Enhancing student success and retention: Leveraging learning analytics and student

Student success is an essential component of higher education. Factors encompassing success are multi-faceted ranging from academic achievement, engagement, and progression within programs through to employment, skills development, and co-curricular activities. Student success can be enhanced by embedding transition pedagogy into curriculum (Kift, 2009) and facilitating the development of a sense of capability, purpose, identity, resourcefulness and connectedness (Lizzio, 2006).
At Flinders University, we have applied student success literature to create Student Success Frameworks at the institution and College-levels (Kift, 2009; Lizzio, 2006; Lane et al., 2019). These college based student-centred and holistic frameworks utilise the University strategy principles but provide tailored initiatives addressing specific college needs.
A key initiative of all six college level student success frameworks is the implementation of a personalised student outreach initiative using learning analytics to identify students needing support and provide ‘nudges’ to encourage retention and student success (Lawrence et al., 2021; Brown et al., 2022).
Learning analytics provide an effective tool for identifying and supporting students at risk of low engagement and topic non-completion (Lawrence et al., 2019). Evidence shows that leveraging students’ analytics to inform outreach strategies effectively retains students in courses (see Ifenthaler and Yau (2020) for review). Despite evidence that learning analytics support student success, only pockets of academic communities normalise their use in everyday practice (Guzmán-Valenzuela et al., 2021).
Participants will walk away from this workshop with an understanding of how to assess student engagement and conduct outreach using learning analytics in Moodle, Canvas, and Blackboard; creating an outline for a Student Success Framework; and having an action plan of how to embed student success in their area.
References
Brown, A., et al. (2023). The creation of a nudging protocol to support online student engagement in higher education. Act Learn High Educ. 24(3), 257-271.https://doi.org/10.1177/1469787421103907
Guzmán-Valenzuela, C., Gómez-González, C., Rojas-Murphy Tagle, A., & Lorca-Vyhmeister, A. (2021). Learning analytics in higher education: a preponderance of analytics but very little learning?. Int J of Educ Technol Higher Educ, 18, 1-19. https://doi.org/10.1186/s41239-021-00258-x
Ifenthaler, D., & Yau, J. Y. K. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Educ Technol Res Dev. 68(4), 1961-1990. https://doi.org/10.1007/s11423-020-09788-z
Kift, S. (2009). Articulating a transition pedagogy to scaffold and to enhance the first year student learning experience in Australian higher education: Final report for ALTC senior fellowship program. Strawberry Hills, NSW: Australian Learning and Teaching Council.
Lane, M., Moore, A., Hooper, L., Menzies, V., Cooper, B., Shaw, N., & Rueckert, C. (2019). Dimensions of student success: a framework for defining and evaluating support for learning in higher education. Higher Educ Res Dev., 38(5), 954–968. https://doi.org/10.1080/07294360.2019.1615418
Lawrence, J., Brown, A., Redmond, P., Maloney, S., Basson, M., Galligan, L., & Turner, J. (2021). Does course specific nudging enhance student engagement, experience and success?: A data-driven longitudinal tale. Stud Success, 12(2), 28-37. https://doi.org/10.5204/ssj.1914
Lizzio, A. (2006). Designing an orientation and transition strategy for commencing students. A Conceptual Summary of Research and Practice. First Year Experience Project. Brisbane, Australia: Griffith University