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Kefalis, C.; Skordoulis, C.; Drigas, A. Digital Simulations in STEM Education: Insights from Recent Empirical Studies, a Systematic Review. Encyclopedia. Available online: https://encyclopedia.pub/entry/57699 (accessed on 14 February 2025).
Kefalis C, Skordoulis C, Drigas A. Digital Simulations in STEM Education: Insights from Recent Empirical Studies, a Systematic Review. Encyclopedia. Available at: https://encyclopedia.pub/entry/57699. Accessed February 14, 2025.
Kefalis, Chrysovalantis, Constantine Skordoulis, Athanasios Drigas. "Digital Simulations in STEM Education: Insights from Recent Empirical Studies, a Systematic Review" Encyclopedia, https://encyclopedia.pub/entry/57699 (accessed February 14, 2025).
Kefalis, C., Skordoulis, C., & Drigas, A. (2025, January 15). Digital Simulations in STEM Education: Insights from Recent Empirical Studies, a Systematic Review. In Encyclopedia. https://encyclopedia.pub/entry/57699
Kefalis, Chrysovalantis, et al. "Digital Simulations in STEM Education: Insights from Recent Empirical Studies, a Systematic Review." Encyclopedia. Web. 15 January, 2025.
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Digital Simulations in STEM Education: Insights from Recent Empirical Studies, a Systematic Review

This study explores the use of digital simulations in STEM education, addressing the gap in systematic reviews synthesizing recent advancements and their implications for teaching and learning by focusing on their impact on learning outcomes and student engagement across general and special education settings. The review includes 31 peer-reviewed empirical studies published in the last five years, sourced from ERIC, Scopus, and Web of Science, and adheres to the PRISMA methodology to ensure transparency and rigor. The findings reveal that interactive simulations are the most widely used type of digital tool, accounting for 25 of the 31 studies, followed by game-based simulations and virtual labs. Quasi-experimental designs dominate the research landscape, often employing pre- and post-tests to evaluate intervention effectiveness. While inquiry-based learning emerges as the most frequently implemented instructional strategy, hybrid and simulation-based approaches also feature prominently. Despite the evident benefits of digital simulations in enhancing conceptual understanding, engagement, and problem-solving skills, research gaps remain, particularly regarding their application in primary and special education contexts. This review underscores the need for diverse research methodologies and broader population studies to maximize the potential of digital simulations in STEM education.

STEM education digital simulations inquiry-based learning learning outcomes student engagement
The integration of digital tools and applications in education has revolutionized learning experiences across general and special education contexts. Research has highlighted the significant role of mobile applications in supporting students with specific needs, such as those on the autism spectrum in secondary education, by enhancing their learning processes and engagement levels [1]. Similarly, mental imagery applications have demonstrated potential for improving learning disabilities and mental health, showcasing the transformative impact of technology on education [2]. Innovations in speech and language therapy through ICTs have also opened up new avenues for intervention, providing tailored solutions for diverse learner populations [3]. Furthermore, STEM education, coupled with metacognitive strategies, has emerged as a critical area for supporting students with specific learning disabilities. Online learning tools for coding and robotics are another example of how digital technologies empower learners by enabling access to practical STEM-related activities, fostering both engagement and skill development [4][5][6].
In recent years, educational simulations have become increasingly prominent in STEM education, providing dynamic, interactive environments that support experiential learning. Digital simulations, encompassing virtual labs, interactive models, and AR-based applications, are computer-based tools designed to replicate real-world processes or systems. These simulations enable learners to interact with and manipulate variables within a virtual setting, facilitating experiential learning and a deeper understanding of scientific concepts [7][8]. Digital simulations, including virtual labs and interactive models, enable students to explore complex scientific phenomena, practice problem-solving skills, and deepen their understanding of core concepts in ways that traditional methods may not facilitate. The effectiveness of these tools in fostering engagement and enhancing learning outcomes has sparked substantial interest among educators and researchers alike, particularly for both general and special education contexts.
Despite the increasing use of digital simulations in STEM education, there is no systematic review that provides a comprehensive understanding of recent advancements and synthesizes findings across different scientific disciplines. This study fills this gap by offering an integrated perspective on modern approaches and the educational impacts of simulations. Previous reviews on AR in science education [9] have explored specific aspects of digital simulations. However, these studies focused narrowly on AR applications, leaving a broader examination of diverse simulation tools across STEM disciplines unaddressed.
However, despite the growing body of literature, there remains a need for a comprehensive understanding of how digital simulations contribute to measurable educational outcomes across various student populations and educational levels. This systematic review seeks to analyze recent empirical studies that examine the impact of digital simulations on learning outcomes and student engagement in STEM education, thereby offering insights into best practices and highlighting areas for further investigation.

Research Questions

  • What are the predominant research designs employed in studies examining the effectiveness of digital simulations in STEM education?
  • What types of digital simulations are most commonly employed in STEM education?
  • What intervention categories are most commonly implemented in studies utilizing digital simulations in STEM education?
These questions will guide a systematic exploration of recent empirical evidence, focusing on the educational implications and methodological rigor of digital simulations within the STEM domain.

References

  1. Stathopoulou, A.; Karabatzaki, Z.; Tsiros, D.; Katsantoni, S.; Drigas, A. Mobile apps the educational solution for autistic students in secondary education. Int. J. Interact. Mob. Technol. 2019, 13, 89–101.
  2. Drigas, A.; Dede, D.E.; Dedes, S. Mobile and other applications for mental imagery to improve learning disabilities and mental health. Int. J. Comput. Sci. Issues 2020, 17, 18–23.
  3. Drigas, A.; Petrova, A. ICTs in speech and language therapy. Int. J. Eng. Pedagog. 2014, 4, 49–54.
  4. Kefalis, C.; Skordoulis, C.; Drigas, A. The Role of 3D Printing in Science, Technology, Engineering, and Mathematics (STEM) Education in General and Special Schools. Int. J. Online Biomed. Eng. 2024, 20, 4–18.
  5. Drigas, A.; Kefalis, C. STREAMING: A Comprehensive Approach to Inclusive STEM Education. Sci. Electron. Arch. 2024, 17, 1–7.
  6. Lytra, N.; Drigas, A. STEAM education-metacognition—Specific learning disabilities. Sci. Electron. Arch. 2021, 14, 41–48.
  7. Gui, Y.; Cai, Z.; Yang, Y.; Kong, L.; Fan, X.; Tai, R.H. Effectiveness of digital educational game and game design in STEM learning: A meta-analytic review. Int. J. STEM Educ. 2023, 10, 1–25.
  8. Clark, D.; Nelson, B.; Sengupta, P.; D’Angelo, C. Rethinking science learning through digital games and simulations: Genres, examples, and evidence. In Learning Science: Computer Games, Simulations, and Education Workshop; The National Academies Press: Washington, DC, USA, 2009.
  9. Irwanto, I.; Dianawati, R.; Lukman, I.R. Trends of Augmented Reality Applications in Science Education: A Systematic Review from 2007 to 2022. Int. J. Emerg. Technol. Learn. 2022, 17, 157–175.
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