Educational Neuroscience

PS507: Educational Neuroscience EDUCATIONAL NEUROSCIENCE What is Educational Neuroscience? Education + Psychology + Neuroscience What: vision is to bring together these three disciplines to promote better learning in the classroom Why: generate research that can provide an account of learning and teaching, which can form education Education is about enhancing learning, and neuroscience is about understanding the mental processes involved in learning There has been exploitation with programmes which claim to tell teachers how to engage their pupils’ brains o Little basis in actual scientific research o Potentially harmful/hinder students’ learning Teachers should be able to gain accurate and useful scientific information in an accessible manner Build up evidence that explains what works best in the classroom, some of which are things that teachers are already doing Neuromyths in Education Where do they originate? Early 2000s with advertisement of brain-based learning, stemming from an over-literal interpretation of research findings (e.g. hemispheric specialisation) Lots of theoretical progress in understanding the neurocognitive development underpinning educational skills (e.g. numeracy, literacy) In the UK, there is a prevalence of neuromyths among teachers o E.g. most teachers believe that students should learn by following their preferred learning styles; differences in how the left and right brain work can inform different styles of learning PS507: Educational Neuroscience Pseudo-neuroscience found in many schools Many of these concepts are unscientific and educationally unhelpful Need to clearly communicate messages combining scientific and educational understanding to teachers Neuromyth # 1: left brain vs right brain There is a difference between left brain thinking and right brain thinking Individuals differ in the extent to which they favour either the ‘left-brain’ or the ‘right-brain’ There is some science behind it as different brain regions are associated with different styles of activity Nielsen et al. 2013 o Analysis of brain scans from over 1,000 individuals at rest o Presence of brain lateralization in relation to some tasks (e.g. language) o No evidence to support the notion that people are intrinsically left or right sided in how their brains worked Impact on teaching and education o Some people are better (or more suited) than others to certain tasks because of brain structure o ‘Whole-brain learning’ approach ▪ Including both analytical and creative aspects in a task ▪ May keep students attentive for longer and provide more opportunities for learning ▪ But not based on good science Neuromyth #2: boys vs. girls • • • • Girls and boys show different aptitudes in key cognitive skills (e.g. girls are better at creative tasks, boys are better at science/maths) Group differences look at averages – what do they tell us about individuals? Some gender differences might exist o Males outperform females on tests of mental rotation, which involve comparing pictures of 3D objects in different orientations and deciding if they are the same or different (Voyer et al., 1995) o Females outperform males on word fluency, where participants were asked to think of as many examples as they can of a certain category (Weiss et al., 2008) Janet Hyde (2005): the ‘gender similarities hypothesis’ o Analysis of 46 meta-analysis that examined around 7m people on gender differences across different behaviours o 78% of the studies showed gender differences to be small or negligible o The same applies to data on children (Leahey & Guo, 2000) o Differences tend to be larger for attitudes towards the discipline than for performance (Quest et al., 2010) PS507: Educational Neuroscience • Impact on teaching and education o Spencer, Steele and Quinn (1999) – maths test in college students ▪ Men outperformed women when they were told that the test usually reveals gender differences ▪ No such difference emerged when they were told it was a gender fair test o Parents hold lower expectations for their daughters’ maths success than for their sons’ (Lummis & Stevenson, 1990) o Parent ratings of their children’s competence in maths strongly predicts their children’s own beliefs about their academic competency (Herbert & Stipek, 2005) o Masculinity prevents academic achievement: boys in the UK systematically under-perform in comparison to girls (Forde et al., 2006) o Focus on changing expectations around gender o Group differences are small and not relevant to academic potential Neuromyth #3: learning styles • • • • • • • We learn more effectively when taught via our preferred ‘learning style’ Students have different preferences for how learning material is presented When material is presented in a way that suits a learner’s preference, learning is somehow enhanced o Over 96% of British teachers believe in this principle The VARK questionnaire: how do I learn best? Learning style hypothesis (Pashler et sl., 2008) o Visual learners learn best with visual instructional methods o Verbal learners learn best with verbal instructional methods Husmann and O’Loughlin 2018: o 426 anatomy students completed the VARK questionnaire and a study strategy survey o Student performance in anatomy was not correlated with heir score in any VARK categories o Specific study strategies, such as practising microscope work and using lecture notes, were associated with better grade performance, regardless of the students’ learning style If there is no compelling evidence, why is the idea of learning styles so popular? o Most learning styles taxonomies are ‘type’ theories: people are classified in groups (rather than assigning people graded scores on different dimensions) – and people like to find out ‘what type of person one is’ o People are seen and treated by educators as unique individuals o Everybody has the potential to lean effectively and easily o Responsibility (i.e. external locus of control) PS507: Educational Neuroscience • • • • • • Is what learners say they prefer good for them? o The learner is assumed to ‘know’ what is best for them o Would this be a justified reason to give children the food they prefer? ▪ E.g. many children will prefer sweets to vegetables Clark (1982) found in a meta-analysis of studies that learner preference was typically uncorrelated or negatively correlated to learning s=and learning outcomes o This means that learners who reported preferring a particular instructional technique typically did not benefit from being taught in that technique Constantinidou and Baker (2002) found no relationship between a visual learning style and the actual learning of verbal items that were presented either visually or auditory Massa and Mayer (2006) also found no support for the idea that different instructional methods, emphasizing either pictorial or verbal information, should be used for visualisers and verbalisers Cook, Thompson an, Thomas and Thomas (2009) found no support for the idea that different instructional methods, (inductive vs deductive), should be used for concrete learners and abstract learners. So, should we completely give up on tailoring our teaching styles? o Research shows that learning is improved (for almost everyone) by combining different activities – such as drawing alongside more passive study (Schmek et al., 2014) o Expertise reversal effect (Kalyga et al., 2010): depending on their level of expertise, learners benefit from different instructional techniques. Neuromyth #4: the stereotypical teen • • • Before: teenage behaviour was almost entirely down to hormonal changes in puberty Now: we know that adolescence is a critical period of neurological change, much of which is responsible for the unique characteristics of adolescent behaviour There is a strong need to establish connections with peers, to connect and obtain their approval ‘Teenagers are risk-takers’ • • • • Some adolescent-typical behaviours are common across species, culture and history o Adolescent mice drink more alcohol when they are with other mice (Logue et al., 2004) Gardner & Steinberg (2005): in a laboratory driving game, adolescents took more driving risks when they were in the presence of their peers Relative to adults, adolescents are more susceptible to the influence of their peers in risky situations. Adolescents have greater brain activity in reward-related brain regions (ventral striatum and orbitofrontal cortex) when peers were watching o The activity in these regions was a predictor of risk taking. PS507: Educational Neuroscience • • • The presence of peers increase risk taking among adolescents but not adults Blakemore (2018): social risk weighs more strongly than any other risk during adolescence - thus going along with peers might be seen as more favourable than facing social exclusion Teenagers are hypersensitive to social exclusion (Sebastian et al., 2010) o Significant decline in mood after social exclusion ‘Teenagers are melodramatic’ • • • Development of the limbic system during adolescence o Structural changes: amygdala and hippocampus increase in volume during puberty (Goddings et al., 2014) o Functional changes: fronto-limbic connectivity undergoes developmental changes during adolescence (Gee et al., 2013; Gabard-Durnam et al., 2014) o Hormonal influences on the limbic system: pubertal development has a key role on the structural changes observed (Goddins et al., 2014) o These changes can provide an explanation to why teenagers appear as ‘melodramatic’. Subcortical natural systems typically associated with affective responding (e.g., amygdala) are thought to mature earlier than the regions that adults use to regulate affective responses (e.g., prefrontal cortex, PFC) Gee et al., 2013: Developmental shift in functional connectivity between amygdala and mPFC What have we learned so far? o Adolescence is a sensitive period of social development o Adolescence is also a period of heightened vulnerability to mental health problems o Potential substantial effect on brain and behavioural development during adolescence Coronavirus: impact on young people o The TELL study explored subjective experiences of the COVID-19 pandemic and lockdown in the UK among 109 16-19-year-olds during May 2020 o Heightened emotionality o Uncertainty, time of change, missing out o Frustration and mistrust o Personal growth and development o Positive thinking o Self-care strategies o Togetherness o What do the TELL studies mean for education settings? o Mixed feelings about returning to education o Provide support for the future o Provide time for social engagement and team building PS507: Educational Neuroscience o Guidance in talking about difficult emotions o Talk about self-care and coping with difficult situations