Research Article

Enhancing business students’ self-efficacy and learning outcomes: A multiple intelligences and technology approach

Sri Gunawan 1 * , Chich-Jen Shieh 2
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1 Universitas Airlangga, Surabaya, Jawa Timur, INDONESIA2 Hubei University of Automotive Technology, Hubei, CHINA* Corresponding Author
Contemporary Educational Technology, 15(4), October 2023, ep470, https://doi.org/10.30935/cedtech/13647
Published Online: 07 September 2023, Published: 01 October 2023
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ABSTRACT

This research investigates the effect of multiple intelligences (MIs) teaching strategy with technology-enriched environments on business administration students’ self-efficacy, confidence, and learning outcomes. The study involved 276 participants from a university’s business administration department, undergoing an international business course. A range of technology-based activities incorporating MI strategies was employed, exploring key topics such as globalization, corporate social responsibility, and market segmentation. Hypothesis testing revealed that high expectations and changes in viewpoints positively impacted self-concept, ability, and motivation, contributing to improved learning outcomes. The integration of technology in teaching facilitated these transformations, demonstrating how digital tools like virtual reality, interactive platforms, and online tutorials can enhance learning experiences. However, the effect on learning gain varied when viewpoints changed, indicating a need for further research into the differential impact of technology on learning outcomes. Despite some limitations, the study offers compelling evidence supporting the integration of MIs teaching strategy with technology-enriched environments in business administration education. Future studies should further explore the role of emerging technologies in this context.
Keywords: multiple intelligences teaching strategy, technology-enriched environments, technology education, motivation in learning, technology integration in teaching

CITATION (APA)

Gunawan, S., & Shieh, C.-J. (2023). Enhancing business students’ self-efficacy and learning outcomes: A multiple intelligences and technology approach. Contemporary Educational Technology, 15(4), ep470. https://doi.org/10.30935/cedtech/13647

REFERENCES

  1. Ahamad, A. N., Samsudin, M. A., Ismail, M. E., & Ahmad, N. J. (2021). Enhancing the achievement in physics’ motion concept through online multiple intelligence learning approach. EURASIA Journal of Mathematics, Science and Technology Education, 17(2), em1941. https://doi.org/10.29333/ejmste/9698
  2. Alghamdi, A., Karpinski, A. C., Lepp, A., & Barkley, J. (2020). Online and face-to-face classroom multitasking and academic performance: Moderated mediation with self-efficacy for self-regulated learning and gender. Computers in Human Behavior, 102, 214-222. https://doi.org/10.1016/j.chb.2019.08.018
  3. Allen, S. J. (2020). On the cutting edge or the chopping block? Fostering a digital mindset and tech literacy in business management education. Journal of Management Education, 44(3), 362-393. https://doi.org/10.1177/1052562920903077
  4. Armstrong, T. (2009). Multiple intelligences in the classroom. ASCD.
  5. Attaran, M., Stark, J., & Stotler, D. (2018). Opportunities and challenges for big data analytics in US higher education: A conceptual model for implementation. Industry and Higher Education, 32(3), 169-182. https://doi.org/10.1177/0950422218770937
  6. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215. https://doi.org/10.1037/0033-295X.84.2.191
  7. Barrington, E. (2004). Teaching to student diversity in higher education: How multiple intelligence theory can help. Teaching in Higher Education, 9(4), 421-434. https://doi.org/10.1080/1356251042000252363
  8. Bedenlier, S., Bond, M., Buntins, K., Zawacki-Richter, O., & Kerres, M. (2020). Facilitating student engagement through educational technology in higher education: A systematic review in the field of arts and humanities. Australasian Journal of Educational Technology, 36(4), 126-150. https://doi.org/10.14742/AJET.5477
  9. Chin, K.-Y., & Wang, C.-S. (2021). Effects of augmented reality technology in a mobile touring system on university students’ learning performance and interest. Australasian Journal of Educational Technology, 37(1), 27-42. https://doi.org/10.14742/ajet.5841
  10. Davis, K., Christodoulou, J., Seider, S., & Gardner, H. (2019). The theory of multiple intelligences. In R. J. Sternberg, & S. B. Kaufman (Eds.), The Cambridge handbook of intelligence (pp. 485-503). Cambridge University Press. https://doi.org/10.1017/9781108770422.028
  11. Dvoretskaya, E., Mishchenko, E. S., & Dvoretsky, D. (2020). Mobile technologies in education: Student expectations–Teaching reality gap. Advances in Intelligent Systems and Computing, 916, 946-957. https://doi.org/10.1007/978-3-030-11932-4_87
  12. Eid, M. I. M., & Al-Jabri, I. M. (2016). Social networking, knowledge sharing, and student learning: The case of university students. Computers and Education, 99, 14-27. https://doi.org/10.1016/j.compedu.2016.04.007
  13. Fadilloh, H., Rustaman, N. Y., & Sanjaya, Y. (2021). Designing a field trip: The role of multiple intelligence and scientific reasoning. Journal of Physics: Conference Series, 1806, 012149. https://doi.org/10.1088/1742-6596/1806/1/012149
  14. Fogarty, G., Cretchley, P., Harman, C., Ellerton, N., & Konki, N. (2001). Validation of a questionnaire to measure mathematics confidence, computer confidence, and attitudes towards the use of technology for learning mathematics. Mathematics Education Research Journal, 13(2), 154-160. https://doi.org/10.1007/BF03217104
  15. Gardner, H. E. (1983). Frames of mind: The theory of multiple intelligences. Basic Books.
  16. Ghasemy, M., Teeroovengadum, V., Becker, J. M., & Ringle, C. M. (2020). This fast car can move faster: A review of PLS-SEM application in higher education research. Higher Education, 80(6), 1121-1152. https://doi.org/10.1007/s10734-020-00534-1
  17. Gómez Sierra, C. J. (2020). Impact through digital marketing tools in social networks and web analytics in higher education institutions. IOP Conference Series: Materials Science and Engineering, 844, 012050. https://doi.org/10.1088/1757-899X/844/1/012050
  18. Green, Z. A. (2021). Multiple intelligences mediate generalized self-efficacy and academic achievement. Baltic Journal of Psychology, 20(1, 2), 34-51. https://doi.org/10.22364/bjp.20.01-02
  19. Gul, R., & Rafique, M. (2017). Teachers preferred approaches towards multiple intelligence teaching: Enhanced prospects for teaching strategies. Journal of Research and Reflections in Education, 2, 197-203.
  20. Gunning, A. M., & Mensah, F. M. (2011). Preservice elementary teachers’ development of self-efficacy and confidence to teach science: A case study. Journal of Science Teacher Education, 22(2), 171-185. https://doi.org/10.1007/s10972-010-9198-8
  21. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R. Springer. https://doi.org/10.1007/978-3-030-80519-7
  22. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
  23. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  24. Hassan, H. (2020). The effect of using a program based on multiple intelligences theory in teaching geometry on developing preparatory stage pupils’ habits of mind. Journal of Research in Curriculum Instruction and Educational Technology, 6(1), 149-174. https://doi.org/10.21608/jrciet.2020.67947
  25. Henseler, J., Hubona, G., & Ray, P. A. (2017). Partial least squares path modeling: Updated guidelines. In Partial least squares path modeling (pp. 19–39). Springer. https://doi.org/10.1007/978-3-319-64069-3_2
  26. Hernández-Barco, M., Cañada-Cañada, F., Corbacho-Cuello, I., & Sánchez-Martín, J. (2021). An exploratory study interrelating emotion, self-efficacy and multiple intelligence of prospective science teachers. Frontiers in Education, 6, 1-12. https://doi.org/10.3389/feduc.2021.604791
  27. Hwang, G. J., Sung, H. Y., Hung, C. M., & Huang, I. (2013). A learning style perspective to investigate the necessity of developing adaptive learning systems. Educational Technology and Society, 16(2), 188-197.
  28. Irgang dos Santos, L. F., Könzgen Huck, N., De Miranda, R. L., & Da Silveira, F. (2022). An overview about multiple intelligences: A comparative study with business administration students of two private universities in southern Brazil. Independent Journal of Management & Production, 13(1), 168-184. https://doi.org/10.14807/ijmp.v13i1.1552
  29. Kaur, D. P., Mantri, A., & Horan, B. (2020). Enhancing student motivation with use of augmented reality for interactive learning in engineering education. Procedia Computer Science, 172(2019), 881-885. https://doi.org/10.1016/j.procs.2020.05.127
  30. Latorre-Cosculluela, C., Suárez, C., Quiroga, S., Anzano-Oto, S., Lira-Rodríguez, E., & Salamanca-Villate, A. (2022). Facilitating self-efficacy in university students: An interactive approach with flipped classroom. Higher Education Research and Development, 41(5), 1603-1617. https://doi.org/10.1080/07294360.2021.1937067
  31. Luka, I. (2019). Creating a culture-based language learning course for developing adult learners’ 21st century skills. Journal of Education Culture and Society, 10(2), 151-169. https://doi.org/10.15503/jecs20192.151.169
  32. Mahasneh, A. M. (2013). The relationship between multiple intelligence and self-efficacy among sample of Hashemite University students. International Journal of Education and Research, 1(5), 1-12.
  33. Marino, M. P., & Crocco, M. S. (2020). The pre-service practicum experience and inquiry-oriented pedagogy: Evidence from student teachers׳ lesson planning. Journal of Social Studies Research, 44(1), 151-167. https://doi.org/10.1016/j.jssr.2019.02.001
  34. Müller, F. A., & Wulf, T. (2020). Technology-supported management education: A systematic review of antecedents of learning effectiveness. International Journal of Educational Technology in Higher Education, 17(1). https://doi.org/10.1186/s41239-020-00226-x
  35. Ng, D. K. E., & Stillman, G. (2007). Interdisciplinary learning : Development of mathematical confidence , value, and the interconnectedness of mathematics scales. Mathematics: Essential Research, Essential Practice, 2, 533-542.
  36. Nguyen, H. C. (2019). Motivation in learning English language: A case study at Vietnam National University, Hanoi. The European Journal of Educational Sciences, 06(01). https://doi.org/10.19044/ejes.v6no1a4
  37. Pate, L. P. (2016). Technology implementation: Impact on students’ perception and mindset. The International Journal of Information and Learning Technology, 33(2), 91-98. https://doi.org/10.1108/IJILT-10-2015-0033
  38. Perry, P. (2011). Concept analysis: Confidence/self-confidence. Nursing Forum, 46(4), 218-230. https://doi.org/10.1111/j.1744-6198.2011.00230.x
  39. Ray, S., & Danks, N. (2020). SEMinR. https://cran.r-project.org/web/packages/seminr/vignettes/SEMinR.html
  40. Sadler, I. (2013). The role of self-confidence in learning to teach in higher education. Innovations in Education and Teaching International, 50(2), 157-166. https://doi.org/10.1080/14703297.2012.760777
  41. Sandybayev, A. (2020). The impact of e-learning technologies on student’s motivation: Student centered interaction in business education. International Journal of Research in Tourism and Hospitality, 6(2), 16-24. https://doi.org/10.20431/2455-0043.0601002
  42. Schunk, D. H. (1991). Self-efficacy and academic motivation. Educational Psychologist, 26(3-4), 207-231. https://doi.org/10.1080/00461520.1991.9653133
  43. Shonfeld, M., Cotnam-Kappel, M., Judge, M., Ng, C. Y., Ntebutse, J. G., Williamson-Leadley, S., & Yildiz, M. N. (2021). Learning in digital environments: A model for cross-cultural alignment. Educational Technology Research and Development, 69(4), 2151-2170. https://doi.org/10.1007/s11423-021-09967-6
  44. V, A., & AHM, V. (2017). Multiple intelligence approach in the school curriculum: A review article. International Journal of Home Science, 3(3), 324-327.
  45. Vincent, A., Ross, D., & Williams, A. (2002). Using the multiple intelligences theory in international business. Journal of Teaching in International Business, 14(1), 45-63. https://doi.org/10.1300/J066v14n01_04
  46. Wekerle, C., Daumiller, M., & Kollar, I. (2022). Using digital technology to promote higher education learning: The importance of different learning activities and their relations to learning outcomes. Journal of Research on Technology in Education, 54(1), 1-17. https://doi.org/10.1080/15391523.2020.1799455
  47. Wen, L., Pan, J., Yi, K., & Cui, J. (2019). Research on electronic technology teaching based on multiple intelligence theory. Iwedss, 1181-1184.
  48. Yusoff, M. S. B. (2019). ABC of content validation and content validity index calculation. Education in Medicine Journal, 11(2), 49-54. https://doi.org/10.21315/eimj2019.11.2.6
  49. Zarei, A. A., & Taheri, S. (2013). Multiple intelligences as predictors of self-efficacy. The International Journal of Language Learning and Applied Linguistics World, 124-135.
  50. Zhang, Y. (2022). The effect of on educational technology on EFL learners’ self-efficacy. Frontiers in Psychology, 13, 1-8. https://doi.org/10.3389/fpsyg.2022.881301
  51. Zhou, Y. (2020). Research on teaching reform of business administration major in colleges and universities under “internet + education.” Lifelong Education, 9(7), 23. https://doi.org/10.18282/le.v9i7.1459