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Hello readers and welcome to this week's installment of Learning Science Weekly, which is fueled by my very expensive oatmilk latte habit. (And yes, I am on a first-name basis with my local barista.)

This week, we're taking a look at three topics:

  • Learning analytics and user behavior
  • Note-taking using devices
  • Training transfer

Grab a cup o' joe (or tea, no judgement here) and read on!

Understanding Learning Strategies using Analytics

How does learner behavior change across an entire MOOC program? That’s the question asked by researchers who examined learning analytics to understand the engagement levels of 175 employees participating in a four-MOOC professional development program. Their results, reported in the April 2021 issue of Computers in Human Behavior, suggested that there was a significant association between the use of three different program-level learning strategies and the learner’s performance in the course. Unsurprisingly, learners who were classified as using the “Consistent” strategy were most successful; “Disorganized” students were least successful; and in the middle were my favorite, “Get-it-done” learners. This “Get-it-done” strategy was the most popular across the group; these learners showed a high level of initial engagement that quickly waned and an early focus on completing assessments. Why? Researchers explained that most learners “want to achieve the maximum learning outcome through minimal effort” and thus adopt a “goal-oriented learning approach” (Barthakur et al., 2021). In addition, researchers found that “Disorganized” learners try to make up for lack of activity at the start of each course – suggesting poor self-regulation skills, rather than a lack of interest or motivation. Researchers recommend that these learners are identified early using analytics and that program managers design instructional interventions to help these learners have better self-regulation and manage their time more effectively. Taking this one step further: what if your LMS could signal when learners are engaging in “Disorganized” behaviors, thus triggering a series of instructional messages encouraging them to adopt self-regulation strategies? Something to consider...

Key Takeaway: Learning analytics, including trace data (like the number of times a certain type of content was accessed), can help us classify learners using engagement patterns; these patterns can inform the way we design meaningful, targeted interventions to enhance learning.

Read More ($): Barthakur, A., Kovanovic, V., Jocsimovic, S., Siemens, G., Richey, M., & Dawson, S. (2021). Assessing program-level learning strategies in MOOCs. Computers in Human Behavior, 117.

Taking Notes: What Works?

In an article published in the journal Frontiers in Behavioral Neuroscience, researchers tested the efficacy of taking notes using three different means: on a phone, using a tablet, or with an old-fashioned paper notebook. Using quizzes and fMRIs, they concluded that “brain activations related to memory, visual imagery, and language during the retrieval of specific information, as well as the deeper encoding of that information, were stronger in participants using a paper notebook than in those using electronic devices” (Umejima et al., 2021).

Key Takeaway: We’ve said it before, but taking notes on paper is usually the best way to go when it comes to memory retention.

Read More (open): Umejima, K., Ibaraki, T., Yamazaki, T., & Sakai, K.L. (2021). Paper Notebooks vs. Mobile Devices: Brain Activation Differences During Memory Retrieval. Frontiers in Behavioral Neuroscience, 15.

The Problem of Learning Transfer

Are learners able to successfully transition between acquiring and applying new knowledge? That’s the question asked by researchers, who investigated the ways that participants acquired and applied complex problem-solving skills. Their results showed that the majority of participants were unable to apply their new skills after training -- in other words, they failed to transfer their learning.

In the context of workplace learning and customer education, this is very relevant: how often do we provide training for people with only knowledge acquisition in mind and no consideration for the successful application of a skill? These researchers suggest a variety of strategies to improve the application of acquired skills, including the use of metacognition (a subject to which we dedicated an entire issue). They also identify the opportunity to “build and adapt cognitive models on how transferring knowledge should be assessed, addressed, and taught in order to ensure efficient learning for students, and get closer to filling the crucial performance gap between knowledge acquisition and knowledge application in educational contexts” (Nicolay et al., 2021). Translation: more research is needed. Along these lines, next week we’ll review a few studies that have examined training transfer in workplace contexts, like this one that found “a direct and positive association among self-efficacy, work climate and training intervention design with training transfer” of management skills (Yaqub, Singh, & Dutta, 2021).

Key Takeaway: If your learners can complete a training and only understand a skill, they’re missing the other half of the puzzle. Help people apply their new knowledge before considering your instructional session a success.

Read More ($): Nicolay, B., Krieger, F., Stadler, M., Gobert, J., & Grieff, S. (2021). Lost in transition – Learning analytics on the transfer from knowledge acquisition to knowledge application in complex problem solving. Computers in Human Behavior, 115.

New Podcast Episode!

This week, Julia had the opportunity to chat with Dr. Karl Kapp, who she considers to be the guru of gamification. Check it out on our site or wherever you get your podcasts.

Pets of Learning Science Weekly

Last week we issued a call for more pet photos and wow, did you deliver! It was hard choosing just one picture to feature but we present to you Olive, the kitten with the most mesmerizing eyes! She's the companion of Matt M., who says he religiously reads our content and also listens to our podcast (awww, thanks!!). Matt, look out for an email from us -- we'd like to send you some LSW swag!

Send us your pet pics at

Wondering why we’re including animal photos in a learning science newsletter? It may seem weird, we admit. But we’re banking on the baby schema effect and the “power of Kawaii.” So, send us your cute pet pics -- you’re helping us all learn better!

The LSW Crew

Learning Science Weekly is written and edited by Julia Huprich, Ph.D. Our head of growth and community is Julieta Cygiel.

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