June 2017 research round-up

Research highlights in learning and education from around the world

Like Comment

Test format dictates learning strategies

This study by UCLA researchers investigated how the type of test someone expects affects the learning strategy they use. It showed that when a test was expected to be difficult, students strategized more appropriately. This was particularly the case when it was the format of the test that signalled difficulty.

Students were given either a word recall or word recognition test, with different words assigned different point values, and asked to maximize their point score. For the harder recall test, the best strategy is to prioritise remembering the most valuable words, which is exactly what the students did. For the easier recognition test, there is little need for this strategy, and students showed little preference for learning higher-valued words. However, when the recognition test was made harder, students did focus on remembering the more valuable words, but not to the same extent as during the recall test. The results suggest that expected test format is more important than expected test difficulty in driving learning strategies.

Middlebrooks CD, Murayama K, Castel AD (2017) Test expectancy and memory for important information. Journal of Experimental Psychology: Learning, Memory, and Cognition 43(6) 972-985.

Forgetting, to learn

Why do we need to forget? Intuitively, the simple answer is that the brain does not hold enough capacity to store all of our experiences. However in a recent Perspective article in the journal Neuron, researchers from the University of Toronto propose that rather than being caused by our brain’s limitations, forgetting is actually a good thing: it helps us generalize from our experiences, and allows more efficient and flexible learning.

The authors first cover what we know about the neurobiological mechanisms of how memories are stored and forgotten. Next, they provide some examples of how memory transience can actually enhance new learning and behavioral flexibility. They also discuss how our gist- rather than detail-oriented memories help us to generalize across experiences, providing better guidance for future behaviors.

Ultimately, the authors argue that our fallible memories actually help us to thrive in an environment that is always changing and unpredictable. Still, this knowledge might be little comfort to students who are asked to memorize the periodic table.

Richards BL and Frankland PW (2017) The persistence and transience of memory. Neuron 94:1071-1084

Deep learning in higher education

Learning strategies can be categorised as surface or deep. Surface learning is learning by memorization, and allows facts and knowledge to be repeated or recalled. Deep learning is more meaningful, critical learning, and involves connecting new information with past knowledge. To generate understanding, deep learning is preferable.

In this study, Finnish and Belgian researchers wanted to know whether university students develop deeper approaches to learning during their studies. To address this, the authors analyzed 43 published studies on the topic, and found that around 40% of papers reported an increase in deep approaches during higher education (based on students’ self-reported strategies). However, ~40% reported no change, and 20% reported decreases. Changes in surface approaches also varied widely, with similar numbers of studies reporting increases and decreases in surface learning.

The authors conclude that there is no empirical evidence that students develop deeper approaches to learning during higher education. They suggest that existing studies are not controlled well enough, or similar enough to each other in methodology, to generate consistent results.

Asikainen H and Gijbels D (2017) Do students develop towards more deep approaches to learning during studies? A systematic review on the development of students’ deep and surface approaches to learning in higher education. Educational Psychology Review 29(2): 205-234 

Brain network changes help executive functions

Executive functions such as working memory, attention and emotional control allow us to plan and make decisions. These traits become more evident as a child ages, and the presence of certain executive functions has even been proposed as indicating that a child is ready to start school.

Even at relatively early stages, the brain exhibits highly interconnected brain networks called modules. Previous studies have looked at when these modules were coactive, showing that different modules become more independent and distinct from each other as a child progresses through adolescence and into adulthood.

In this study, researchers looked at whether structural segregation also occurred. Specifically, they scanned the brains of over 800 participants, aged 8–22, and looked at whether the white matter connections within and between modules changed. Their results showed that white matter connections within modules became stronger, whereas those between modules became weaker – in effect segregating them from each other – changes that make the entire brain network more efficient. The authors also showed that executive function performance correlated with the degree of segregation, even when discounting the effects of age. They conclude that structural changes during brain development increase the segregation of brain modules, leading to improved executive functions.

Baum GL et al. (2017) Modular segregation of structural brain networks supports the development of executive function in youth. Current Biology 27: 1561-1572

Alan Woodruff

Community Editor, Queensland Brain Institute