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Exploring Student Preference between Textbook Chapters and Adaptive Learning Lessons in an Introductory Environmental Geology Course

  • E. Christa FarmerEmail author
  • Amy J. Catalano
  • Adam J. Halpern
Original Paper

Abstract

In a Fall 2017 introductory course in Environmental Geology, homework assignments alternated between traditional textbook chapters in an electronic format and adaptive learning platform (ALP) modules on the Smart Sparrow (www.smartsparrow.com) platform to assess student preference for and satisfaction with either modality. Few studies have evaluated the role of ALP technology in a classroom setting, and none have investigated ALPs in a homework setting. To probe student preferences between these assignments, and their engagement with the material through the different modalities, all (n = 17) students in the course were given eight surveys over the Fall 2017 semester. A subset of six students volunteered for qualitative interviews in addition to the quantitative surveys. Analysis of the results shows that students were more satisfied with the ALP modules, except for the longest assigned module. No relationships were found between preference for one module over another and major, engagement, or interest in environmental geology. A majority of the students interviewed identified the interactivity of the adaptive learning modules as a contributing factor to the retention of concepts presented. This suggests students experienced a higher level of cognitive engagement with the ALP material.

Keywords

Adaptive learning platforms Student satisfaction Personal interest 

Notes

Acknowledgements

The authors appreciate the participation of the students in the Fall 2017 GEOL005 Environmental Geology course, and formative discussions of the research plan with Julie Sexton, Assistant Director of Assessment at the University of Northern Colorado. The authors also gratefully acknowledge the suggestions of four anonymous reviewers and appreciate the efforts of the editors to improve the manuscript.

Funding Information

Access to the Smart Sparrow adaptive learning platform was provided by Smart Sparrow and The Inspark Teaching Network for all 17 students, one faculty member (ECF), and one instructional designer who collaborated on module development (AJH).

Compliance with Ethical Standards

Disclosure Statement

Except for the direct financial assistance provided by Smart Sparrow and The Inspark Teaching Network as described above, none of the authors have any financial interest benefit from this research.

Supplementary material

11528_2019_435_MOESM1_ESM.docx (16 kb)
ESM 1 (DOCX 16.4 kb)

References

  1. Belland, B. R., Walker, A. E., Kim, N. J., & Lefler, M. (2017). Synthesizing results from empirical research on computer-based scaffolding in STEM education: A meta-analysis. Review of Educational Research, 87(2), 309–344.  https://doi.org/10.3102/0034654316670999.CrossRefGoogle Scholar
  2. Bolliger, D. U., & Wasilik, O. (2012). Student satisfaction in large undergraduate online courses. Quarterly Review of Distance Education, 13(3), 153–165.Google Scholar
  3. Griff, E. R., & Matter, S. F. (2013). Evaluation of an adaptive online learning system. British Journal of Educational Technology, 44(1), 170–176.CrossRefGoogle Scholar
  4. Handelsman, J., Ebert-May, D., Beichner, R., Bruns, P., Chang, A., DeHaan, R., et al. (2004). Scientific teaching. Science, 304, 521–522.CrossRefGoogle Scholar
  5. Harackiewicz, J. M., Durik, A. M., Barron, K. E., Linnenbrink-Garcia, L., & Tauer, J. M. (2008). The role of achievement goals in the development of interest: Reciprocal relations between achievement goals, interest, and performance. Journal of Educational Psychology, 100(1), 105–122.CrossRefGoogle Scholar
  6. Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111–127.CrossRefGoogle Scholar
  7. Huang, B., & Hew, K. F. (2016). Measuring learners’ motivation level in massive open online courses. International Journal of Information and Education Technology, 6(10), 759–764.CrossRefGoogle Scholar
  8. Johnson, R., & Christensen, L. (2017). Educational research. Washington, D.C: Sage.Google Scholar
  9. Keller, J. M. (2009). Motivational design for learning and performance: The ARCS model approach (ebook). Springer.Google Scholar
  10. Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: A meta-analytic review. Review of Educational Research, 86(1), 42–78.CrossRefGoogle Scholar
  11. Mitchell, M. (1993). Situational interest: Its multifaceted structure in the secondary school mathematics classroom. Journal of Educational Psychology, 85(3), 424–436.CrossRefGoogle Scholar
  12. Murray, M. C., & Pérez, J. (2015). Informing and performing: A study comparing adaptive learning to traditional learning. Informing Science: The International Journal of an Emerging Transdiscipline, 18, 111–125.CrossRefGoogle Scholar
  13. Opidee, I. (2014). Textbook industry forecast: Radical change ahead. Retrieved August, 9, 2019 from www.universitybusiness.com.
  14. Park, S. W., & Kim, C. M. (2016). The effects of a virtual tutee system on academic reading engagement in a college classroom. Educational Technology Research Development, 64, 195–218.CrossRefGoogle Scholar
  15. Pelech, J., & Hibbard, S. T. (2011). Evaluating the effectiveness of reading strategies for college students: An action research approach. Journal of Research in Education, 21(1), 99–114.Google Scholar
  16. Pintrich, P. R, Smith, D. A., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). Office of Educational Research and Improvement. Accessed 11 July 2017 at http://files.eric.ed.gov/fulltext/ED338122.pdf.
  17. Posner, Z. (2018). Personalizing adaptive learning. TD: Talent Development, 72(1), 24–28.Google Scholar
  18. Salinger, T., & Fleischman, S. (2005). Research matters: Teaching students to interact with text. Educational Leadership, 63(2), 90–92.Google Scholar
  19. Sculz, A. C. (2013). Reinventing book printing: The next generation of custom textbooks. Publishers Weekly.Google Scholar
  20. Sit, S., & Brudzinski, M. R. (2017). Creation and assessment of an active e-learning introductory geology course. Journal of Science Education and Technology, 26, 629–645.  https://doi.org/10.1007/s10956-017-9703-3.CrossRefGoogle Scholar
  21. Stains, M., Harshman, J., Barker, M. K., Chasteen, S. V., Cole, R., DeChenne-Peters, S. E., et al. (2018). Anatomy of STEM teaching in north American universities. Science, 359(6383), 1468–1470.CrossRefGoogle Scholar
  22. Vandsburger, E., & Duncan-Daston, R. (2011). Evaluating the study guide as a tool for increasing students' accountability for reading the textbook. Journal of College Reading and Learning, 42(1), 6–23.CrossRefGoogle Scholar
  23. Waters, J. K. (2014). Adaptive learning: Are we there yet? T H E Journal, 41(4), 12–16.Google Scholar
  24. Webley, K. (2013). A is for adaptive. Time, 81, 23 0040781X.Google Scholar
  25. Xu, D., Huang, W. W., Wang, H., & Heales, J. (2014). Enhancing e-learning effectiveness using an intelligent agent-supported personalized virtual learning environment: An empirical investigation. Information & Management, 51, 430–440.CrossRefGoogle Scholar

Copyright information

© Association for Educational Communications & Technology 2019

Authors and Affiliations

  1. 1.Geology, Environment, and Sustainability DepartmentHofstra UniversityHempsteadUSA
  2. 2.Teaching, Learning and Technology DepartmentHofstra UniversityHempsteadUSA
  3. 3.School of EducationHofstra UniversityHempsteadUSA

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