The Impact of OER’s Continuous Improvement Cycles on Students’ Performance: A Longitudinal Analysis of the RISE Framework
DOI:
https://doi.org/10.19173/irrodl.v25i4.7624Keywords:
open educational resources, OER, student performance, longitudinal analysis, learning analytics, higher education, RISE analysisAbstract
Open educational resources (OER) have been praised for revolutionizing education. However, practitioners and instructors battle keeping OER updated and measuring their impact on students’ performance. Few studies have analyzed the improvement of OER over time in relation to achievement. This longitudinal study uses learning analytics through the open-source Resource Inspection, Selection, and Enhancement (RISE) analysis framework to assess the impact of continuous improvement cycles on students’ outcomes. Panel data (i.e., performance and use) from 190 learning objectives of OER of an introductory sociology course were analyzed using a hierarchical linear model. Results show that more visits to an OER do not improve student achievement, but continuous improvement cycles of targeted OER do. Iterative implementation of the RISE analysis for resource improvement in combination with practitioners’ expertise is key for students’ learning. Given that the RISE classification accounted for 65% of the growth of students’ performance, suggesting a moderate to large effect, we speculate that the RISE analysis could be generalized to other contexts and result in greater student gain. Institutions and practitioners can improve the OER’s impact by introducing learning analytics as a decision-making tool for instructional designers. Yet, user-friendly implementation of learning analytics in a “click-and-go” application is necessary for generalizability and escalation of continuous improvement cycles of OER and tangible improvement of learning outcomes. Finally, in this article, we identify the need for efficient applications of learning analytics that focus more on “learning” and less on analytics.
References
Aesoph, L. M. (2018). Self-publishing guide. BCcampus. https://opentextbc.ca/selfpublishguide/
Avila, C., Baldiris, S., Fabregat, R., & Graf, S. (2017). ATCE: An analytics tool to trace the creation and evaluation of inclusive and accessible open educational resources. In I. Molenaar, X. Ochoa, & S. Dawson (Chairs), LAK ’17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference (pp. 183–187). ACM. https://dl.acm.org/doi/10.1145/3027385.3027413
Avila, C., Baldiris, S., Fabregat, R., & Graf, S. (2020). Evaluation of a learning analytics tool for supporting teachers in the creation and evaluation of accessible and quality open educational resources. British Journal of Educational Technology, 51(4), 1019–1038. https://doi.org/10.1111/bjet.12940
Barbier, S. (2021, October 18). The hidden costs of open educational resources. Inside Higher Ed. https://www.insidehighered.com/views/2021/10/19/arguments-favor-oer-should-go-beyond-cost-savings-opinion
Bodily, R., Nyland, R., & Wiley, D. (2017). The RISE Framework: Using learning analytics for the continuous improvement of open educational resources. The International Review of Research in Open and Distributed Learning, 18(2). https://doi.org/10.19173/irrodl.v18i2.2952
Bonafini, F. C., Chae, C., Park, E., & Jablokow, K. W. (2017). How much does student engagement with videos and forums in a MOOC affect their achievement? Online Learning, 21(4). https://doi.org/10.24059/olj.v21i4.1270
Boscardin, C. K., Sebok-Syer, S. S., & Pusic, M. V. (2022). Statistical points and pitfalls: Growth modeling. Perspectives on Medical Education, 11(2), 104–107. https://doi.org/10.1007/S40037-022-00703-1
Castellanos-Reyes, D., Maeda, Y., & Richardson J. C. (2021). The relationship between social network sites and perceived learning and satisfaction: A systematic review and meta-analysis. In M. Griffin & C. Zinskie (Eds.), Social media: Influences on education (pp. 231-263). Information Age Publishing. https://www.researchgate.net/publication/354935042_The_relationship_between_social_network_sites_and_perceived_learning_and_satisfaction_A_systematic_review_and_meta-analysis
Castellanos-Reyes, D., Romero-Hall, E., Vasconcelos, L. & García, B. (2022). Mobile learning in emergency situations: Four design cases from Latin America. In V, Dennen, C, Dickson-Deane, X. Ge, D. Ifenthaler, S. Murthy, & J. Richardson (Eds.), Global perspective on educational innovations for emergency solutions (1st Ed., pp. 89-98). Springer Cham. https://doi.org/10.1007/978-3-030-99634-5
Castellanos-Reyes, D., Koehler, A. A., & Richardson, J. C. (2023). The i-SUN process to use social learning analytics: A conceptual framework to research online learning interaction supported by social presence. Frontiers in Communication, 8, 1212324. https://doi.org/10.3389/fcomm.2023.1212324
Caswell, T., Henson, S., Jensen, M., & Wiley, D. (2008). Open content and open educational resources: Enabling universal education. The International Review of Research in Open and Distributed Learning, 9(1). https://doi.org/10.19173/irrodl.v9i1.469
Colvard, N. B., Watson, C. E., & Park, H. (2018). The impact of open educational resources on various student success metrics. International Journal of Teaching and Learning in Higher Education, 30(2), 262–276. https://www.isetl.org/ijtlhe/pdf/IJTLHE3386.pdf
Curran, P. J., Obeidat, K., & Losardo, D. (2010). Twelve frequently asked questions about growth curve modeling. Journal of Cognition and Development, 11(2), 121–136. https://doi.org/10.1080/15248371003699969
Garrison, D. R., & Cleveland-Innes, M. (2005). Facilitating cognitive presence in online learning: Interaction is not enough. American Journal of Distance Education, 19(3), 133–148. https://doi.org/10.1207/s15389286ajde1903_2
Giannakos, M. N., Chorianopoulos, K., & Chrisochoides, N. (2015). Making sense of video analytics: Lessons learned from clickstream interactions, attitudes, and learning outcome in a video-assisted course. The International Review of Research in Open and Distributed Learning, 16(1). https://doi.org/10.19173/irrodl.v16i1.1976
Griffiths, R., Mislevy, J., Wang, S., Shear, L., Ball, A., & Desrochers, D. (2020). OER at scale: The academic and economic outcomes of Achieving the Dream’s OER Degree Initiative. SRI International. https://www.sri.com/publication/education-learning-pubs/oer-at-scale-the-academic-and-economic-outcomes-of-achieving-the-dreams-oer-degree-initiative/
Grimaldi, P. J., Basu Mallick, D., Waters, A. E., & Baraniuk, R. G. (2019). Do open educational resources improve student learning? Implications of the access hypothesis. PLOS ONE, 14(3), Article e0212508. https://doi.org/10.1371/journal.pone.0212508
Hattie, J., Rogers, H. J., & Swaminathan, H. (2014). The role of meta-analysis in educational research. In A. D. Reid, E. P. Hart, & M. A. Peters (Eds.), A companion to research in education (pp. 197–208). https://doi.org/10.1007/978-94-007-6809-3
Ifenthaler, D. (2015). Learning analytics. In J. M. Spector (Ed.), The SAGE encyclopedia of educational technology (Vol. 2, pp. 447–451). SAGE.
Knight, S., Friend Wise, A., & Chen, B. (2017). Time for change: Why learning analytics needs temporal analysis. Journal of Learning Analytics, 4(3), 7–17. https://doi.org/10.18608/jla.2017.43.2
Martin, M. T., Belikov, O. M., Hilton, J., III, Wiley, D., & Fischer, L. (2017). Analysis of student and faculty perceptions of textbook costs in higher education. Open Praxis, 9(1), 79–91. https://doi.org/10.5944/openpraxis.9.1.432
Müller, F. J. (2021). Say no to reinventing the wheel: How other countries can build on the Norwegian model of state-financed OER to create more inclusive upper secondary schools. Open Praxis, 13(2), 213–227. https://doi.org/10.5944/openpraxis.13.2.125
Owen Wilson, L. (2016). Anderson and Krathwohl Bloom’s Taxonomy revised. Quincy College. https://quincycollege.edu/wp-content/uploads/Anderson-and-Krathwohl_Revised-Blooms-Taxonomy.pdf
Pardo, A., Ellis, R. A., & Calvo, R. A. (2015). Combining observational and experiential data to inform the redesign of learning activities. In J. Baron, G. Lynch, & N. Maziarz (Chairs), LAK ’15: Proceedings of the Fifth International Conference on Learning Analytics And Knowledge (pp. 305–309). ACM. https://doi.org/10.1145/2723576.2723625
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Sage.
Raudenbush, S. W., & Liu, X.-F. (2001). Effects of study duration, frequency of observation, and sample size on power in studies of group differences in polynomial change. Psychological Methods, 6(4), 387–401. https://doi.org/10.1037/1082-989X.6.4.387
Richardson, J. C., Castellanos Reyes, D., Janakiraman, S., & Duha, M. S. U. (2023). The process of developing a digital repository for online teaching using design-based research. TechTrends :For Leaders in Education & Training, 67(2), 217–230. https://doi.org/10.1007/s11528-022-00795-w
Romero-Ariza, M., Abril Gallego, A. M., Quesada Armenteros, A., & Rodríguez Ortega, P. G. (2023). OER interoperability educational design: Enabling research-informed improvement of public repositories. Frontiers in Education, 8, Article 1082577. https://doi.org/10.3389/feduc.2023.1082577
Spurrier, A., Hodges, S., & Schiess, J. O. (2021). Priced out of public schools: District lines, housing access, and inequitable educational options. Bellwether Education Partners. https://bellwether.org/publications/priced-out/
Tang, H. (2021). Implementing open educational resources in digital education. Educational Technology Research and Development, 69(1), 389–392. https://doi.org/10.1007/s11423-020-09879-x
Tlili, A., Garzón, J., Salha, S., Huang, R., Xu, L., Burgos, D., Denden, M., Farrell, O., Farrow, R., Bozkurt, A., Amiel, T., McGreal, R., López-Serrano, A., & Wiley, D. (2023). Are open educational resources (OER) and practices (OEP) effective in improving learning achievement? A meta-analysis and research synthesis. International Journal of Educational Technology in Higher Education, 20(1), Article 54. https://doi.org/10.1186/s41239-023-00424-3
Van Allen, J., & Katz, S. (2020). Teaching with OER during pandemics and beyond. Journal for Multicultural Education, 14(3–4), 209–218. https://doi.org/10.1108/JME-04-2020-0027
Wiley, D. (2007), On the sustainability of open educational resource initiatives in higher education. Center for Educational Research and Innovation, The Organization for Economic Co-operation and Development.
Wiley, D. (2018). RISE: An R package for RISE analysis. Journal of Open Source Software, 3(28), Article 846. https://doi.org/10.21105/joss.00846
Wiley, D. (2012, October 16). OER quality standards. Improving Learning. https://opencontent.org/blog/archives/2568
Winitzky-Stephens, J. R., & Pickavance, J. (2017). Open educational resources and student course outcomes: A multilevel analysis. The International Review of Research in Open and Distributed Learning, 18(4). https://doi.org/10.19173/irrodl.v18i4.3118
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