were not targeted to be taught to them mostly by observing their peers. Conclusions The findings are discussed in accordance with the findings of previous studies, and suggestions for further research are provided.

Enhancing fieldwork readiness in occupational therapy students with generative AI

The rapid integration of artificial intelligence (AI) into health professions education is revolutionizing traditional teaching methodologies and enhancing learning experiences. This study explores the use of generative AI to aid occupational therapy (OT) students in intervention planning. OT students often lack the background knowledge to generate a wide variety of interventions, spending excessive time on idea generation rather than clinical reasoning, practice skills, and patient care. AI can enhance creative ideation but students must still adhere to evidence-based practice, patient safety, and privacy standards. Students used ChatGPT v. 3.5 in a lecture and assignment to integrate generative AI into intervention planning. Students analyzed a case study, generated ideas with ChatGPT, selected interventions that aligned with the client’s needs, and provided a rationale. They conducted evidence-based searches and wrote an analysis on how the research influenced their decisions. The results demonstrate generative AI’s potential as a valuable tool for OT students, enhancing their comfort with AI and understanding of ethical and safety considerations. Qualitative feedback highlighted AI’s role in boosting efficiency and creativity in intervention planning, with most students expressing strong intent to use ChatGPT in clinical practice due to its ability to reduce cognitive load and generate innovative ideas. These findings suggest that integrating generative AI into the OT curriculum could enhance intervention planning and improve clinical readiness.

The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI-supported assessment

The rapid adoption of generative artificial intelligence (GenAI) technologies in higher education has raised concerns about academic integrity, assessment practices and student learning. Banning or blocking GenAI tools has proven ineffective, and punitive approaches ignore the potential benefits of these technologies. As a result, assessment reform has become a pressing topic in the GenAI era. This paper presents the findings of a pilot study conducted at British University Vietnam exploring the implementation of the Artificial Intelligence Assessment Scale (AIAS), a flexible framework for incorporating GenAI into educational assessments. The AIAS consists of five levels, ranging from “no AI” to “full AI,” enabling educators to design assessments that focus on areas requiring human input and critical thinking. The pilot study results indicate a significant reduction in academic misconduct cases related to GenAI and enhanced student engagement with GenAI technology. The AIAS facilitated a shift in pedagogical practices, with faculty members incorporating GenAI tools into their modules and students producing innovative multimodal submissions. The findings suggest that the AIAS can support the effective integration of GenAI in higher education, promoting academic integrity while leveraging technology’s potential to enhance learning experiences. Implications for practice or policy: Higher education institutions should adopt flexible frameworks like the AIAS to guide ethical integration of GenAI into assessment practices. Educators should design assessments that leverage GenAI capabilities, while supporting critical thinking and human input. Institutional policies related to GenAI should be developed in consultation with stakeholders and regularly updated to keep pace with technological advancements. Policymakers should prioritise research funding into the impacts of GenAI on higher education to inform evidence-based practices.

Leveraging Artificial Intelligence In Project-Based Service Learning To Advance Sustainable Development: A Pedagogical Approach For Marketing Education

ABSTRACT Artificial intelligence (AI) has revolutionized various aspects of teaching and learning in higher education, with the potential to significantly enhance learning experiences, streamline administrative tasks, and foster personalized education. As the use of AI by students and instructors expands, it is crucial to carefully consider both its benefits and risks, as well as to adhere to ethical guidelines and best practices. A systematic literature review was conducted to investigate the application of experiential learning theory in marketing education, particularly focusing on the integration of new technologies and tools, such as AI, within project-based service learning (PBSL). This review explores how these integrations may positively impact student learning outcomes, community partner benefits, and contributions toward the United Nations’ Sustainable Development Goals (SDGs). Specifically, the potential of AI in the marketing classroom to advance these goals was examined utilizing the Artificial Intelligence for Service Learning and Experiential Education (AISLE) model. This model advocates for an ethical approach to using AI in educational settings, leveraging theory-based innovative practices to achieve positive, measurable outcomes for both students and community partners.

Enhancing learning experiences: EEG-based passive BCI system adapts learning speed to cognitive load in real-time, with motivation as catalyst.

Computer-based learning has gained popularity in recent years, providing learners greater flexibility and freedom. However, these learning environments do not consider the learner's mental state in real-time, resulting in less optimized learning experiences. This research aimed to explore the effect on the learning experience of a novel EEG-based Brain-Computer Interface (BCI) that adjusts the speed of information presentation in real-time during a learning task according to the learner's cognitive load. We also explored how motivation moderated these effects. In accordance with three experimental groups (non-adaptive, adaptive, and adaptive with motivation), participants performed a calibration task (n-back), followed by a memory-based learning task concerning astrological constellations. Learning gains were assessed based on performance on the learning task. Self-perceived mental workload, cognitive absorption and satisfaction were assessed using a post-test questionnaire. Between-group analyses using Mann-Whitney tests suggested that combining BCI and motivational factors led to more significant learning gains and an improved learning experience. No significant difference existed between the BCI without motivational factor and regular non-adaptive interface for overall learning gains, self-perceived mental workload, and cognitive absorption. However, participants who undertook the experiment with an imposed learning pace reported higher overall satisfaction with their learning experience and a higher level of temporal stress. Our findings suggest BCI's potential applicability and feasibility in improving memorization-based learning experiences. Further work should seek to optimize the BCI adaptive index and explore generalizability to other learning contexts.

From Consoles to Classrooms: Preliminary Insights About Pre-Service Teachers and Video Games

Integrating video games into the classroom is a promising way to enhance learning experiences, as the market of serious games is expanding. European schools are investing in digital equipment, and the use of educational video games is technologically viable. Nonetheless, actual experiences of video games in class are still rare. A key gap to be explored is understanding how pre-service secondary teachers perceive and are prepared to use digital games in their future classrooms. Do they think it would enhance their teaching and their students’ learning? Do they feel prepared for it? To answer these questions, and possibly address future challenges, we conducted a comprehensive study with students at Zurich University of Teacher Education (PHZH). The research process began with the development and testing of a detailed questionnaire that focused on participants' personal gaming behaviour, preferences, and perceptions of the educational potential of video games. Key areas such as serious games, game design, gamification, game-based learning, and game culture were explored to assess the relevance and understanding of these concepts in an educational context. This paper explains the development and structure of the questionnaire as a measurement instrument as well as the underlying literature and methodological considerations. The first implementation and the preliminary survey with 48 PHZH students are presented, and the practicability and reliability of the questionnaire are evaluated. The result of the survey suggests pre-service teachers are generally positive about integrating video games and game design into the classroom, yet enthusiasm is not enough without additional support.

Empowering the Faculty of Education Students: Applying AI’s Potential for Motivating and Enhancing Learning

AbstractThis study aimed to investigate how AI impacts students’ intrinsic motivation and learning experiences in various cultural and academic settings. An analysis of the effects of AI-powered learning tools on intrinsic motivation and learning enhancement was conducted in early 2024. The study recruited 455 students (192 males and 263 females) from Egypt, Saudi Arabia, Spain, and Poland who were studying diverse majors in educational faculties. Using a 5-point Likert scale, the validated instrument included three dimensions with a total of 10 items: intrinsic motivation and AI, AI and enhancing learning, and overall perception of AI in education. Significant differences were found by nationality and major, with Polish students and education technology majors showing the highest motivation levels. As a result of enhancing learning experiences, autonomy, and critical thinking skills, AI tools were found to positively influence motivation. Motivation, however, was not significantly influenced by academic level. Despite ethical concerns, students held a moderately positive view of artificial intelligence in education. Further research on optimal AI implementation and ethical considerations in education is necessary based on these findings.

Undergraduate Senior Nursing Students' Perceptions of Beneficial Prebriefing Practices.

Examining nursing students' perceptions of prebriefing and what components are most effective in preparation for simulation may help standardize prebriefing and enhance learning experiences. This qualitative descriptive study explored the perceptions of prebriefing, prework assignments, and what methods of prebriefing increased self-confidence when undergraduate nursing students participated in simulation. An inductive approach to content analysis was used to interpret the data. Two themes that emerged from the data were preparation is essential to simulation success and preparation is essential to future success. Additionally, five subthemes were identified: understanding content in advance, logistical clarity, well-prepared students are invested, increased self-confidence, and pride in education and learning. Prebriefing is essential to simulation and undergraduate nursing student success. Although prebriefing practices vary between educators, undergraduate nursing students valued prework and expressed a preference for written assignments. Overall, students perceived prework as increasing their self-confidence during simulation. [J Nurs Educ. 2024;63(10):693-697.].

여자 대학생의 학업 정서 군집과 유형: 군집 간 수업 참여 및 학업성취도 차이 분석

Learners can experience mixed emotions simultaneously. This study identified the emotion clusters based on positive activated (e.g., energetic) positive deactivated (e.g., calm), negative activated (e.g., angry), and negative deactivated (e.g., fatigued) emotions experienced by students in academic situations. We also examined differences in behavioral engagement, cognitive engagement, disengagement, and academic achievement among the derived emotion clusters. A total of 159 undergraduate students enrolled at a university in the Seoul metropolitan area participated in this study. As results, first, four different emotion clusters were identified: Positive (37%), Negative (16%), High-Mixed (31%), Moderate-Mixed (16%) clusters. Second, there were significant differences in the level of class engagement among the four clusters, with the Positive cluster generally showing a higher level of class engagement and the Negative cluster showing a lower level of class engagement. The High-Mixed cluster showed a similar level of class engagement to the Positive cluster but also displayed a higher level of disengagement. However, there were no significant differences in academic achievement according to the emotion clusters. This study empirically confirms that undergraduate students in academic situations often feel mixed rather than singular affects, through person-oriented analysis. Additionally, by examining the relations between the emotion clusters and academic-related variables, this study provides implications on which emotions should be educationally supported to enhance learning experiences.

The efficacy of simulation-based learning versus non-simulation-based learning in endocrinology education: a systematic review and meta-analysis

BackgroundSimulation-Based Learning (SBL) is increasingly adopted in medical education across various specialties, employing realistic simulations to significantly enhance learning experiences. However, a comprehensive evaluation of its effectiveness specifically in endocrinology has not yet been conducted. The study aims to systematically review and meta-analyze the impact of SBL versus Non-Simulation-Based Learning (NSBL) on knowledge acquisition, skills, satisfaction, and interest in learning among endocrinology trainees.MethodsThis systematic review and meta-analysis adhered to the PRISMA guidelines, searching PubMed, Web of Science, Embase, Cochrane library, China National Knowledge Infrastructure (CNKI), Wanfang Data, Weipu, and Chinese Biomedical Database (CBM) until March 2024. We included randomized controlled trials comparing SBL to NSBL in endocrinology education. The quality evaluation relied on the Cochrane risk-of-bias assessment tool. The main results included evaluations from both theoretical and practical assessments. Additional measures consisted of assessing satisfaction and interest in learning.ResultsWe identified 22 studies suitable for systematic review and 21 for meta-analysis, involving a total of 2517 participants. SBL greatly enhanced theoretical knowledge [standardized mean difference (SMD) = 1.00, 95% confidence interval (CI): 0.68–1.32, P < 0.00001, I2 = 89%] and practical skills (SMD = 1.56, 95% CI: 1.11–2.01, P < 0.00001, I2 = 93%) compared to NSBL. Additionally, SBL was associated with higher satisfaction and greater interest in learning. No significant publication bias was detected, and sensitivity analysis confirmed the stability of these findings.ConclusionsSBL significantly enhances knowledge, skills, satisfaction, and interest in learning within endocrinology education compared to NSBL. These findings support the integration of high-quality SBL into endocrinology curricula to improve educational outcomes. Future research should explore the lasting effects of SBL on knowledge retention and clinical practice, as well as to evaluate its cost-effectiveness and compatibility with various educational tools in diverse settings.

Understanding Teachers' Perspectives on ChatGPT-Generated Assignments in Higher Education

The rapid integration of artificial intelligence (AI) in education has transformed instructional methodologies and administrative tasks. However, teachers in higher education face challenges, particularly in creating high-quality assignments and rubrics amidst increasing administrative burdens. This study investigates the potential of AI, specifically ChatGPT, in streamlining assignment creation. Through automating aspects of assignment development, AI tools offer support to teachers while maintaining pedagogical integrity. However, empirical investigation is needed to understand perceptions and effectiveness. Using observations and semi-structured qualitative interviews, the study explores teachers' perceptions of AI-generated assignments and their impact on student learning outcomes and engagement. It also examines students' experiences and perceptions, understanding AI's role in enhancing learning experiences and facilitating teacher productivity. The data were analysed by content analysis. Findings suggest that teachers found the usage of ChatGPT helpful in reducing their administrative workload while maintaining academic integrity. Additionally, students embraced attempting the assignments, and doing so contributed to enhancing their subject knowledge. Furthermore, teachers facilitated students by encouraging them to reconsider the problem, persisting in their efforts, and inviting communication and collaboration with peers. The study also discusses the implications for teachers, highlighting AI's transformative potential.

Generative AI in student English learning in Thai higher education: More engagement, better outcomes?

Despite the growing body of research exploring artificial intelligence (AI) in educational contexts, there remains a critical gap in understanding the specific effects of generative AI (GAI) on English language learning, particularly within higher education in Thailand. This study addresses this gap by employing an explanatory sequential mixed-method design to explore both student and teacher perspectives. Quantitative data were analyzed using descriptive statistics, Mann-Whitney U tests, Spearman correlation analysis, and Kendall–Theil regression to examine students' acceptance, usage, and the relationship between GAI engagement and academic performance. Qualitative data, collected through structured written interviews, were analyzed using thematic analysis to uncover key themes from both student and teacher narratives. Quantitative findings reveal high student acceptance of GAI tools in terms of performance expectancy (M = 3.66, SD = .58), effort expectancy (M = 3.61, SD = .59), facilitating conditions (M = 3.51, SD = .59), and use behavior (M = 3.52, SD = .48), while social influence remained relatively lower (M = 3.31, SD = .54). Mann-Whitney U tests showed no statistically significant differences in GAI usage across high- and low-performing students (p > .05). Correlation analyses indicated strong associations between performance expectancy and other factors (ρ = .87, p < .001), yet no significant correlation with GPA (ρ = −.06, p = .76). Qualitative results from student reflections revealed improved efficiency, enhanced engagement, and increased linguistic confidence. Yet, concerns about overreliance on AI and the necessity for critical use were noted. Teacher narratives accentuated ethical concerns and the potential for GAI misuse, highlighting the need for balanced, responsible integration of AI into pedagogical practices. These findings underscore the potential of GAI to enhance learning experiences while emphasizing the importance of maintaining academic integrity and fostering critical thinking.

The effect of dynamic geometry software use for teaching and learning Grade 11 circle geometry

Background: Dynamic digital technologies (DDTs) are having an impact on children’s learning because they have the ability to improve learning while also addressing the issue of lack of interest and motivation. DDTs can also serve as a viable solution to the current crisis state of mathematics education in South Africa.Aim: The study examined how using GeoGebra dynamic geometry software in the teaching and learning of circle geometry in Grade 11 affected learners’ performance as well as their experiences.Setting: Eighty mathematics learners in Grade 11 participated in the study: 40 each in the experimental and control groups.Methods: The explanatory mixed methods research design was employed for this study, which comprised an experimental and control group design, wherein the experimental group was taught using GeoGebra activities, a control group was taught using a traditional approach (quantitative) and focus group discussions were conducted to gather students’ narratives about GeoGebra use (qualitative).Results: The study’s findings demonstrated that following the use of GeoGebra software for instruction, there were statistically significant differences between the experimental and control groups with t = 4.1762, p = 0.000077 and a Cohen’s d = 1.096277, which connotes a significant effect size as it is more noteworthy than the 0.8 thresholds.Conclusion: The study concluded that when learners are taught using GeoGebra software instead of traditional teaching methods, they seem to perform better academically in circle geometry and enjoy learning mathematics more.Contribution: This study contributes to improving the quality of mathematics education by leveraging technology to enhance learning experiences and outcomes.