Learning Analytics In Practice: Nudging Students Towards Study Success

Now presented as a poster
Summary

Effective adoption of learning analytics by teachers is required to realise its potential. Barriers to adoption include data access, data analysis skills, and ethical concerns. This workshop focuses on the current debates around learning analytics used for student engagement and student conceptual understanding. Discussions and hands-on activities will draw on class room teaching in the NZ higher education context to 1. raise awareness about various data sources available to gain actionable insights on student engagement, and 2. To introduce simple to use learning analytics tools to gain insight into student (dis)engagement and student (mis)conceptions which facilitate action by teachers.

Learning Objectives

  1. To share learning analytics practices drawn from educators’ experiences and the literature.
  2. To gain an awareness of what data sources might constitute good proxies as indicators of student learning issues.
  3. To identify specific students/ groups based on teacher-determined criteria of performance and/or engagement using the open-source Student Relationship Engagement System (SRES) and real world (anonymised) student data.
  4. To design teaching interventions via personalised messaging to students in SRES to promote student engagement.
  5. To explore student conceptions using a text analysis tool and devise teaching interventions to promote conceptions aligned with learning objectives.

Abstract

For students to succeed in their studies, they must be well supported, be engaged socially and academically, and receive clear expectations and feedback on their learning (e.g. Biggs and Tang, 2011; Tinto, 2009; Hattie & Timperley 2007). Teachers are constantly looking for ways to understand and encourage learning with the goal of improving student success, particularly across diverse demographic and equity groups. Student engagement, achievement, retention and course design are amongst the broader areas where learning analytics (LA) practice has the potential to deepen teachers’ understanding of learning and provide real time insights into student progress. However, teachers are often faced with complex systems that hinder data access from learning management systems and other sources. In this hands-on workshop participants will have the opportunity to explore simple to use tools that enable adoption of LA without needing to be expert data analysts. This workshop should be valuable to anyone involved in teaching and learning in the higher education context. Example data sets are provided drawing on real classroom scenarios and issues of student engagement and knowledge misconceptions. Participants learn how to navigate two LA tools designed to improve the student experience: i) the Student Relationship Engagement System (SRES) as an example of enhancing student engagement based on indicators of course use, interaction and attendance and ii) a text analysis tool to reveal student conceptions from written short-answer responses to questions designed to encourage deep approaches to learning. LA has the potential to connect teachers with their students at scale. Moreover, LA implemented from the “bottom-up” allows teachers / educators to gain insights into learning based on teacher-criteria rather than having to rely on institutional data that inform business decisions. Participants are asked to bring their own device (laptop or tablet), data sets are provided.

References

Biggs, J., & Tang, C. (2011). Teaching for quality learning at university (4th ed.). London: McGraw-Hill International.

Tinto, V. (2009). Taking student retention seriously: Rethinking the first year of university. Keynote Address presented at FYE Curriculum Design Symposium 2009. Brisbane, Australia. Retrieved August 17, 2016 from http://www.fyecd2009.qut.edu.au/resources/SPE_VincentTinto_5Feb09.pdf

Hattie, J., & Timperley, H. (2007). The power of feedback. Review of educational research, 77(1), 81-112.

Steve Leictweiss
Marion
Jenny McDonald