Search Results (31)

(1) Background: Developing cultural competence and reflective communication skills remains a challenge in nursing education. Traditional teaching methods often provide limited opportunities for safe practice of culturally sensitive interactions in emotionally complex situations. Artificial intelligence (AI)–based patient simulations may offer a scalable approach to experiential and reflective learning. (2) Aim: This study explored the educational potential of AI-based patient simulations in supporting nursing students’ self-assessed cultural competence, reflective awareness, and communication confidence. (3) Methods: A convergent mixed-methods pre–post study was conducted among 24 s-cycle nursing students. Participants engaged in individual AI-based patient simulations with simulated patients representing diverse cultural contexts. Quantitative data were collected using an exploratory cultural competence self-assessment scale administered before and after the simulation. Qualitative data included post-simulation reflection forms and AI-student interaction transcripts, analysed using inductive thematic analysis. (4) Results: A statistically significant increase in overall self-assessed cultural competence was observed (Wilcoxon signed-rank test: Z = 4.05, p < 0.001, r = 0.59), with the greatest improvements in communication adaptability and perceived communication sufficiency. Qualitative findings indicated an emotional shift from uncertainty to engagement, heightened awareness of cultural complexity, reflective reassessment of assumptions, and high perceived educational value of AI simulations. (5) Conclusions: AI-based patient simulations represent a promising pedagogical tool for fostering reflective and communication-oriented learning in culturally complex nursing contexts. Their primary value lies in supporting experiential learning, emotional engagement, and the development of cultural humility, suggesting their potential role as a complementary educational strategy in advanced nursing education. Full article

Experiential learning involves gaining knowledge and understanding from real-life experiences, which helps develop new theories through fresh insights. Kolb described learning as the process of creating knowledge through transforming experience. Its main idea is that challenges and experiences, followed by reflection, lead to learning and growth. An experiential learning module (ELM) is a type of simulation that replicates a real-world situation, simplified to help participants understand complex problems from their perspective. It is based specifically on Kolb’s experiential learning cycle. ELMs use pictures, videos, and voice-over presentations to create a rich, contextually relevant, vicarious learning experience for classroom learners. In this study, the main ELM developed in Haiti was based on Kolb’s learning cycle. The primary goal of the ELM was to help global agriculturalists tackle complex issues related to food insecurity in developing countries. The purpose of this paper is to explain what experiential learning modules are and how to implement them in a study abroad program. An ELM on plantain production in Haiti was used as a case example. Students completed pre- and post-reflection surveys to evaluate their initial assumptions, expectations, and knowledge about the subject, as well as what they learned. A learning assessment measured their understanding of the ELM content. By analyzing the participants’ comments, the instructional approach proved effective in providing a vicarious experience within the classroom. The results from the initial classroom use of the banana and plantain learning module, along with student reactions, offered valuable feedback that led to proposed revisions and improvements to the tool. Full article

Time management is a critical competency for first-year college students, yet many struggle with limited self-regulation, and existing interventions are often short-term and weakly grounded in theory. This study explored how a design-based research (DBR) approach integrating experiential learning and digital tools could strengthen students’ time management skills. From 2021 to 2023, 238 first-year students at a research university in central China participated in a three-month hybrid Freshman Orientation Seminar, with data collected from daily submissions via a WeChat mini-program. Over three iterative DBR cycles, the intervention combined experiential learning theory with authentic time management practice, guided by quantitative and qualitative evidence to refine the pedagogical model. The process yielded six design principles and a supporting digital tool. In the final iteration, students demonstrated substantial gains, including improved planning, greater task completion, more accurate time allocation, and higher satisfaction with time use. These findings suggest that sustained, theory-guided experiential learning, when supported by digital tools, can significantly enhance time management competencies. The study contributes practical strategies for embedding self-regulated learning into higher education through technology-enhanced experiential approaches. Full article

The integration of Artificial Intelligence (AI) into higher education offers new opportunities for inclusive and sustainable learning. This study investigates the impact of an AI-enabled microlearning cycle—comprising short instructional videos, formative quizzes, and structured discussions—on student engagement, inclusivity, and academic performance in postgraduate management education. A mixed-methods design was applied across two cohorts (2023, n = 138; 2024, n = 140). Data included: (1) survey responses on engagement, accessibility, and confidence (5-point Likert scale); (2) learning analytics (video views, quiz completion, forum activity); (3) academic results; and (4) qualitative feedback from open-ended questions. Quantitative analyses used Wilcoxon signed-rank tests, regressions, and subgroup comparisons; qualitative data underwent thematic analysis. Findings revealed significant improvements across all dimensions (p < 0.001), with large effect sizes (r = 0.35–0.48). Engagement, accessibility, and confidence increased most, supported by behavioural data showing higher video viewing (+19%), quiz completion (+21%), and forum participation (+65%). Regression analysis indicated that forum contributions (β = 0.39) and video engagement (β = 0.31) were the strongest predictors of grades. Subgroup analysis confirmed equitable outcomes, with non-native English speakers reporting slightly higher accessibility gains. Qualitative themes highlighted interactivity, real-world application, and inclusivity, but also noted quiz-related anxiety and a need for industry tools. The AI-enabled microlearning model enhanced engagement, equity, and academic success, aligning with SDG 4 (Quality Education) and SDG 10 (Reduced Inequalities). By combining Cognitive Load Theory, Kolb’s experiential learning, and Universal Design for Learning, it offers a scalable, pedagogically sustainable framework. Future research should explore emotional impacts, AI co-teaching models, and cross-disciplinary applications. By integrating Kolb’s experiential learning, Universal Design for Learning, and Cognitive Load Theory, this model advances both pedagogical and ecological sustainability. Full article

The contemporary landscape is characterised by overlapping values and pressures, where ecosystem services and cultural spaces are used by diverse categories of users. In fragile contexts such as the Phlegraean Fields in Italy, the exponential growth of mass tourism has intensified the anthropogenic impacts, exacerbated by limited landscape awareness among local communities. Thus, walkability fosters direct exploration, while experiential transects provide a lens to read ecological, cultural, and perceptual layers of places. Together with digital storytelling, these approaches converge in a phygital approach that enriches physical experience without supplanting it. The study covered approximately 115 km of routes across five municipalities, combining road audits, an 11-item survey, participatory mapping, and ArcGIS StoryMaps. Results showed a structurally complex and functionally fragile mobility system: sidewalks are discontinuous, lighting insufficient, less than one quarter of the network is fully pedestrian, and cycling facilities are almost absent. At the same time, digital layers diversified routes and supported situated learning. By integrating geo-spatial analysis and phygital tools, the research demonstrates a replicable strategy to enhance the awareness and sustainable enjoyment of complex landscapes. The present research is part of the PNRR project Changes ‘PE5Changes_Spoke1-WP4-Historical Landscapes Traditions and Cultural Identities’. Full article

The rapid integration of Generative Artificial Intelligence in higher education challenges social work as student adoption outpaces pedagogical guidance. This paper argues that the unguided use of AI fosters cognitive debt: a cumulative deficit in critical thinking, ethical reasoning, and professional judgment that arises from offloading cognitive tasks. To counter this risk, a pedagogical model is proposed, synthesizing experiential learning, andragogy, and critical pedagogies. The framework reframes AI from a passive information tool into an active object of critical inquiry. Through structured assignments across micro, mezzo, and macro practice, the model guides students through cycles of concrete experience with AI, reflective observation of its biases, abstract conceptualization of ethical principles, and active experimentation with responsible professional use. Aligned with professional ethical standards, the model aims to prepare future social workers to scrutinize and shape AI as a tool for social justice. The paper concludes with implications for faculty development, institutional policy, accreditation, and a forward-looking research agenda. Full article

The rapid integration of artificial intelligence (AI), particularly generative AI (Gen-AI), into higher education presents a critical challenge: preparing students for the complex ethical dilemmas inherent in AI-driven research and practice. Current AI ethics education, however, often remains fragmented, overly theoretical, and disconnected from practical application, leaving a significant gap between knowing ethical principles and acting upon them. To address this pressing issue, this study proposes and validates a full-cycle AI ethics education system designed to bridge this gap. The system integrates three core components: (1) an updated four-dimensional ethics framework focused on Gen-AI challenges (research review, data privacy, algorithmic fairness, intellectual property); (2) a “cognition-behavior” dual-loop training mechanism that combines theoretical learning with hands-on, simulated practice; and (3) a full life-cycle education platform featuring tools like virtual laboratories to support experiential learning. A mixed-methods study with 360 students and 20 instructors demonstrated the system’s effectiveness, showing significant improvement in students’ ethical knowledge, a large effect size in enhancing ethical decision-making capabilities, and high user satisfaction. These findings validate a scalable model for AI ethics education that moves beyond passive instruction toward active, situated learning, offering a robust solution for higher education institutions to cultivate ethical responsibility in the age of Gen-AI. Full article

Mixed reality (MR) laboratories combine physical elements with virtual components, providing convenient experiential environments for testing engineering concepts. This article reports the design, validation, and implementation of an MR laboratory for engineering students to practice the implementation of control algorithms in microcontrollers. First, the design of the MR lab is described in detail. In this, a seesaw electromechanical system is emulated, being synchronized with electrical signals that represent sensors’ measurements and actuators’ commands. Thus, a control algorithm implemented by the students in a microcontroller can affect the simulated system in real time. The real seesaw system was used to validate the simulated plant in the MR lab, finding that the same control algorithm effectively controls both the simulated and physical seesaw systems. A practice, designed based on Kolb’s experiential learning cycle, where the students must implement P, PI, and PID controllers in the MR lab, was implemented. A survey was conducted to assess the students’ motivation, and a post-test was administered to evaluate their learning outcomes. Full article

Despite the recognized importance of creativity in secondary education, the role of design as a faculty for teaching abstract creative concepts effectively is seldom explored in depth, hindering students’ development. To address these issues, this study aimed to motivate secondary students to engage more deeply in innovative design by proposing a university-led workshop approach within a design competition module. This module was first implemented at Hong Kong Polytechnic University in the 2023/24 academic year, involving 301 students from 52 secondary schools in Hong Kong. Grounded in Kolb’s Experiential Learning Cycle, this research examines the current challenges of design education and explores the role of the proposed competition in cultivating secondary students’ innovative design capabilities. The findings contribute to understanding how this creative pedagogy can enhance secondary students’ interest and motivation in developing creative design skills by integrating university-led workshops into competitions, thereby enabling both secondary and tertiary educational institutions to address creative design challenges. Full article

The structural characteristics of hickory trees exhibit a significant correlation with their fruit yield. As a distinctive high-quality nut of Zhejiang Province, hickory is a unique high-end dry fruit and woody oil plant in China. However, the long growth cycle and extended maturation period make their management particularly challenging, especially in the absence of high-precision 3D digital models. This study aims to optimize hickory tree management and identify trees with the most optimal structural features. It employs gradient-boosted machine learning modeling based on 23 key tree characteristics, transforming the experiential knowledge of forest farmers into quantifiable parameters. The consensus model achieved an LOOCV average accuracy of 87%, a training set accuracy of 100%, and a test set accuracy of 78%. Through this approach, three structural parameters that significantly impact the hickory tree were identified: the number of branches, the total length of all branches, and the crown base height from the ground. These parameters were used to select trees with superior structural traits. Furthermore, a novel method based on distance metrics was developed to assess the structural similarity of trees. This research not only highlights the importance of incorporating tree structural characteristics into forest management practices but also demonstrates how modern technological tools can enhance the productivity and economic returns of hickory forests. Through this integration, both the sustainability and economic viability of hickory forests are improved. Full article

Traditional lectures in architectural engineering often fall short of effectively conveying practical applications. This study introduces a hybrid teaching approach that integrates structured field trips with traditional lectures based on Kolb’s four-step experiential learning cycle to address this. An experimental design was implemented to assess the impact of this method on achieving core Course Learning Outcomes (CLOs). Using SPSS, independent-sample t-tests, and one-way ANOVA, we compared CLO scores across intervention groups, student seniority levels, and field trip frequency. At the same time, multiple linear regression analyses were used to analyze the influence of students’ attitudes, prior experiences, and enjoyment on the CLO scores. CLO achievement was further validated through the Course Learning Outcome Analysis Tool (COAT). The findings reveal that students exposed to field trips performed significantly better, particularly freshmen and junior students, who showed greater knowledge gains than their senior peers. Additionally, a higher frequency of trips was associated with improved academic performance, and students’ positive attitudes, prior exposure, and enjoyment of field trips positively influenced their CLO outcomes. These results underscore the effectiveness of integrating experiential learning into architectural engineering education, offering a compelling supplement to conventional lectures and addressing the limitations of traditional instructional methods by fostering deeper, more meaningful student engagement and learning. Full article

This work integrates the circular economy (CE) into experiential learning in higher education, focusing on industrial and systems engineering. It addresses the need for suitable learning experiences and pedagogical strategies to enhance CE and sustainability education in active learning research. Accordingly, this study proposes integrating Kolb’s experiential learning cycle with the ADDIE model into an instructional design framework for reflective and active engagement in learning activities within realistic circular supply chain scenarios. The methodology demonstrates this framework through a case study of an undergraduate module for CE problem-solving, focusing on waste reduction within small and medium enterprises in Mexico City. Based on student surveys and achievement metrics, results show positive student feedback and evaluation results, meeting module targets. This work’s main contribution offers a framework for creating novel experiential learning cases and cultivating sustainability-related and disciplinary learning outcomes. It also recognises valuable links for citizenship commitment, problem-solving, community engagement, and CE education. However, this work acknowledges limitations in complex problem-solving difficulties, a resource-demanding nature, restricted transferability, and the limited evaluation of learning effectiveness. Future research will explore this work’s relevance across Kolb’s learning styles and diverse industries, focusing on student interest and motivation, and evaluating its impact on student outcomes in various educational contexts. Full article

Project-Based Learning (PBL), as an experiential methodology, improves learning outcomes and competencies (technical and non-technical) in engineering students. The Conceive–Design–Implement–Operate (CDIO) approach, adopted globally in engineering education, is based on PBL but expands the curriculum framework. Developed by MIT and the Royal Institute of Technology (KTH) in Sweden, CDIO focuses on the entire life cycle of engineering projects to train engineers so that they are capable of applying knowledge in real-life situations. Integrating CDIO and PBL into engineering curricula requires changes in teaching methodologies, teacher training and workspaces. The literature has explored their combination, highlighting shared values and mutual reinforcements. An assessment model is crucial for implementing PBL and evidencing improvement in student and course skills. Only through assessment and the cycle of continuous improvement will the adoption of PBL in engineering programs be advanced. A systematic review of the literature is proposed to identify effective methods in the evaluation of educational programs based on PBL, analyzing related research areas and evaluations according to the CDIO approach. Full article

The post-pandemic era shaped by COVID-19 has compelled universities to reimagine their learning experiences, adapting to new educational requirements and heightened expectations. However, this transformation brings forth novel pedagogical requirements and learning limitations. In today’s educational landscape, learners seek active and relevant learning experiences that seamlessly integrate interactivity, crisis awareness, and global challenges tied to a resilience and sustainability perspective. To address this imperative, our work introduces an experiential learning lab to articulate Kolb’s experiential learning cycle and authentic assessment principles. By incorporating real-world events as study scenarios, higher-order skill challenges, and self-regulated learning in alignment with reflective and practical activities, we aim to enhance students’ engagement and learning relevance. To illustrate practical implementation, we propose a case study methodology regarding an experiential learning lab for operations management education. Specifically, we delve into a case study centred around the Social Lab for Sustainable Logistics, involving a circular economy challenge as a learning experience during the post-COVID-19 pandemic. Preliminary results indicate that the experiential learning lab helped to create the learning experience in alignment with intended learning outcomes. However, further instances of such learning experiences are necessary to explore the contribution and applicability of the lab across diverse settings and disciplines. Full article

In the dynamic landscape of modern education, characterized by an increasingly active involvement of IT technologies in learning, the imperative to transfer to university students the skills necessary to integrate Artificial Intelligence (AI) into the process represents an important goal. This paper presents a novel framework for knowledge transfer, diverging from traditional programming language-centric approaches by integrating PSoC 6 microcontroller technology. This framework proposes a cyclical learning cycle encompassing theoretical fundamentals and practical experimentation, fostering AI literacy at the edge. Through a structured combination of theoretical instruction and hands-on experimentation, students develop proficiency in understanding and harnessing AI capabilities. Emphasizing critical thinking, problem-solving, and creativity, this approach equips students with the tools to navigate the complexities of real-world AI applications effectively. By leveraging PSoC 6 as an educational tool, a new generation of individuals is efficiently cultivated with essential AI skills. These individuals are adept at leveraging AI technologies to address societal challenges and drive innovation, thereby contributing to long-term sustainability initiatives. Specific strategies for experiential learning, curriculum recommendations, and the results of knowledge application are presented, aimed at preparing university students to excel in a future where AI will be omnipresent and indispensable. Full article