Learning activities that work, versus learning activities people like

Do you give learners what they say they want, or what they really need to achieve their goals? Rienties’ area of interest is in learning analytics. At the The Open University (OU), students report that they dislike collaborative learning but an investigation into the data shows that they learn better when they engage in those types of activities. Rientes’ inaugural address (shown in the video) is a fun discussion about his recent research, using massive datasets to uncover the best learning activities for learning, and the discrepancy between what he found and what learners believed about themselves. His speech is complemented by a more sober article he authored (about this same research), which is one of several papers investigating different aspects of his findings.

Inaugural lecture of Bart Rienties (2018) YouTube video, added by OUresearch on YouTube [Online]. Available at https://www.youtube.com/watch?v=GIWrygqmOIs.

Inge, S. (2018) ‘Student satisfaction “unrelated” to academic performance — study’, Times Higher Education (THE), February 12 [Online]. Available at https://www.timeshighereducation.com/news/student-satisfaction-unrelated-academic-performance-study.

Rienties, B., and Toetenel, L. (2016) ‘The impact of learning design on student behaviour, satisfaction and performance: A cross-institutional comparison across 151 modules’, Computers in Human Behavior, vol. 60, pp. 333-341 [Online]. DOI: 10.1016/j.chb.2016.02.074.

Outline (for journal article)

  1. Introduction
  2. Learning analytics complements learning design
  3. Method
    1. OU Learning Design Initiative (OULDI) learning design
    2. Setting
    3. Instruments
      1. Learning Design mapping
      2. VLE data
      3. Learner satisfaction
      4. Academic retention
      5. Institutional analytics data
    4. Data analysis
  4. Results
    1. Linking learning design activities
    2. Relating learning design with VLE behaviour
    3. Relating learning design with learner satisfaction
    4. Relating learning design with learner performance
  5. Discussion
  6. Conclusions and future work


OU sends out satisfaction surveys to their students asking how they found various aspects of their modules. Rather consistently, students reported that they were happiest when they worked individually rather than collaboratively in groups. However, Rienties looked at data for over 111,000 students in 151 modules, and found that ‘the best predictor for whether students actually passed the module was whether there were collaborative learning activities, such as discussion forums and online [synchronous, teacher-led instruction] sessions’ (Inge, 2018). The main indicator for academic retention (whether or not the student continues their studies) is the ‘time learners spent on communication activities’ (Rienties and Toetenel, 2016, p. 333). Thus, he argues, while learner feedback is important, the people designing courses should make sure to do so in a way that promotes learning.

Rienties does not couch this in terms of “calibration”, but I think that’s in play here: we are not always the best judge about what works best for supporting our learning. 

“Learning Design” and categories of learning activities

OU previously participated in a large initiative called the OU Learning Design Initiative (OULDI)  . It had several parts, and one was something called (rather confusingly) “learning design”. Learning Design in that context is similar to instructional design, but they had envisioned it as a specific process that’s unlike ADDIE and other instructional design processes. It supports a ‘collaborative design approach in which practitioners make informed design decisions with a pedagogical focus through using representations in order to build a shared vision’ (Rienties and Toetenel, 2016, p. 334)

Part of Learning Design was identifying a taxonomy to help categorize and describe learning activities in a module; the taxonomy was used with a mapping tool so that they could visually display the flow of activities in a module. This exercise of mapping courses was useful to Rienties and Toetenel (2016) because they could correspond other learning data with the types of activities.

Other sources of data


The modules tended to offer more assimilative and assessment types of activities. When students faced assimilative and assessment activities, they visited the LMS fewer times than they did with the other types of activities. At least for the people who responded to the satisfaction survey, learners more often felt like the assimilative activities were better for their learning. They felt they were learning better with lone activities, like reading and thinking. They felt like they learned less with activities that required communication with others, and activities that were inquiry- and discovery-based.

However, when the types of learning activities were mapped to retention this was found to not be the case. ‘The primary predictor of academic retention was the relative amount of communication activities. This may be an important finding as in particular in online learning there tends to be a focus on designing for cognition rather than social learning activities’ (Rienties and Toetenel, 2016, p. 339).

This learning activity category...Is...Used frequently?Liked by learners?Best for learning?
AssimilativeAttending to information:
Reading, watching, listening, thinking about, accessing, observing, reviewing
Finding and handling informationSearching for, and processing, information:
Listing, analyzing, collating, plotting, finding, discovering, accessing, using, gathering, ordering, classifying, selecting, assessing, manipulating
CommunicationDiscussing new information with others:
Communicating, debating, discussing, arguing, sharing, reporting, collaborating, presenting, describing, questioning
ProductiveConstructing an artifact:
Listing, creating, building, making, designing, constructing, contributing, completing, producing, writing, drawing, refining, composing, synthesizing, remixing
ExperientialApplying learning in a real-world setting:
Practicing, applying, mimicking, experiencing, exploring, investigating, performing, engaging
Interactive or adaptiveApplying learning in a simulated setting:
Exploring, experimenting, trialing, improving, modelling, simulating
AssessmentSummative, formative, and self-assessments:
Writing, presenting, reporting, demonstrating, critiquing

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