Emerging Technologies in Teaching and Learning to Solve Real-World Challenges: Perspectives, Challenges, and Future Directions

A special issue of Education Sciences (ISSN 2227-7102). This special issue belongs to the section "Technology Enhanced Education".

Deadline for manuscript submissions: closed (30 June 2025) | Viewed by 7552

Special Issue Editors


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Guest Editor
College of Education, Purdue University, 100 North University Street, West Lafayette, IN 47907, USA
Interests: extended reality (VR; AR; MR); artificial intelligence (AI); machine learning; educational technologies; immersive learning; instructional design; teaching and learning

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Guest Editor
Department of Curriculum Studies, College of Education, University of Saskatchewan, Saskatoon, SK S7N 0X1, Canada
Interests: immersive education; XR technologies; AI education; AI literacy; teacher education; environmental and sustainability education

Special Issue Information

Dear Colleagues,

Rapid technological advancements over the past decade have led to a profound transformation in how educators teach and students learn (Almufarreh and Arshad, 2023; Chaka, 2023; Sharrab et al., 2023; Van Mechelen et al., 2023).

These advancements and the technologies they have produced, e.g., generative AI, virtual reality (VR), and augmented reality (AR), have opened new avenues for immersive learning and student engagement and they are reshaping traditional approaches to teaching, training, and learning (Davis and McGrath, 2019; Lowell and Yan, 2024). They have also created new challenges (Adams et al., 2023; Almufarreh and Arshad, 2023; Grimus, 2020; Kalaif et al., 2023; Schaper et al., 2023; Stahl and Eke, 2024) and their adoption can impact theories and processes for teaching and learning, education systems, training programs, policies, and leadership (Cukurova and Luckin, 2018; Grimus, 2020; Fowler et al., 2019; Lowell and Yan, 2024; Pelletier et al., 2022).

As educators, trainers, researchers, and practitioners, we find ourselves at the intersection of innovation and pedagogy, with a need to explore how these emerging technologies are being utilized to enhance teaching and learning to address real problems while also considering how we can navigate needed changes and potential challenges.

This Special Issue explores the use of emerging technologies in various educational settings, such as K-12, higher education, organizational training, and informal learning environments, to address challenges related to teaching, learning, and performance. From AI, VR, and AR, to personalized learning platforms, gamification, and robotics, we seek to understand and provide evidence of the potential of these tools in fostering meaningful learning experiences and outcomes.

We ask how educators can harness these technologies to create effective, interactive, practical, inclusive, and/or immersive learning experiences and what challenges and ethical considerations arise as we integrate these emerging technologies into formal and informal learning spaces to address education and training needs.

A note on definitions: Although there are numerous definitions of emerging technologies (e.g., Litvinski and Litvinski, 2018; Small et al., 2014), we agree with Rotolo et al. (2023), in that emerging technologies have five attributes: “radical novelty, fast growth, coherence, prominent impact, and uncertainty and ambiguity” (p. 1839), while we also agree with Veletsianos’ (2010, 2016) pedagogical lens that in education, emerging technologies can also be viewed as  “…tools, concepts, innovations, and advancements utilized in diverse educational settings to serve varied education-related purposes” and as “evolving organisms that experience hype cycles, while at the same time being potentially disruptive, not yet fully understood, and not yet fully researched” (p. 3).

We seek contributions with insights into emerging technologies and pedagogy from diverse disciplines—computer science, psychology, education, and beyond—inviting empirical studies, theoretical frameworks, and practical case examples. We hope to provide knowledge, ignite discussions, and inspire innovation. 

References

Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligence, 4, 100131. https://doi.org/10.1016/j.caeai.2023.100131

Almufarreh, A., & Arshad, M. (2023). Promising emerging technologies for teaching and learning: Recent developments and future challenges. Sustainability, 15(8), 6917. https://doi.org/10.3390/su15086917

Chaka, C. (2023). Fourth industrial revolution—a review of applications, prospects, and challenges for artificial intelligence, robotics and blockchain in higher education. Research and Practice in Technology Enhanced Learning, 18(2), 2-39. https://doi.org/10.58459/rptel.2023.18002

Cukurova, M., & Luckin, R. (2018). Measuring the impact of emerging technologies in education: A pragmatic approach. In J. Voogt, G. Knezek, R. Christensen, & K. W. Lai (Eds.), Second Handbook of Information Technology in Primary and Secondary Education. Springer

Fowler, W. C., Ting, J. M., Meng, S., Li, L., & Tirrell, M. V. (2019). Integrating systems thinking into teaching emerging technologies. Journal of Chemistry Education, 96(2), 2805–2813. https://doi.org/10.1021/acs.jchemed.9b00280

Grimus, M. (2020). Emerging technologies: Impacting learning, pedagogy and curriculum development. In S. Yu, M. Ally, & A. Tsinakos (Eds.), Emerging Technologies and Pedagogies in the Curriculum. Bridging Human and Machine: Future Education with Intelligence (pp. 127–151). Springer.

Khlaif, Z. N., Sanmugam, M., Joma, A. I., Odeh, A., & Barham, K. (2023). Factors influencing teacher’s technostress experienced in using emerging technology: A qualitative study. Technology, Knowledge and Learning, 28(2), 865-899.

Litvinski, O., & Litvinski, O. (2018). Emerging technology: Toward a conceptual definition. International Journal of Trade, Economics and Finance, 9(6), 256-262.

Lowell, V. L., & Yan, W. (2024). The design of immersive virtual reality (IVR) learning using systems thinking. TechTrends 68(1), 149-160. https://doi.org/10.1007/s11528-023-00922-1

Pelletier, K., McCormack, M., Reeves, J., Robert, J., Arbino, A., Al-Freih, M., Dickson-Deane, C., Guevara, C., Koster, L., Sánchez-Mendiola, M., Bessette, L. S., & Stine, J. (2022). 2022 EDUCAUSE Horizon Report, Teaching and Learning Edition (pp. 1-58). EDUCAUSE. Retrieved April 2, 2024, from https://www.learntechlib.org/p/221033/

Rotolo, D., Hicks, D., & Martin, B. R. (2015). What is an emerging technology? Research Policy, 44(10), 1827-1843. https://doi.org/10.1016/j.respol.2015.06.006

Schaper, M. M., Smith, R. C., Van Mechelen, M., Tamashiro, M. A., & Iversen, O. S. (2023). Co-designing sustainable practices for emerging technologies education. International Journal of Technology and Design Education, 1-23.

Sharrab, Y., Almutiri, N. T., Tarawneh, M., Alzyoud, F., Al-Ghuwairi, A. R., & Al-Fraihat, D. (2023). Toward smart and immersive classroom based on AI, VR, and 6G. International Journal of Emerging Technologies in Learning, 18(2), 4-16. https://doi.org/10.3991/ijet.v18i02.35997

Small, H., Boyack, K. W., & Klavans, R. (2014). Identifying emerging topics in science and technology. Research Policy 48(8), 1450–1467, http://dx.doi.org/10.1016/j.respol.2014.02.005

Stahl, B. C., & Eke, D. (2024). The ethics of ChatGPT–Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700.

Van Mechelen, M., Smith, R. C., Schaper, M. M., Tamashiro, M., Bilstrup, K. E., Lunding, M., ... & Sejer Iversen, O. (2023). Emerging technologies in K–12 education: A future HCI research agenda. ACM Transactions on Computer-Human Interaction, 30(3), 1-40.

Veletsianos, G. (2016). The defining characteristics of emerging technologies and emerging practices in digital education. Emergence And Innovation in Digital Learning: Foundations and Applications, 3-16.

Veletsianos, G. (Ed.) (2010). Emerging technologies in distance education. Issues in Distance Education. AU Press. https://doi.org/10.15215/aupress/9781897425763.01

Prof. Dr. Victoria Lowell
Dr. Paula MacDowell
Guest Editors

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Keywords

  • emerging technologies
  • technology-enhanced learning
  • educational technology
  • educational innovation
  • digital pedagogy
  • digital literacy
  • immersive learning

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Published Papers (4 papers)

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Research

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26 pages, 1178 KiB  
Article
Towards Dynamic Learner State: Orchestrating AI Agents and Workplace Performance via the Model Context Protocol
by Mohan Yang, Nolan Lovett, Belle Li and Zhen Hou
Educ. Sci. 2025, 15(8), 1004; https://doi.org/10.3390/educsci15081004 - 6 Aug 2025
Viewed by 342
Abstract
Current learning and development approaches often struggle to capture dynamic individual capabilities, particularly the skills they acquire informally every day on the job. This dynamic creates a significant gap between what traditional models think people know and their actual performance, leading to an [...] Read more.
Current learning and development approaches often struggle to capture dynamic individual capabilities, particularly the skills they acquire informally every day on the job. This dynamic creates a significant gap between what traditional models think people know and their actual performance, leading to an incomplete and often outdated understanding of how ready the workforce truly is, which can hinder organizational adaptability in rapidly evolving environments. This paper proposes a novel dynamic learner-state ecosystem—an AI-driven solution designed to bridge this gap. Our approach leverages specialized AI agents, orchestrated via the Model Context Protocol (MCP), to continuously track and evolve an individual’s multi-dimensional state (e.g., mastery, confidence, context, and decay). The seamless integration of in-workflow performance data will transform daily work activities into granular and actionable data points through AI-powered dynamic xAPI generation into Learning Record Stores (LRSs). This system enables continuous, authentic performance-based assessment, precise skill gap identification, and highly personalized interventions. The significance of this ecosystem lies in its ability to provide a real-time understanding of everyone’s capabilities, enabling more accurate workforce planning for the future and cultivating a workforce that is continuously learning and adapting. It ultimately helps to transform learning from a disconnected, occasional event into an integrated and responsive part of everyday work. Full article
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23 pages, 1650 KiB  
Article
Generative AI-Enhanced Virtual Reality Simulation for Pre-Service Teacher Education: A Mixed-Methods Analysis of Usability and Instructional Utility for Course Integration
by Sumin Hong, Jewoong Moon, Taeyeon Eom, Idowu David Awoyemi and Juno Hwang
Educ. Sci. 2025, 15(8), 997; https://doi.org/10.3390/educsci15080997 - 5 Aug 2025
Viewed by 367
Abstract
Teacher education faces persistent challenges, including limited access to authentic field experiences and a disconnect between theoretical instruction and classroom practice. While virtual reality (VR) simulations offer an alternative, most are constrained by inflexible design and lack scalability, failing to mirror the complexity [...] Read more.
Teacher education faces persistent challenges, including limited access to authentic field experiences and a disconnect between theoretical instruction and classroom practice. While virtual reality (VR) simulations offer an alternative, most are constrained by inflexible design and lack scalability, failing to mirror the complexity of real teaching environments. This study introduces TeacherGen@i, a generative AI (GenAI)-enhanced VR simulation designed to provide pre-service teachers with immersive, adaptive teaching practice through realistic GenAI agents. Using an explanatory case study with a mixed-methods approach, the study examines the simulation’s usability, design challenges, and instructional utility within a university-based teacher preparation course. Data sources included usability surveys and reflective journals, analyzed through thematic coding and computational linguistic analysis using LIWC. Findings suggest that TeacherGen@i facilitates meaningful development of teaching competencies such as instructional decision-making, classroom communication, and student engagement, while also identifying notable design limitations related to cognitive load, user interface design, and instructional scaffolding. This exploratory research offers preliminary insights into the integration of generative AI in teacher simulations and its potential to support responsive and scalable simulation-based learning environments. Full article
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21 pages, 297 KiB  
Article
Peer Feedback, English Public Speaking Self-Efficacy, and Performance in Facebook and Brightspace
by Lucia Urena-Rodriguez, Victoria L. Lowell and Weijian Yan
Educ. Sci. 2025, 15(7), 879; https://doi.org/10.3390/educsci15070879 - 9 Jul 2025
Viewed by 1647
Abstract
Social media applications (SMAs) stand at the forefront of emerging technologies in language education due to their transformative potential to enhance English speaking skills. Unlike traditional tools, SMAs leverage features like real-time communication, multimedia integration, and global connectivity, fostering authentic, meaningful interactions in [...] Read more.
Social media applications (SMAs) stand at the forefront of emerging technologies in language education due to their transformative potential to enhance English speaking skills. Unlike traditional tools, SMAs leverage features like real-time communication, multimedia integration, and global connectivity, fostering authentic, meaningful interactions in socially engaging environments. Although learning management systems (LMSs) such as Brightspace have been predominantly used to conduct English language learning activities, including peer feedback, SMAs like Facebook offer unique affordances that may further promote student engagement and confidence. Developing public speaking skills is critical for effective communication in English language education; however, many students struggle with self-efficacy, speaking anxiety, and providing meaningful feedback to peers. Given the potential benefits of SMAs, this study explored their comparative impact on three dimensions of English language learning: English public speaking self-efficacy, peer feedback self-efficacy, and English speaking performance. This quasi-experimental study used a pretest–posttest design with undergraduate students (n = 15) at a large Midwestern university in the United States. Independent sample t-tests were conducted to compare outcomes between the Facebook and Brightspace groups. The results revealed that both SMAs and LMSs were equally effective platforms for peer feedback activities, with no significant differences found between groups across the three targeted areas of learning. Full article

Other

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20 pages, 459 KiB  
Systematic Review
Business Simulation Games for the Development of Decision Making: Systematic Review
by Alexander Velez and Rebeca Kerstin Alonso
Educ. Sci. 2025, 15(2), 168; https://doi.org/10.3390/educsci15020168 - 31 Jan 2025
Viewed by 3675
Abstract
Business simulation games (BSGs) are considered a useful instructional tool to be implemented in the classroom, especially in light of new trends in education. The key components of the paradigm are BSGs and Decision Making (DM), as the latter is often essential to [...] Read more.
Business simulation games (BSGs) are considered a useful instructional tool to be implemented in the classroom, especially in light of new trends in education. The key components of the paradigm are BSGs and Decision Making (DM), as the latter is often essential to a high-quality education. Thus, over the last 10 years, efforts to find possible methods to enhance BSG learning experiences for the development of DM in higher education have increased. The goals of this article were to examine the effect of BSGs on students’ DM at university, and to identify the elements that can be developed in the BSG learning experience to promote DM. Following PRISMA criteria, a systematic review was carried out using Scopus, Web of Science, and ProQuest. A total of 13 of the 2897 papers that were first discovered underwent a comprehensive review, with all conclusions and findings subjected to analysis. Following implementation, the majority of the BSG learning experiences enhanced DM results. In summary, a few key elements have been highlighted that must be followed to ensure the BSG learning experience helps students foster their DM. Full article
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