Enhancing Business Students' Big Data Learning: Integrating Augmented Reality, Mind Mapping, and STEM Strategies
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| Title: | Enhancing Business Students' Big Data Learning: Integrating Augmented Reality, Mind Mapping, and STEM Strategies |
|---|---|
| Language: | English |
| Authors: | Yu-Hung Chiang (ORCID |
| Source: | Journal of Educational Computing Research. 2025 63(4):841-863. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 23 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research Tests/Questionnaires |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Business Education, College Students, Foreign Countries, Data, Integrated Activities, Teaching Methods, Cognitive Mapping, Educational Technology, Computer Simulation, Computer Uses in Education, STEM Education, Instructional Effectiveness, Blended Learning, Academic Achievement, Student Experience |
| Geographic Terms: | Taiwan |
| DOI: | 10.1177/07356331251323484 |
| ISSN: | 0735-6331 1541-4140 |
| Abstract: | As big data and artificial intelligence become integral to business decision-making, business management students require proficiency in data science and big data. However, the use of instructional technologies, such as augmented reality (AR) and mind mapping to teach these subjects is limited. This study introduces an innovative pedagogical model that integrates VAR materials and mind mapping with STEM teaching strategies to enhance learning outcomes and flow experiences among business management students. The researchers divided eighty-two participants into two experimental groups and a control group to assess (a) the impact of AR materials on learning big data expertise (b) the effectiveness of mind mapping combined with STEM strategies on programming skills and understanding big data concepts; and (c) the influence of a combined virtual and physical classroom model on learning achievement, learning experience, and flow experience. The results indicated that the implemented teaching model significantly enhanced learning achievement, experience, and immersion, with mind mapping and STEM strategies proving particularly effective. In conclusion, the integration of AR with Mind mapping and STEM strategies markedly improves learning performance, quality of learning, students' attitudes, interest, and the overall educational experience in big data education. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1470960 |
| Database: | ERIC |
| Abstract: | As big data and artificial intelligence become integral to business decision-making, business management students require proficiency in data science and big data. However, the use of instructional technologies, such as augmented reality (AR) and mind mapping to teach these subjects is limited. This study introduces an innovative pedagogical model that integrates VAR materials and mind mapping with STEM teaching strategies to enhance learning outcomes and flow experiences among business management students. The researchers divided eighty-two participants into two experimental groups and a control group to assess (a) the impact of AR materials on learning big data expertise (b) the effectiveness of mind mapping combined with STEM strategies on programming skills and understanding big data concepts; and (c) the influence of a combined virtual and physical classroom model on learning achievement, learning experience, and flow experience. The results indicated that the implemented teaching model significantly enhanced learning achievement, experience, and immersion, with mind mapping and STEM strategies proving particularly effective. In conclusion, the integration of AR with Mind mapping and STEM strategies markedly improves learning performance, quality of learning, students' attitudes, interest, and the overall educational experience in big data education. |
|---|---|
| ISSN: | 0735-6331 1541-4140 |
| DOI: | 10.1177/07356331251323484 |
