The Learning Scientists Podcast

This episode was funded by The Wellcome Trust, Chartered College of Teaching, and supporters like you. For more details on how to help support our podcast, please see our Patreon page. In today's episode, we feature one of our patrons, Abby Zavos.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=rssShow Notes:This is the sixth 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. In this episode, we speak with Jessica Massonnié, who is pursuing her PhD at Birkbeck University on the effects of noise in primary school classrooms. She Tweets at @jess_masso and you can find her website here. Primary school classrooms tend to be noisy (approximately as noisy as traffic or a vacuum cleaner). Jessica's work looks at how this noise affects learning outcomes. One of her first studies looked at the effect of recoded classroom noise on children's creativity in a lab environment. In the podcast, Jessica talks about some preliminary findings from this study.More recently, Jessica has moved on to classroom-based research. In a study that takes place in France, she is looking at individual differences in how annoying children find noise. This factor appears to be related to how difficult it is for children to switch between tasks, and how often they mind-wander. Jessica is also looking at the effects of a mindfulness intervention on noise levels, noise awareness, and French/math test performance. The big take-awayIt's important to be aware of noise levels; for example you can easily download an app to check noise levels in your environment. It would also be good to identify sources of noise in the learning environment - particular noises that are completely irrelevant to learning, such as the sounds of chairs scraping on the floor - and attempt to eliminate those noises.Relevant reading and links:Klatte, M., Bergström, K., & Lachmann, T. (2013). Does noise affect learning? A short review on noise effects on cognitive performance in children. Frontiers in Psychology, 4, 578.Mehta, R., Zhu, R., & Cheema, A. (2012). Is noise always bad? Exploring the effects of ambient noise on creative cognition. Journal of Consumer Research, 39, 784-799.Shield, B., & Dockrell, J. E. (2004). External and internal noise surveys of London primary schools. The Journal of the Acoustical Society of America, 115, 730-738.A website with yoga tutorials, created by the expert we have hired for my school study. A kit created by the association I am part of, to introduce children to the brain, to attention and distraction.Previous Episodes from this series:Episode 21 with Dr. Emma BlakeyEpisode 22 with Michael HobbissEpisode 23 with Rina LiaEpisode 24 with Ignatius GousEpisode 25 with Amanda Triccas and Clare Badger

This episode was funded by The Wellcome Trust, and supporters like you. For more details on how to help support our podcast, please see our Patreon page.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=rssShow Notes:This is the fifth 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. In this episode, we speak to Ms. Amanda Triccas and Dr. Claire Badger at The Godolphin and Latymer School. Amanda was Yana's teacher in the 1990s, and we've reconnected recently around the science of learning. Amanda has always worked in the private sector - usually in girls' schools - and a few years ago got into the science of learning. Claire's PhD is in Chemistry, and they both work at Godolphin and Latymer School for Girls. Amanda and Claire both got interested in the science of learning when Amanda found The Learning Scientists Twitter account and recognized Yana's name. For Claire, it was starting at the school with Amanda, and reading Efficiency in Learning: Evidence-Based Guidelines to Manage Cognitive Load by Clark, Nguyen, and Sweller.We discuss how cognitive psychology can help teachers and students. Amanda mentions efficiency, and Claire mentions having more time for teachers to do things in the classroom by optimizing learning. We also discuss students' resistance to change, and teachers' fear of embarrassing themselves in front of students.Claire and Amanda integrate strategies from cognitive psychology into their teaching, but they also explain their importance to their students, as well as to parents by providing them with the 6 strategies for effective learning posters.As a Senior Teacher in Teaching and Learning, Claire set up a teaching-learning community based on ideas by Dylan William (see this White Paper). This allowed teachers who were interested in the science of learning to come together and explore theory and practice. This community soon grew to encompass virtually all the teachers in the school. Similarly, Claire has created student learning communities, though these require more guidance to avoid misunderstandings.Amanda and Claire have some thoughts for how we can help. The illustrated work we've done with Oliver Caviglioli has been particularly useful, and they would like to see further resources produced for younger children. Claire also likes the Education Endowment Foundation (EEF), which provides concrete examples of how strategies can be used in the classroom. She would like to see more comprehensive reviews and summaries of the literature, with suggestions for teachers and students.Claire is currently pursuing her Masters in Learning and Teaching at the UCL Institute of Education.Previous Episodes from this series:Episode 21 with Dr. Emma BlakeyEpisode 22 with Michael HobbissEpisode 23 with Rina LiaEpisode 24 with Ignatius Gous

This episode was funded by The Wellcome Trust, and supporters like you. For more details on how to help support our podcast, please see our Patreon page.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=rssShow Notes:This is the fourth 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 Ignatius Gous.Ignatius begins the episode with an interesting explanation about the origins of his name. Ignatius is a professor at the University of South Africa, which is primarily a distance university, with students from all over the world taking online classes. He has developed a program for students to learn better and master content more effectively. This program is used by learners at the primary, secondary, and college levels, with advanced students of medicine and law, and even in the workplace. Ignatius has long wondered why neuromyths are so prevalent, and his theory is that people want to know about how the brain works, and these neuromyths fill the void. He thus set out to create a framework that would actually be useful and evidence-based, to help those interested in learning to do so more effectively - even those as young as primary school age.According to Ignatius, learning is not linear - it is more of a spiral - but it still needs structure. Ignatius built his model with the Fibonacci code as the basis. The spiral includes 6 aspects involved in the learning process, with metacognition as the 7th. You can see all the steps represented here in visual form: We talk in this episode about different mnemonic strategies that fit into this model, including the method of loci - you can read more about this method in this blog post. We also discuss the importance of learning basic facts before moving on to transferring learning to new, more complex situations. One idea Ignatius suggests is for students to memorize the headings of a chapter to use as a guideline for organizing and retrieving information. This ties in with this guest blog post by Yana’s former student, who used a similar method for retrieval practice after taking notes in class.Ignatius emphasizes that we need to always think about how students are going to use the material we are teaching them. He calls his model “the golden spiral for life-long learning”, because learning isn’t just something you do to cram for a test - learning happens until you die. Previous Episodes from this series:Episode 21 with Dr. Emma BlakeyEpisode 22 with Michael HobbissEpisode 23 with Rina Lia

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, Josh Fisher, and his free math apps at Guzinta Math.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=rssShow Notes:This is the third 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 Rina Lai. (Check out Episode 21 for our first interview with Dr. Emma Blakey and Episode 22 with Michael Hobbiss!)Please excuse any issues with sound quality. We were quite literally recording on the fly! Rina P.Y Lai (黎栢凝) received her B.A in psychology at the University of British Columbia and MPhil in psychology & education at Cambridge University. She is now a PhD candidate and a member of a the INSTRUCT research group, a laboratory at Cambridge university that integrates cognitive developmental science to inform learning. She is particularly interested in the cognitive underpinnings of computational thinking. Currently, she is collaborating with computer scientists to develop a new computerized assessment of computational thinking that could be used by students, teachers and researchers. Rina is the founding member and internal vice president of the Cambridge China Education Forum. She has also co-founded the LT Academy, which provides consultancy services to STEM and robotics education to education institutions. You can find her on her website at rinalai.com and on Instagram @rina_py_lai. You can also check out PEDAL: Centre for Research on Play in Education, Development & Learning to see the work she is involved with.Rina's Masters project focused on the differences between executive function and metacognition. Both are higher cognitive domains, both linked to prefrontal cortex, and both relate to academic outcomes. Executive functioning is an umbrella term that includes a number of neuropsychological processes including working memory, cognitive inhibition, cognitive flexibility, and planning. Meta-cognition is a cognitive domain concerned with how we think about our own thinking, and how we regulate our thoughts to maximize learning. For example, if a child has a question in class, they have to use inhibition to ask the question at the right time, and working memory to remember the question. Rina's group looked at educational outcomes including arithmetic, vocabulary, verbal reasoning, and non-verbal reasoning (previous research focused on one or only a couple of outcomes). Interestingly, they found that executive function and metacognition have both shared and unique contributions to educational outcomes.After doing her Masters, Rina volunteered at a robotics camp for kids age 8-10, and this experience changed her trajectory. Now, Rina's research direction has shifted to studying computational thinking. Computational thinking is a set of cognitive processes that help us formulate a problem and devise a solution. These processes include decomposition, abstraction, algorithms, and debugging. Contrary to what it sounds like, this is not about using a computer! This is a skill that should be integrated into different subjects, rather than taught in isolation. Rina set out to look at computational thinking skills and how they relate to educational outcomes. In her literature review, she realized that there was no good assessment for computational thinking, since most are currently tailored to computer programming specifically. This has led Rina to focus on how to measure computational thinking to identify strengths and weaknesses of different processes within this domain.In the future, Rina hopes to use the assessment in her own research to look for the relationship between computational thinking educational outcomes, and she also hope that teachers might find it useful as a formative assessment.The big takeawayRina's biggest takeaway is a quote she shared with us:"We are currently preparing students for jobs that don’t yet exist . . . using technologies that haven’t yet been invented . . . in order to solve problems we don’t even know are problems yet."—Richard Riley, Secretary of Education under Clinton" —Richard Riley, Secretary of Education under ClintonPrevious Episodes from this series:Episode 21 with Dr. Emma BlakeyEpisode 22 with Michael Hobbiss

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=rssShow 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 itselfTop-down: your prior knowledge, interest, motivationBoth 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 taskMike 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 takeawayWe 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, choosing what type of music you are listening to, and using pictures effectively.References:(1) Forster, S., & Lavie, N. (2009). Harnessing the wandering mind: The role of perceptual load. Cognition, 111, 345-355.Previous Episodes from this series:Episode 21 with Dr. Emma Blakey

Dr. Emma Blakey, Lecturer in Developmental Psychology at the University of Sheffield who studies how young children develop self-regulation. She discusses what executive function means and its components. She describes rapid preschool gains around ages 3–4 and links to language and brain growth. She covers school readiness, task switching and interleaving for young learners, and practical classroom supports.

They explain why sleep is crucial for both physical health and cognitive functioning. They describe lab and classroom studies showing sleep after learning boosts retention and helps apply and integrate new material. They discuss how even small sleep deficits hurt performance. Practical sleep hygiene tips and advice for building lifelong healthy habits are offered.

Researchers discuss a study where medical residents attended interactive conferences and then either practiced retrieval with feedback or reread study guides. The experiment used repeated testing and repeated study across weeks, with a six-month retention check. Findings highlight how retrieval practice compares to common review habits in clinical training settings.

Alyssa Smith, a third-year medical student who uses evidence-based study strategies. She describes switching from cramming to spacing, interleaving, and retrieval practice. She explains using Anki, Sketchy-style visuals, DIY diagrams, and weekly schedules to manage heavy coursework. She encourages adopting these methods early to build durable long-term learning.

This episode was funded by The Wellcome Trust.Show Notes:Today's episode is the second of two episodes that we recorded specifically for parents. Our goal was to take what we know about the science of learning and focus on how it can be used by you - parents - to help your children with their learning and performance on tests, exams, and other types of assessments. We hope that these 2 episodes will be applicable to parents of a range of students, regardless of age and specific subject(s) being studied.You may be a parent of a child whose school is implementing effective strategies from cognitive psychology, or you may be interested in helping your child utilize these strategies at home even if they are not part of the school's regular practice. We talk about the strategies from both of these perspectives.In the previous episode, we talked about how parents can help their children with spaced practice and retrieval practice, and we touched on interleaving. In this episode, we talk about elaboration, concrete examples, and dual coding.Elaboration involves adding details to our memories. One way to do that is to simply have conversations with your children about topics that may relate to concepts that they have learned in class. You can also encourage elaborative interrogation by posing how and why questions. If your child isn't ready to answer them yet, that's OK - you can look up the answer together, or even ask their teachers.Concrete examples are important for your children to experience when trying to learn an abstract idea. Because concrete information is easier to understand and remember, finding and generating concrete examples for the abstract ideas they are studying will help your children learn more. It's important to ensure that your child understands the connection between the concrete example and the abstract idea, so that they don't just remember the example alone.Dual coding involves combining words and visuals to provide multiple ways for information to be understood and later remembered. You can help your children connects words and visuals by drawing with them, or having them describe a picture to you. However, it's important to note that this technique is not just for children who like art; be careful with labeling your child as a "visual learner", as this does not appear to be a useful categorization. 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