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Show Notes:

In our last episode, Yana interviewed Alexander Chamessian, an MD PhD student who has been consistently utilizing evidence-based learning strategies. In this bite-size research episode, Yana follows up with a study on retrieval practice with complex medical information.

In this study by scientists at a department of Health and Kinesiology (1), students taking an exercise physiology re-read or practiced retrieval practice on background texts and journal articles, and then took critical analysis and factual texts. The debate between John Sweller (2) and Jeff Karpicke (3) on whether retrieval practice works with complex materials can be found in this special issue.

The following table shows the phases in the experiment:

Image from Dobson, Linderholm, & Perez (2018)

The main result can be found in this figure:

Image from Dobson, Linderholm, & Perez (2018)

References:

(1) Dobson, J., Linderholm, T., & Perez, J. (2018). Retrieval practice enhances the ability to evaluate complex physiology information. Medical Education, 52, 513-525.

(2) Van Gog, T., & Sweller, J. (2015). Not new, but nearly forgotten: the testing effect decreases or even disappears as the complexity of learning materials increases. Educational Psychology Review, 27, 247-264.

(3) Karpicke, J. D., & Aue, W. R. (2015). The testing effect is alive and well with complex materials. Educational Psychology Review, 27, 317-326.

This episode was funded by The Wellcome Trust.

Show Notes:

This is a bite-size research episode, where we briefly describe research findings on a specific topic. This week, Yana talks about interleaving while trying to learn how to categorize things.

In the last episode, we talked about the research on interleaving. The idea behind interleaving is that students might switch up their studying so that they are not studying the same idea or concept for a long time, but instead are alternating the material they are studying. Mainly, the benefits that we discussed come from studies of motor learning (1) or problem solving (2). So, we talked about studies where students were given math homework based on one type of problem, or math homework with problems from different areas that required different approaches to solve them (2).

In this episode, Yana talks about a different type of learning that has also been shown to benefit from interleaving: learning which items are part of one category, and which are part of another. Earlier research on this topic looked at how people learn to classify paintings by different artists (3), or different types of birds into a taxonomy (4). In these studies, students aren’t interleaving problem solving or retrieval practice. Instead, they are just studying examples from different categories. And in these studies, interleaving examples from different categories generally helps the learner extract the main features of each category.

The set of studies described in this episode (5) applied this type of design to students learning chemistry. In this set of experiments, students studied visual representations of chemicals, as shown below. Each diagram shows the structure of the elements, and how they form the chemicals.

Image from Eglington and Kang (2017)

They saw 12 examples of chemicals in each of 5 categories - 60 examples in total. Then, when they came back two days later, students were shown new visual representations from these 5 chemical categories, and were asked to determine which category they fit into. What differed between the two groups of students was whether the examples from the 5 categories had appeared interleaved or blocked during the study phase. Those who had seen the chemicals interleaved during study got an average to 85% on the categorization quiz 2 days later, compared to only 71% in the blocked condition. In a follow-up experiment with more complex materials, students who interleaved performed at 65% and students who blocked performed at 49% on the later test, showing the same pattern of results. The authors also found that participants in the interleaving group outperformed those in the blocking group even when both groups were given cues about similarities and differences between categories.

This type of learning - that is, learning how to categorize visual representations of chemical elements - may seem quite basic, but it is actually very important for those who want to go on and study chemistry in more depth. For example, knowing which chemicals belong to which category is essential to understanding how the chemicals interact. And, the same can be said for any subject: knowing the basics is essential to later understanding of more complex abstract ideas.

Tune in over the next two months to learn about the remaining two strategies, concrete examples and dual coding!

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References:

(1) Shea, J. B., & Morgan, R. L. (1979). Contextual interference effects on the acquisition, retention, and transfer of a motor skill. Journal of Experimental Psychology: Human Learning and Memory, 5, 179-187.

(2) Taylor, K., & Rohrer, D. (2010). The effects of interleaved practice. Applied Cognitive Psychology, 24 , 837-848.

(3) Kornell, N., & Bjork, R. A. (2008). Learning concepts and categories: Is spacing the “enemy of induction”? Psychological Science, 19, 585-592.

(4) Tauber, S. K., Dunlosky, J., Rawson, K. A., Wahlheim, C. N., & Jacoby, L. L. (2013). Self-regulated learning of a natural category: Do people interleave or block exemplars during study?. Psychonomic Bulletin & Review, 20, 356-363.

(5) Eglington, L. G., & Kang, S. H. (2017). Interleaved Presentation Benefits Science Category Learn...

This episode was funded by The Wellcome Trust, and supporters like you. For more details, please see our Patreon page. In today's episode, we feature one of our patrons, Bob Reuter.

Listening on the web? You can subscribe to our podcast to get new episodes each month! Go to our show on iTunes or wherever you get your podcasts.

RSS feed: http://www.learningscientists.org/learning-scientists-podcast/?format=rss

Show Notes:

This is the second episode in a series recorded in London! In June 2018 we attended the European Association for Research on Learning and Instruction conference (or, more simply, EARLI) for the special interest group on Neuroscience and Education (@EarliSIG22). While there, we recorded live interviews with teachers and researchers. This episode features Michael Hobbiss. (Check out Episode 21 for our first interview with Dr. Emma Blakey!)

Please excuse any issues with sound quality. We were quite literally recording on the fly!

Michael Hobbiss started his career as a teacher for 8 years, teaching psychology and biology in the UK and abroad. He is now back in the UK, pursuing his PhD with Dr. Nilli Lavie at University College London. His focus is on attention, distraction, and cognitive control in adolescents. Mike tweets at @mikehobbiss and blogs at The Hobbolog.

In the beginning of the episode, Mike describes the two main ways attention is captured:

Bottom-up: the object or stimulus itself
Top-down: your prior knowledge, interest, motivation

Both of these processes are prone to distraction. But surprisingly, Mike says, we don't know all that much about how students get distracted during learning. We do know that attention is related to important educational outcomes: for example, teacher ratings of children's attention at age 5 correlate with the children's later academic success (although, teacher ratings are not always reliable and tend to vary between cultures). We also know that inattention can be related to being unhappy. For his PhD, Michael has set out to investigate attention processes in adolescents.

The irrelevant distractor task

Mike uses the "irrelevant distractor" task in his research. In this task, participants have to pick a particular object out of a visual display. For example, they might have to pick out the letter O from an array of Xs. This would be an easy task - one with low "perceptual load", because the other letters (Xs) do not look similar to the target letter (O). In a high perceptual load version of this task, participants would need to pick out the letter X from, say, letters like K or M, which are more similar. At the same time, during this task, random irrelevant distractors such as Sponge Bob will pop up on the screen.

Image from a presentation by Dr. Sophie Forster

Typically, when the task has higher perceptual load, people are less likely to notice and be distracted (in other words, slowed down) by the irrelevant distractor (1). However, Mike didn't find this pattern in his research with adolescents - in the episode he describes a very different pattern of results that involved adolescents' accuracy as well as speed. Interestingly, Mike found a relationship between students' self-reported level of distraction during class and their performance on this task.

While these results are exciting, Mike warns against acting on these findings immediately in the classroom - we need to understand a lot more about how distraction varies within and between children before we build interventions to address it.

The big takeaway

We tend to think of attention as a resource that we either have or don't have; this may not be a useful way to think about it. Many factors in the environment influence attention, so there is enormous potential to improve attention - for example, putting your phone away when you're trying to work, ...

This episode was funded by listeners like you. For more details on how to help support our podcast and gain access to exclusive content, please see our Patreon page.

Show Notes:

In Episode 78, Megan, Cindy, Carolina, and Althea talk through the resources available on learningscientists.org.

This episode was funded by The Wellcome Trust.

Show Notes:

This is a bite-size research episode, where we briefly describe research findings on a specific topic. This week, Megan Sumeracki talks about elaborative interrogation with middle school students.

In the study Megan describes (1), elaborative interrogation worked well for students who were working independently, and with a partner. In this study, 6th and 7th grade students learned two types of science facts: those that were consistent with their prior knowledge, and those that were inconsistent. An example of a consistent or unsurprising science fact from their research is "the larger an animal is, the more oxygen it needs to live". But take, for example, this fact: "the sun is made up of every color, including blue and violet". This type of fact might be more surprising to students. The study looked at how elaborative interrogation impacted learning of both types of facts.

The students worked either independently, or in pairs - and in one of the following three learning conditions:
1) Elaborative interrogation: answering the question "why is that fact true?" and using their class materials to help.
2) Select their own study strategy: students were told to study the facts in whatever way they think will help them learn them best, and think back to strategies that have worked in the past.
3) Read the information for understanding, out loud.

Learning was assessed both immediately, and 60 days after the study session. Learning in pairs versus independently did not make a difference, but students who practiced elaborative interrogation learned more than those in the other two learning conditions. This was true both for facts that were consistent, and those that were inconsistent with prior knowledge. Importantly, this learning was durable - 60 days after the study session, students who practiced elaborative interrogation still performed best. It's interesting to note that students who selected their own study strategy did not better than those who just read for understanding.

Here's an important caveat to the findings: the quality of the elaborative interrogation answers mattered. Students performed best when they produced an adequate response to the question. However, producing an "inadequate" response was still better than providing no response at all. And finally, studying in pairs did not lead to a larger number of adequate responses than studying alone.

So far, we’ve covered retrieval practice, spaced practice, and elaborative interrogation in our podcasts. Over the next three months we’ll be talking about interleaving, concrete examples, and dual coding!

Subscribe to our Podcast!

Go to our show on iTunes or wherever you get your podcasts.

RSS feed: http://www.learningscientists.org/learning-scientists-podcast/?format=rss

References:

(1) Woloshyn, V. E., & Stockley, D. B. (1995). Helping students acquire belief-inconsistent and belief-consistent science facts: Comparisons between individual and dyad study using elaborative interrogation self-selected study and repetitious-reading. Applied Cognitive Psychology, 9, 75-89.