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Educational Technology Research and Development

, Volume 67, Issue 6, pp 1529–1545 | Cite as

Developing real life problem-solving skills through situational design: a pilot study

  • Lin ZhongEmail author
  • Xinhao Xu
Development Article
  • 119 Downloads

Abstract

Current problem-solving research has advanced our understanding of the problem-solving process but has provided little advice on how to teach problem-solving skills. In addition, literature reveals that individual difference is an essential issue in problem-solving skills instruction but has been rarely addressed in current research. Building upon information-processing theory, this article proposes an instructional design model, namely the situational design model, which serves as an approach to accommodate individual difference in problem-solving skills instruction. This design model was further examined with a pilot study in an introductory technology course and results showed a significant difference in students’ academic performance and problem-solving skills, especially the non-recurrent skills. The proposed situational design model contributes to research and practice by providing a novel lens to explore problem-solving skills and assisting in the design of instruction that aims to develop student’s expertise in solving real world problems.

Keywords

Problem-solving skills Individual differences Learning readiness Situational design 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Angeli, C. (2013). Examining the effects of field dependence–independence on learners’ problem-solving performance and interaction with a computer modeling tool: Implications for the design of joint cognitive systems. Computers & Education,62, 221–230.CrossRefGoogle Scholar
  2. Bulu, S. T., & Pedersen, S. (2012). Supporting problem-solving performance in a hypermedia learning environment: The role of students’ prior knowledge and metacognitive skills. Computers in Human Behavior,28(4), 1162–1169.CrossRefGoogle Scholar
  3. Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods. New York: Irvington.Google Scholar
  4. Delahaye, B. L., & Smith, H. E. (1995). The validity of the learning preference assessment. Adult Education Quarterly,45, 159–173.CrossRefGoogle Scholar
  5. Eseryel, D., Ge, X., Ifenthaler, D., & Law, V. (2011). Dynamic modeling as a cognitive regulation scaffold for developing complex problem-solving skills in an educational massively multiplayer online game environment. Journal of Educational Computing Research,45(3), 265–286.CrossRefGoogle Scholar
  6. Frensch, P. A., & Funke, J. (1995). Definitions, traditions, and a general framework for understanding complex problem solving. In P. A. Frensch & J. Funke (Eds.), Complex problem solving: The European perspective (pp. 3–26). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  7. Ge, X. (2013). Designing learning technologies to support self-regulation during ill-structured problem-solving processes. In R. Azevedo & V. Aleven (Eds.), International Handbook of Metacognition and Learning Technologies (pp. 213–228). Berlin: Springer.CrossRefGoogle Scholar
  8. Ge, X., & Land, S. M. (2004). A conceptual framework for scaffolding ill-structured problem-solving processes using question prompts and peer interactions. Educational Technology Research and Development,52(2), 5–22.CrossRefGoogle Scholar
  9. Ge, X., Law, V., & Huang, K. (2016). Detangling the interrelationships between self-regulation and ill-structured problem solving in problem-based learning. The Interdisciplinary Journal of Problem-Based Learning,10(2), 11.  https://doi.org/10.7771/1541-5015.1622.CrossRefGoogle Scholar
  10. Guglielmino, L. M. (1978). Development of the self-directed learning readiness scale. (Doctoral dissertation, University of Georgia, 1977). Dissertation. Abstracts International, 38, 6467.Google Scholar
  11. Hanover Research. (2016). McGraw-hill education 2016 workforce readiness survey. Retrieved from https://www.fastcompany.com/3059940/these-are-the-biggest-skills-that-new-graduates-lack.
  12. Hersey, P., Blanchard, K. H., & Johnson, D. E. (2012). Management of organizational behavior: Leading human resources (10th ed.). Upper Saddle, NJ: Prentice Hall.Google Scholar
  13. Jeotee, K. (2012). Reasoning skills, problem solving ability and academic ability: Implications for study programme and career choice in the context of higher education in Thailand (Doctoral dissertation, Durham University).Google Scholar
  14. Jonassen, D. H. (2007). Learning to solve complex, scientific problems. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  15. Jonassen, D. H., & Grabowski, B. (2012). Handbook of individual differences, learning, and instruction. New York: Routledge.Google Scholar
  16. Kalyuga, S., & Sweller, J. (2004). Measuring knowledge to optimize cognitive load factors during instruction. Journal of Educational Psychology,96(3), 558–568.CrossRefGoogle Scholar
  17. Kalyuga, S., & Sweller, J. (2005). Rapid dynamic assessment of expertise to improve the efficiency of adaptive e-learning. Educational Technology Research and Development,53(3), 83–93.CrossRefGoogle Scholar
  18. Kim, M. K. (2012). Theoretically grounded guidelines for assessing learning progress: Cognitive changes in ill-structured complex problem-solving contexts. Educational Technology Research and Development,60(4), 601–622.CrossRefGoogle Scholar
  19. Kim, M. C., & Hannafin, M. J. (2011). Scaffolding problem solving in technology-enhanced learning environments (TELEs): Bridging research and theory with practice. Computers & Education,56(2), 403–417.CrossRefGoogle Scholar
  20. Klegeris, K., Bahniwal, M., & Hurren, H. (2013). Improvement in generic problem-solving abilities of students by use of tutor-less problem-based learning in a large classroom setting. CBE Life Sciences Education,12, 70–73.CrossRefGoogle Scholar
  21. Lee, C. B. (2010). The interactions between problem solving and conceptual change: System dynamic modeling as a platform for learning. Computers & Education,55(3), 1145–1158.CrossRefGoogle Scholar
  22. Matemba, C. K., Awinja, J., & Otieno, K. O. (2014). Relationship between problem solving approaches and academic performance: A case of Kakamega municipality, Kenya. International Journal of Human Resource Studies,4(4), 10.CrossRefGoogle Scholar
  23. McCormick, N. J., Clark, L. M., & Raines, J. M. (2015). Engaging students in critical thinking and problem solving: A brief review of the literature. Journal of Studies in Education, 5(4), 100–113.CrossRefGoogle Scholar
  24. Muna, K., Sanjaya, R. E., Syahmani, & Bakti, I. (2017). Metacognitive skills and students’ motivation toward chemical equilibrium problem solving ability: A correlational study on students of XI IPA SMAN 2 Banjarmasin. In AIP Conference Proceedings (Vol. 1911, No. 1, p. 020008). AIP Publishing.Google Scholar
  25. Newell, A., & Rosenbloom, P. (1981). Mechanisms of skill acquisition and the law of practice. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 1–55). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  26. Nokes, T. J., Schunn, C. D., & Chi, M. T. H. (2010). Problem solving and human expertise. In International encyclopedia of education (pp. 265–272). Elsevier Ltd.  https://doi.org/10.1016/b978-0-08-044894-7.00486-3.CrossRefGoogle Scholar
  27. Raes, A., Schellens, T., Wever, B. D., & Vanderhoven, E. (2012). Scaffolding information problem solving in web-based collaborative inquiry learning. Computers & Education,59(1), 82–94.CrossRefGoogle Scholar
  28. Renkl, A., & Atkinson, R. K. (2007). Cognitive skill acquisition: Ordering instructional events in example-based learning. In F. E. Ritter, J. Nerb, E. Lehtinen, & T. O’Shea (Eds.), In order to learn: How ordering effect in machine learning illuminate human learning and vice versa. Oxford: Oxford University Press.Google Scholar
  29. Robertson, I. S. (2016). Problem solving: Perspectives from cognition and neuroscience (2nd ed.). Hove: Psychology Press.CrossRefGoogle Scholar
  30. Salden, R., Aleve, V., Schwonke, R., & Renkl, A. (2010). The expertise reversal effect and worked examples in tutored problem solving. Instructional Science,38, 289–307.CrossRefGoogle Scholar
  31. Säljö, R., & Wyndhamn, J. (1990). Problem-solving, academic performance and situated reasoning. A study of joint cognitive activity in the formal setting. British Journal of Educational Psychology,60(3), 245–254.CrossRefGoogle Scholar
  32. Shute, V., Wang, L., Greiff, S., Zhao, W., & Moore, G. (2016). Measuring problem solving skills via stealth assessment in an engaging video game. Computers in Human Behavior,63, 106–117.CrossRefGoogle Scholar
  33. Van Merriënboer, J. J. G. (1997). Training complex cognitive skills. Englewood Cliffs, NJ: Educational Technology Publications.Google Scholar
  34. Van Merriënboer, J. J. G. (2013). Perspectives on problem solving and instruction. Computers & Education,64(1), 153–160.CrossRefGoogle Scholar
  35. Van Merriënboer, J. J. G. (2016). How people learn. In N. Rushby & D. W. Surry (Eds.), The Wiley handbook of learning technology (pp. 15–34). West Sussex: Wiley.CrossRefGoogle Scholar
  36. Van Merriënboer, J. J. G., & Bruin, A. B. H. (2013). Research paradigms and perspectives on learning. In J. M. Spector, et al. (Eds.), Handbook of research on educational communications and technology (pp. 21–29). New York: Springer.Google Scholar
  37. Van Merriënboer, J. J. G., Clark, R. E., & Croock, M. B. M. (2002). Blueprints for complex learning: The 4C/ID-model. Educational Technology Research and Development,50(2), 39–64.CrossRefGoogle Scholar
  38. Yu, K., Fan, S., & Lin, K. (2014). Enhancing students’ problem-solving skills through context-based learning. International Journal of Science and Mathematics Education,13, 1377–1401.CrossRefGoogle Scholar

Copyright information

© Association for Educational Communications and Technology 2019

Authors and Affiliations

  1. 1.Department of Workforce Education and DevelopmentSouthern Illinois University CarbondaleCarbondaleUSA
  2. 2.School of Information Science & Learning TechnologiesUniversity of Missouri ColumbiaColumbiaUSA

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