Abstract
The importance of teachers in online learning is widely acknowledged to effectively support and stimulate learners. With the increasing availability of learning analytics data, online teachers might be able to use learning analytics dashboards to facilitate learners with different learning needs. However, deployment of learning analytics visualisations by teachers also requires buy-in from teachers. Using the principles of technology acceptance model, in this embedded case-study, we explored teachers’ readiness for learning analytics visualisations amongst 95 experienced teaching staff at one of the largest distance learning universities by using an innovative training method called Analytics4Action Workshop. The findings indicated that participants appreciated the interactive and hands-on approach, but at the same time were skeptical about the perceived ease of use of learning analytics tools they were offered. Most teachers indicated a need for additional training and follow-up support for working with learning analytics tools. Our results highlight a need for institutions to provide effective professional development opportunities for learning analytics.
Highlights
Over 20 years of research has consistently found that teachers play an essential role in online, open and distributed learning (Lawless & Pellegrino, 2007; Mishra & Koehler, 2006; Shattuck & Anderson, 2013; van Leeuwen, Janssen, Erkens, & Brekelmans, 2015)
No significant differences in satisfaction were found in terms of gender, discipline, or functional role, indicating that participants in general were positive about the Analytics4Action Workshop (A4AW) programme
Our study amongst 95 experienced teachers indicated that most teachers found our learning analytics dashboards a potentially useful addition to their teaching and learning practice
Summary
Over 20 years of research has consistently found that teachers play an essential role in online, open and distributed learning (Lawless & Pellegrino, 2007; Mishra & Koehler, 2006; Shattuck & Anderson, 2013; van Leeuwen, Janssen, Erkens, & Brekelmans, 2015). With the increasing availability of learner data (i.e., “static data” about the learner; such as demographics or prior educational success) and learning data (i.e., “dynamic data” about the behaviour of a learner; such as engagement in a virtual learning environment, library swipes or number of discussion forum messages) in most institutions (Fynn, 2016; Heath & Fulcher, 2017; Rienties, Giesbers, Lygo-Baker, Ma, & Rees, 2016), powerful analytics engines (Hlosta, Herrmannova, Zdrahal, & Wolff, 2015) that offer visualisations of student learning journeys (Charleer, Klerkx, Duval, De Laet, & Verbert, 2016; Daley, Hillaire, & Sutherland, 2016; Jivet, Scheffel, Specht, & Drachsler, 2018) may enable teachers to provide effective support to diverse groups of learners. Several authors have indicated that learning analytics dashboards may empower teachers to provide just-in-time support (Daley et al, 2016; Herodotou et al, 2017; Mor, Ferguson, & Wasson, 2015; Verbert, Duval, Klerkx, Govaerts, & Santos, 2013) and help them to fine-tune the learning design; especially if large numbers of students are struggling with the same task (Rienties, Boroowa et al, 2016; Rienties & Toetenel, 2016)
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