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Opportunities for educational innovations in authentic project-based learning: understanding instructor perceived challenges to design for adoption

  • Daniel G. Rees LewisEmail author
  • Elizabeth M. Gerber
  • Spencer E. Carlson
  • Matthew W. Easterday
Development Article

Abstract

Authentic project-based learning (APBL) is a highly effective way for instructors to help students learn disciplinary skills, modes of thinking, and collaborative practices by creating solutions to real-world problems for real users and clients. While educational technology innovations can bolster APBL by making a promising but challenging pedagogy more effective, as with many areas of education instructor adoption is slow. Diffusion of innovations theory predicts that instructors will adopt and maintain their use of innovations if innovations are perceived to, and then do, address their challenges. To guide design of future APBL technologies, we interviewed 47 university APBL instructors about their most significant challenges and inductively analyzed the resulting interview transcripts. APBL instructors reported interrelated challenges of: (a) scoping, sourcing challenges and balancing the needs of the program, students, and clients; (b) curriculum preparation, making the curriculum flexible enough for shifting project problems and codify standards to help students understand how to do quality work; (c) providing assistance to teams, including monitoring, and delivering assistance; and (d) coordinating a range of stakeholders involved in assisting teams, including co-instructors, clients, and students. To support instructor adoption in APBL, educational technology innovators might communicate existing technology, or create technological innovations, that provide: (a) scoping tools for sourcing projects, and forming teams; (b) authoring tools for sharing and remixing of curricular materials; (c) project management tools for team management and monitoring; and (d) coordination software to manage all APBL stakeholders.

Keywords

Project-based learning Diffusion of innovations Innovation Qualitative Interview 

Notes

Acknowledgements

We thank the members of the Delta Lab, Simone Ispa-Landa, Bruce Sherin, and Christopher Riesbeck for their feedback on data collection and analysis.

Funding

This work was funded by the National Science Foundation (US) Grant Nos. IIS-1530833 and IIS-1320693.

Compliance with ethical standards

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

References

  1. Archer, K., Savage, R., Sanghera-Sidhu, S., Wood, E., Gottardo, A., & Chen, V. (2014). Examining the effectiveness of technology use in classrooms: A tertiary meta-analysis. Computers & Education, 78, 140–149.Google Scholar
  2. Beyer, H., & Holtzblatt, K. (1998). Contextual design: Defining customer-centered systems. San Franscisco, CA: Morgan Kaufmann.Google Scholar
  3. Biernacki, P., & Waldorf, D. (1981). Snowball sampling: Problems and techniques of chain referral sampling. Sociological Methods & Research, 10(2), 141–163.Google Scholar
  4. Blank, S., & Dorf, B. (2012). The startup owner’s manual. Pescadero, CA: K&S Ranch Press.Google Scholar
  5. Blumenfeld, P., Fishman, B. J., Krajcik, J., Marx, R. W., & Soloway, E. (2000). Creating usable innovations in systemic reform: Scaling up technology-embedded project-based science in urban schools. Educational Psychologist, 35(3), 149–164.Google Scholar
  6. Boling, E., Schwier, R. A., Gray, C. M., Smith, K. M., & Campbell, K. (Eds.). (2016). Studio teaching in higher education: Selected design cases. Abingdon: Routledge.Google Scholar
  7. Borrego, M., Froyd, J. E., & Hall, T. S. (2010). Diffusion of engineering education innovations: A survey of awareness and adoption rates in US engineering departments. Journal of Engineering Education, 99(3), 185–207.Google Scholar
  8. Carlson, S.E., Maliakal, L.V., Rees Lewis, D.G., Gorson, J., Gerber, E.M., & Easterday, M.W. (2018a). Defining and assessing risk analysis: The key to strategic iteration in real-world problem solving. In Proceedings of the International Conference of the Learning Sciences (ICLS). London: ICLS.Google Scholar
  9. Carlson, S. E., Rees Lewis, D. G., Gerber, E. M., & Easterday, M. W. (2018b). Challenges of peer instruction in an undergraduate student-led learning community: Bi-directional diffusion as a crucial instructional process. Instructional Science, 46, 405–433.Google Scholar
  10. Chandra Kruse, L., & Nickerson, J. V. (2018). Portraying design essence. Proceedings of the 51st Hawaii International Conference on System Sciences (HICSS 2018). Waikoloa Village, Hawaii, USA: AIS.Google Scholar
  11. Chang, M. L., & Downey, A. B. (2008, June). A semi-automatic approach for project assignment in a capstone course. In Proceedings of ASEE annual conference and exposition, Pittsburgh, PA. Retrieved from https://peer.asee.org/4116.
  12. Cheung, A. C., & Slavin, R. E. (2013). The effectiveness of educational technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis. Educational research review, 9, 88–113.Google Scholar
  13. Collins, A. (1996). Design issues for learning environments. In S. Vosniadou, E. De Corte, R. Glaser, & H. Mandl (Eds.), International perspectives on the design of technology-supported learning environments (pp. 347–361). New York, NY: Routledge.Google Scholar
  14. Collins, A., & Kapur, M. (2014). Cognitive apprenticeship. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 109–127). Cambridge: Cambridge University Press.Google Scholar
  15. Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571.Google Scholar
  16. de Koster, S., Volman, M., & Kuiper, E. (2017). Concept-guided development of technology in ‘traditional’ and ‘innovative’ schools: Quantitative and qualitative differences in technology integration. Educational Technology Research and Development, 65(5), 1325–1344.Google Scholar
  17. Dunlap, J. C. (2005). Problem-based learning and self-efficacy: How a capstone course prepares students for a profession. Educational Technology Research and Development, 53(1), 65–83.Google Scholar
  18. Dutson, A. J., Todd, R. H., Magleby, S. P., & Sorensen, C. D. (1997). A review of literature on teaching engineering design through project-oriented capstone courses. Journal of Engineering Education, 86(1), 17–28.  https://doi.org/10.1002/j.2168-9830.1997.tb00260.x.Google Scholar
  19. Dym, C. L., Agogino, A. M., Eris, O., Frey, D. D., & Leifer, L. J. (2005). Engineering design thinking, teaching, and learning. Journal of Engineering Education, 94(1), 103–120.  https://doi.org/10.1002/j.2168-9830.2005.tb00832.x.Google Scholar
  20. Easterday, M. W., Rees Lewis, D. G., & Gerber, E. M. (2016). The logic of the theoretical and practical products of design research. Australasian Journal of Educational Technology.  https://doi.org/10.14742/ajet.2464.Google Scholar
  21. Easterday, M. W., Rees Lewis, D. G., & Gerber, E. M. (2018). The logic of design research. Learning: Research and Practice, 4(2), 131–160.Google Scholar
  22. Ertmer, P. A., & Simons, K. D. (2006). Jumping the PBL implementation hurdle: Supporting the efforts of K–12 teachers. Interdisciplinary Journal of Problem-based Learning, 1(1), 5.Google Scholar
  23. Frank, M., & Barzilai, A. (2004). Integrating alternative assessment in a project-based learning course for pre-service science and technology teachers. Assessment & Evaluation in Higher Education, 29(1), 41–61.Google Scholar
  24. Gerber, E. (2014). Design for America: Organizing for civic innovation. Interactions, 21(2), 42–47.Google Scholar
  25. Goel, V., & Pirolli, P. (1992). The structure of design problem spaces. Cognitive Science, 16(3), 395–429.Google Scholar
  26. Hadim, H. A., & Esche, S. K. (2002, November). Enhancing the engineering curriculum through project-based learning. In Proceedings of 32nd annual ASEE/IEEE frontiers in education conference. Boston, MA, USA. Champaign, IL, USA: Stipes Publishing..Google Scholar
  27. Hoit, M., & Ohland, M. (1998). The impact of a discipline-based introduction to engineering course on improving retention. Journal of Engineering Education, 87(1), 79–85.  https://doi.org/10.1002/j.2168-9830.1998.tb00325.x.Google Scholar
  28. ISTE. (2002). National education technology standards for students. Eugene: ISTE.Google Scholar
  29. Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25–39.Google Scholar
  30. Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2015). The NMC Horizon Report: 2015 Higher Education. Austin, TX: New Media Consortium.Google Scholar
  31. Jonassen, D. H., & Hung, W. (2015). All problems are not equal: Implications for problem-based learning. In A. Walker & H. Leary (Eds.), Essential readings in problem-based learning (pp. 17–41). West Lafayette: Purdue University Press.Google Scholar
  32. Jonassen, D., Strobel, J., & Lee, C. B. (2006). Everyday problem solving in engineering: Lessons for engineering educators. Journal of Engineering Education, 95(2), 139–151.Google Scholar
  33. Kolodner, J., Owensby, J., & Guzdial, M. (2004). Case-based learning aids. In D. H. Jonassen (Ed.), Handbook of research on educational communications and technology: A project of the Association for Educational Communications and Technology (2nd ed., pp. 829–861). New York: L. Erlbaum.Google Scholar
  34. Krajcik, J. S., & Czerniak, C. M. (2013). Teaching science in elementary and middle school classrooms: A project-based approach. London: Taylor and Francis.Google Scholar
  35. Kraut, R. E., & Resnick, P. (2011). Encouraging contribution to online communities. In R. E. Kraut & P. Resnick (Eds.), Building successful online communities: Evidence-based social design (pp. 21–76). Boston, MA: MIT Press.Google Scholar
  36. Lepper, M. R., & Malone, T. W. (1987). Intrinsic motivation and instructional effectiveness in computer-based education. In R. E. Snow & M. J. Farr (Eds.), Aptitude, learning, and instruction: III. Conative and affective process analyses (pp. 255–296). Hillsdale, NJ: Lawrence Erlbaum Associates, In.Google Scholar
  37. Lincoln, Y. S., & Guba, E. G. (1985). Establishing trustworthiness. Naturalistic inquiry (pp. 289–331). London: Sage Publications.Google Scholar
  38. Loughry, M. L., Ohland, M. W., & Woehr, D. J. (2014). Assessing teamwork skills for assurance of learning using CATME team tools. Journal of Marketing Education, 36(1), 5–19.  https://doi.org/10.1177/0273475313499023.Google Scholar
  39. Mandala, M., Schunn, C., Dow, S., Goldberg, M., & Pearlman, J. (2018). Uncovering the practices, challenges, and incentives for engineering design faculty. International Journal of Engineering Education, 34(4), 1314–1324.Google Scholar
  40. Matusovich, H. M., Paretti, M. C., McNair, L. D., & Hixson, C. (2014). Faculty motivation: A gateway to transforming engineering education. Journal of Engineering Education, 103(2), 302–330.Google Scholar
  41. McCormick, A. C., & Zhao, C. M. (2005). Rethinking and reframing the Carnegie classification. Change: The Magazine of Higher Learning, 37(5), 51-57.Google Scholar
  42. Miles, M. B., Huberman, A. M., & Saldana, J. (2013). Qualitative data analysis. London: Sage.Google Scholar
  43. Niederhauser, D. S., & Stoddart, T. (2001). Teachers’ instructional perspectives and use of educational software. Teaching and Teacher Education, 17(1), 15–31.Google Scholar
  44. Olds, B. M., & Miller, R. L. (2004). The effect of a first-year integrated engineering curriculum on graduation rates and student satisfaction: A longitudinal study. Journal of Engineering Education, 93(1), 23.  https://doi.org/10.1002/j.2168-9830.2004.tb00785.x.Google Scholar
  45. Panadero, E., & Järvelä, S. (2015). Socially shared regulation of learning: A review. European Psychologist, 20(3), 190–203.Google Scholar
  46. Penuel, W. R., & Spillane, J. P. (2014). Learning sciences and policy design and implementation: Key concepts and tools for collaborative engagement. In K. Sawyer (Ed.), The cambridge handbook of the learning sciences (pp. 649–667). New York, NY: Cambridge University Press.Google Scholar
  47. Prince, M. J., & Felder, R. M. (2006). Inductive teaching and learning methods: Definitions, comparisons, and research bases. Journal of Engineering Education, 95(2), 123–138.  https://doi.org/10.1002/j.2168-9830.2006.tb00884.x.Google Scholar
  48. Rees Lewis, D. G., Easterday, M. W., Harburg, E., Gerber, E. M., & Riesbeck, C. K. (2017). Overcoming barriers between volunteer professionals advising project-based learning teams with regulation tools. British Journal of Educational Technology.  https://doi.org/10.1111/bjet.12550.Google Scholar
  49. Rees Lewis D. G., Gerber E. M., & Easterday. M. W. (2015) Supporting project scoping: The Scoping wheel. In Poster presented at Harvey Mudd Design Workshop IX “Design Thinking in Design Education”. Claremont, CA, US.Google Scholar
  50. Rees Lewis, D.G., Gorson, J., Maliakal, L.V., Carlson, S.E., Riesbeck, C.K., Gerber, E.M., & Easterday, M.W. (2018). Planning to Iterate: Supporting iterative practices for real-world ill-structured problem-solving. In Proceedings of the international conference of the learning sciences (ICLS). London, UK: ICLS.Google Scholar
  51. Rees Lewis, D., Harburg, E., Gerber, E.M., Easterday, M. (2015). Building help-seeking tools for novice designers. In Proceedings of the 2015 ACM SIGCHI conference on creativity & cognition 2015 (pp. 43–52). New York, NY: ACM.Google Scholar
  52. Reifenberg, S., & Long, S. (2017). Negotiating the client-based capstone experience. International Journal of Teaching and Learning in Higher Education, 29(3), 580–588.Google Scholar
  53. Reiser, B. J. (2004). Scaffolding complex learning: The mechanisms of structuring and problematizing student work. The Journal of the Learning Sciences, 13(3), 273–304.Google Scholar
  54. Rogers, E. M. (2003). Diffusion of innovations. New York, NY: Simon and Schuster.Google Scholar
  55. Sadaf, A., Newby, T. J., & Ertmer, P. A. (2016). An investigation of the factors that influence preservice teachers’ intentions and integration of Web 2.0 tools. Educational Technology Research and Development, 64(1), 37–64.Google Scholar
  56. Shaffer, D. W., & Resnick, M. (1999). “Thick” authenticity: New media and authentic learning. Journal of Interactive Learning Research, 10(2), 195–215.Google Scholar
  57. Shenton, A. K. (2004). Strategies for ensuring trustworthiness in qualitative research projects. Education for information, 22(2), 63–75.Google Scholar
  58. Small, M. L. (2009). How many cases do I need? ‘On science and the logic of case selection in field-based research. Ethnography, 10(1), 5–38.  https://doi.org/10.1177/1466138108099586.Google Scholar
  59. Somech, A. (2008). Managing conflict in school teams: The impact of task and goal interdependence on conflict management and team effectiveness. Educational administration quarterly, 44(3), 359–390.Google Scholar
  60. Spillane, J. P., Parise, L. M., & Sherer, J. Z. (2011). Organizational routines as coupling mechanisms: Policy, school administration, and the technical core. American Educational Research Journal, 48(3), 586–619.Google Scholar
  61. Spradley, J. P. (2016). Participant observation. Long Grove, IL: Waveland Press.Google Scholar
  62. Strobel, J., & Van Barneveld, A. (2009). When is PBL more effective? A meta-synthesis of meta-analyses comparing PBL to conventional classrooms. Interdisciplinary Journal of Problem-based Learning, 3(1), 4.  https://doi.org/10.7771/1541-5015.1046.Google Scholar
  63. Sutherland, J., & Sutherland, J. J. (2014). Scrum: The art of doing twice the work in half the time. New York, NY: Crown Business.Google Scholar
  64. Tatar, D., Roschelle, J., Knudsen, J., Shechtman, N., Kaput, J., & Hopkins, B. (2008). Scaling up innovative technology-based mathematics. The Journal of the Learning Sciences, 17(2), 248–286.Google Scholar
  65. Tawfik, A. A., & Kolodner, J. L. (2016). Systematizing scaffolding for problem-based learning: A view from case-based reasoning. Interdisciplinary Journal of Problem-Based Learning, 10(1), 6.  https://doi.org/10.7771/1541-5015.1608.Google Scholar
  66. Vanderlinde, R., & van Braak, J. (2010). Implementing an ICT curriculum in a decentralised policy context: Description of ICT practices in three Flemish primary schools. British Journal of Educational Technology, 41(6), E139–E141.  https://doi.org/10.1111/j.1467-8535.2010.01111.x.Google Scholar
  67. VanLehn, K. (1988). Toward a theory of impasse-driven learning. In H. Mandl & A. Lesgold (Eds.), Learning issues for intelligent tutoring systems (pp. 19–41). New York, NY: Springer.Google Scholar
  68. Weiss, R. S. (1994). Learning from strangers: The art and method of qualitative interview studies. New York, NY: Free Press.Google Scholar
  69. Yadav, A., Subedi, D., Lundeberg, M. A., & Bunting, C. F. (2011). Problem-based learning: Influence on students’ learning in an electrical engineering course. Journal of Engineering Education, 100(2), 253.  https://doi.org/10.1002/j.2168-9830.2011.tb00013.x.Google Scholar
  70. Zaritsky, R., Kelly, A. E., Flowers, W., Rogers, E., & O’Neill, P. (2003). Clinical design sciences: A view from sister design efforts. Educational Researcher, 32(1), 32–34.  https://doi.org/10.3102/0013189x032001032.Google Scholar
  71. Zhang, H., Easterday, M. W., Gerber, E. M., Rees Lewis, D., & Maliakal, L. (2017). Agile research studios: Orchestrating communities of practice to advance research training. In Proceedings of the ACM conference on computer supported cooperative work and social computing, Portland, OR, USA. New York, NY: ACM Press.Google Scholar

Copyright information

© Association for Educational Communications and Technology 2019

Authors and Affiliations

  1. 1.Delta LabNorthwestern UniversityEvanstonUSA
  2. 2.School of Education and Social PolicyNorthwestern UniversityEvanstonUSA
  3. 3.McCormick School of EngineeringNorthwestern UniversityEvanstonUSA

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