Category Archives: Research

Some skills needed for literacy may be developed in infancy: complex babble linked with better reading

A study published in PLOSOne is again something rather nice to know than showing us something new to do, infants capable of complex babble may grow into stronger readers, except it may help us in a future to identify reading disabilities at an early age.

From the press release:

Infants’ early speech production may predict their later literacy, according to a study published October 10, 2018 in the open-access journal PLOS ONE by Kelly Farquharson from Florida State University and colleagues.

Children with difficulties in identifying letters are more likely to develop reading impairments, but such difficulties cannot be uncovered until the child is 3 to 5 years old. The authors of the present study investigated whether assessing language ability even earlier, by measuring speech complexity in infancy, might predict later difficulties.

The authors tracked nine infants from English-speaking US families between the ages of 9 and 30 months. They recorded each infant’s babble as the child interacted with their primary caregiver, looking specifically at the consonant-vowel (CV) ratio, a demonstrated measure of speech complexity. The authors then met each child again when they were six years old to examine their ability to identify letters, a known predictor of later reading impairment.

They found that those children with more complex babble as infants performed better when identifying specific letters in their later reading test. Though the sample size was relatively small and all 9 children participating in this study all developed normally (meaning the range of variability was restricted), these results may indicate a link between early speech production and literacy skill.

The authors suggest that in the future, the complexity of infant babble may be useful as an earlier predictor of reading impairments in children than letter identification tests, enabling parents and professionals to earlier identify and treat children at risk of reading difficulties.

Farquharson adds: “This paper provides exciting data to support an early and robust connection between speech production and later literacy skills. There is clinical utility in this work – we are moving closer to establishing behavioral measures that may help us identify reading disabilities sooner.”

Abstract of the study:

Letter identification is an early metric of reading ability that can be reliability tested before a child can decode words. We test the hypothesis that early speech production will be associated with children’s later letter identification. We examined longitudinal growth in early speech production in 9 typically developing children across eight occasions, every 3 months from 9 months to 30 months. At each occasion, participants and their caregivers engaged in a speech sample in a research lab. This speech sample was transcribed for a variety of vocalizations, which were then transformed to calculate consonant-vowel ratio. Consonant-vowel ratio is a measure of phonetic complexity in speech production. At the age of 72 months, children’s letter knowledge was measured. A multilevel model including fixed quadratic age change and a random intercept was estimated using letter identification as a predictor of the growth in early speech production from 9–30 months, measured by the outcome of consonant-vowel ratio. Results revealed that the relation between early speech production and letter identification differed over time. For each additional letter that a child identified, their consonant-vowel ratio at the age of 9 months increased. As such, these results confirmed our hypothesis: more robust early speech production is associated with more accurate letter identification.

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How much English do non-english children learn outside the classroom?

This morning my colleague Vanessa De Wilde shared her first soon to be published scientific paper with me and I like to share the insights here too as they can be relevant to other people too. The study is soon to be published in Bilingualism: Language and Cognition and was co-authored by Marc Brysbaert and June Eyckmans.

I first want to share with you the abstract as it already summarizes the study clearly:

In this study we examined the level of English proficiency children can obtain through out-of- school exposure in informal contexts prior to English classroom instruction. The second aim was to determine the input types that fuel children’s informal language acquisition. Language learning was investigated in 780 Dutch-speaking children (aged 10-12), who were tested on their English receptive vocabulary knowledge, listening, speaking, reading and writing skills. Information about learner characteristics and out-of-school English exposure was gathered using questionnaires. The results show large language gains for a substantial number of children but also considerable individual differences. The most beneficial types of input were gaming, use of social media and speaking. These input types are interactive and multimodal and they involve language production. We also found that the various language tests largely measure the same proficiency component.

But I want to share some of the findings more in depth:

“The mean score for the receptive vocabulary test was 65% (53% when cognates were left out of the test), attesting to the degree of vocabulary that can be acquired when children areexposed repeatedly to a language through activities that do not focus on language learning but on the negotiation of meaning (e.g. while playing a game).”

“English is seen as a high-status language by the participants in our study (733 participants answered they think English is a fun language, only 27 claimed not to like English), which probably means that they enjoy engaging in (digital) interactions in English.”

“…our findings show the high divergence in the scores obtained, a finding that was also present in Lefever (2010). About a quarter of the students did not pick up much English (yet). ”

A considerable part of the differences in test results could be explained by the amount of exposure the children had received (exposure to the language explained 22% of the variability in the children’s overall proficiency scores). Other variables likely to be involved are individual differences in intelligence and language aptitude (Paradis, 2011; Sun, Steinkrauss, Tendeiro & De Bot 2016; Unsworth, Persson, Prins & De Bot, 2014), which unfortunately could not be addressed in the present study.

“…the two most regularly investigated in studies on contextual learning in a formal context did not turn out to be the most important. These are reading L2 books and watching subtitled television programs. Although both variables are positively correlated with L2 knowledge, the correlations are much lower than those of three other variables.”

“The three most important types of input for children’s language proficiency were: use of social media in English, gaming in English, and speaking English. These three types of exposure are the types which offer ample opportunities for social interaction and authentic communication in contrast with watching television, listening to music, and reading, which are far less interactive. Apparently, passive perception of a language is less effective than active use of the language,…”

“…listening to English music seems to have a negative influence on children’s contextual language learning, when the effects of the other variables are partialled out. This is in line with the finding that productive and multimodal types of input are more effective. The fact that the negative effect is significant is probably due to the nature of the input. Listening or even singing along to a song does not necessarily lead to understanding and learning the language. Furthermore, it takes away time from other activities that are more effective. At the same time, even though the variable is significant, it only explains some 1% of the variation.”

 

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Again: more young people are choosing not to drink alcohol

It’s something often overlooked but what can be found in many countries: young people are drinking less alcohol. But a news study shows that young people in England aren’t just drinking less alcohol, more of them are never taking up alcohol at all, and that the increase is widespread among young people.

From the press release:

Researchers at University College London analysed data from the annual Health Survey for England and found that the proportion of 16-24 year olds who don’t drink alcohol has increased from 18% in 2005 to 29% in 2015.

The authors found this trend to be largely due to an increasing number of people who had never been drinkers, from 9% in 2005 to 17% in 2015. There were also significant decreases in the number of young people who drank above recommended limits (from 43% to 28%) or who binge drank (27% to 18%). More young people were also engaging in weekly abstinence (from 35% to 50%)

Dr Linda Ng Fat, corresponding author of the study said: “Increases in non-drinking among young people were found across a broad range of groups, including those living in northern or southern regions of England, among the white population, those in full-time education, in employment and across all social classes and healthier groups. That the increase in non-drinking was found across many different groups suggests that non-drinking may becoming more mainstream among young people which could be caused by cultural factors.”

Dr Ng Fat said: “These trends are to be welcomed from a public-health standpoint. Factors influencing the shift away from drinking should be capitalised on going forward to ensure that healthier drinking behaviours in young people continue to be encouraged.”

Dr Linda Ng Fat added: “The increase in young people who choose not to drink alcohol suggests that this behaviour maybe becoming more acceptable, whereas risky behaviours such as binge drinking may be becoming less normalised.”

Increases in non-drinking however were not found among ethnic minorities, those with poor mental health and smokers suggesting that the risky behaviours of smoking and alcohol continue to cluster.

The researchers examined data on 9,699 people aged 16-24 years collected as part of the Health Survey for England 2005-2015, an annual, cross-sectional, nationally representative survey looking at changes in the health and lifestyles of people across England. The authors analysed the proportion of non-drinkers among social demographic and health sub-groups, along with alcohol units consumed by those that did drink and levels of binge drinking.

The authors caution that the cross-sectional, observational nature of this study does not allow for conclusions about cause and effect.

Abstract of the study:

Background
Non-drinking among young people has increased over the past decade in England, yet the underlying factor driving this change is unknown. Traditionally non-drinking has been found to be associated with lower socio-economic status and poorer health. This study explores among which sub-groups non-drinking has increased, and how this correlates with changes in drinking patterns, to identify whether behaviours are becoming more polarised, or reduction is widespread among young people.

Methods
Among participants aged 16 to 24 years (N = 9699), within the annual cross-sectional nationally-representative Health Survey for England 2005–2015 datasets, the following analyses were conducted: 1) The proportion of non-drinkers among social-demographic and health sub-groups by year, and tests for linear trends among sub-groups, adjusting for age were calculated. In pooled analyses, an interaction between year and each variable was modelled in sex- and age-adjusted logistic regression models on the odds of being a non-drinker versus drinker 2) At the population level, spearman correlation co-efficients were calculated between the proportion non-drinking and the mean alcohol units consumed and binge drinking on the heaviest drinking day, by year. Ordinary least squares regression analyses were used, modelling the proportion non-drinking as the independent variable, and the mean units/binge drinking as the dependent variable.

Results
Rates of non-drinking increased from 18% (95%CI 16–22%) in 2005 to 29% (25–33%) in 2015 (test for trend; p < 0.001), largely attributable to increases in lifetime abstention. Not drinking in the past week increased from 35% (32–39%) to 50% (45–55%) (p < 0.001). Significant linear increases in non-drinking were found among most sub-groups including healthier sub-groups (non-smokers, those with high physical activity and good mental health), white ethnicity, north and south regions, in full-time education, and employed. No significant increases in non-drinking were found among smokers, ethnic minorities and those with poor mental health. At the population-level, significant negative correlations were found between increases in non-drinking and declines in the mean units consumed (ρ = − 0.85, p < 0.001), and binge drinking (ρ = − 0.87, p < 0.001).

Conclusion
Increases in non-drinking among young people has coincided with a delayed initiation into alcohol consumption, and are to be welcomed. Future research should explore attitudes towards drinking among young people.

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Can rationality be enhanced through education?

Short answer: yes! This is an interesting study but with also an element of frustration. The study ticks many boxes (Randomized controlled trial, big sample,…) and it has clear results. So what’s to complain? Well, the why. How education enhances rationality? But I can live with this frustration as the researchers have found something very relevant – and because there are some theories about that why-question. Oh, and how would this affect boys as the study is only conducted with girls?

From  the press release:

There has been interest across behavioral and social sciences – including psychology, economics and education – in whether people are born to be rational decision-makers or if rationality can be enhanced through education.

Published in Science, a new study led by Hyuncheol Bryant Kim, assistant professor of policy analysis and management at Cornell University, found that education can be leveraged to help enhance an individual’s economic decision-making quality or economic rationality.

“Using a randomized controlled trial of education support and laboratory experiments that mimic real-life examples, we established causal evidence that an education intervention increases not only educational outcomes but also economic rationality in terms of measuring how consistently people make decisions to seek their economic goals,” Kim said.

Kim and his colleagues examined this hypothesis through a controlled trial of education support in Malawi, arranged by a nongovernmental organization, which provided financial support for education in a sample of nearly 3,000 female (2812 to be precise) ninth and 10th graders.

“We found that those who took part in the education intervention had higher scores of economic rationality, suggesting that education is a tool for enhancing an individual’s economic decision-making quality,” Kim said. “While we know that schooling has been shown in previous work to have positive effects on a wide range of outcomes, such as income and health, our work provides evidence of potentially additional benefits coming from improvements in people’s decision-making abilities.”

Traditional economic analysis assumes that humans make rational choices. However, mounting evidence shows that people tend to make systematic errors in judgment and decision-making and that there is a high level of diversity in how rational individuals are.

Kim points out that most other research on improving the quality of decision-making targets the reduction of decision biases. For example, behavioral economists have urged policymakers to intervene in markets and restructure choice environments, the way that a decision is presented, without restraining people’s freedom of choice.

“We take a different stand: proper policy tools can enhance general capabilities of decision making,” Kim said. “Education can better equip people for high-quality decision-making for their lives.”

“Governments must never neglect investments in human capital of their citizens,” he said, noting that Malawi is ranked one of the lowest in the world in human capital – the economic value of citizens. “In addition, this evidence provides an additional rationale for investment in education in resource constrained settings such as Malawi and other developing nations.”

Abstract of the study:

Schooling rewards people with labor market returns and nonpecuniary benefits in other realms of life. However, there is no experimental evidence showing that education interventions improve individual economic rationality. We examine this hypothesis by studying a randomized 1-year financial support program for education in Malawi that reduced absence and dropout rates and increased scores on a qualification exam of female secondary school students. We measure economic rationality 4 years after the intervention by using lab-in-the-field experiments to create scores of consistency with utility maximization that are derived from revealed preference theory. We find that students assigned to the intervention had higher scores of rationality. The results remain robust after controlling for changes in cognitive and noncognitive skills. Our results suggest that education enhances the quality of economic decision-making.

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Yes, retrieval and testing does work, but what limits the effect? Insights from a new meta-analysis

A new meta-analysis does confirm memory retrieval can be beneficial for learning, but also shows there are limits:

  • the frequency and difficulty of questions.
  • Simply asking a question is not enough; students must respond to see a positive effect on learning

Probably you now want to know how much is too much? Well, you’re in for a bit of a disappointment I’m afraid, as you can learn from the press release which explains it better than the original paper imho:

“Frequency is a critical factor. There appears to be a trade-off in how often you test students,” Chan said. “If I lecture nonstop throughout class, this lessens their ability to learn the material. However, too many questions, too often, can have a detrimental effect, but we don’t yet know exactly why that happens or how many questions is too many.”

The answer to that question may depend on the length of the lecture and the type or difficulty of the material, Chan said. Given the different dynamics of a class lecture, it may not be possible to develop a universal lecture-to-question ratio. Regardless, Chan says testing students throughout the lecture is a simple step instructors at any level and in any environment can apply to help students learn.

“This is a cheap, effective method and anyone can implement it in their class,” he said. “You don’t need to give every student an iPad or buy some fancy software – you just need to ask questions and have students answer them in class.”

Chan, Christian Meissner, a professor of psychology at Iowa State; and Sara Davis, a postdoctoral fellow at Skidmore College and former ISU graduate student, examined journal articles from the 1970s to 2016 detailing more than 150 different experiments for their analysis. The researchers looked at what factors influenced the magnitude of this effect, when it happens and when the effect is reversed.

Why testing helps

There are several explanations as to why testing students is beneficial for new learning. The researchers evaluated four main theories for the meta-analysis to examine the strengths and weakness of these explanations from the existing research. The data strongly supported what researchers called the integration theory.

“This theory claims that testing enhances future learning by facilitating the association between information on the test and new, especially related, information that is subsequently studied, leading to spontaneous recall of the previously tested information when they learn related information,” Meissner said. “When this testing occurs, people can better tie new information with what they have learned previously, leading them to integrate the old and the new.”

Learning new information requires an encoding process, which is different from the process needed to retrieve that information, the researchers explained. Students are forced to switch between the two when responding to a question. Changing the modes of operation appears to refocus attention and free the brain to do something different.

A majority of the studies in the analysis focused on college students, but some also included older adults, children and people with traumatic brain injuries. The researchers were encouraged to find that testing could effectively enhance learning across all these groups.

“Memory retrieval can optimize learning in situations that require people to maintain attention for an extended period of time. It can be used in class lectures as well as employee training sessions or online webinars,” Davis said. “Future research could examine factors that can maximize this potential.”

Abstract of the meta-analysis:

A growing body of research has shown that retrieval can enhance future learning of new materials. In the present report, we provide a comprehensive review of the literature on this finding, which we term test-potentiated new learning. Our primary objectives were to (a) produce an integrative review of the existing theoretical explanations, (b) summarize the extant empirical data with a meta-analysis, (c) evaluate the existing accounts with the meta-analytic results, and (d) highlight areas that deserve further investigations. Here, we identified four nonexclusive classes of theoretical accounts, including resource accounts, metacognitive accounts, context accounts, and integration accounts. Our quantitative review of the literature showed that testing reliably potentiates the future learning of new materials by increasing correct recall or by reducing erroneous intrusions, and several factors have a powerful impact on whether testing potentiates or impairs new learning. Results of a metaregression analysis provide considerable support for the integration account. Lastly, we discuss areas of under-investigation and possible directions for future research.

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Using AI to discover learning disabilities in children

Whenever you hear or read artificial intelligence one starts to dream. Ok, I admit: I do. Every time I use Siri I’m reminded what a long way we still have to go, except for when my children ask silly questions. But this study uses AI in a whole different way and way more serious: to check if the humans made a mistake when labelling a child with learning disabilities.

From the press release:

Scientists using machine learning – a type of artificial intelligence – with data from hundreds of children who struggle at school, identified clusters of learning difficulties which did not match the previous diagnosis the children had been given.

The researchers from the Medical Research Council (MRC) Cognition and Brain Sciences Unit at the University of Cambridge say this reinforces the need for children to receive detailed assessments of their cognitive skills to identify the best type of support.

The study, published in Developmental Science, recruited 550 children who were referred to a clinic – the Centre for Attention Learning and Memory – because they were struggling at school.

The scientists say that much of the previous research into learning difficulties has focussed on children who had already been given a particular diagnosis, such as attention deficit hyperactivity disorder (ADHD), an autism spectrum disorder, or dyslexia. By including children with all difficulties regardless of diagnosis, this study better captured the range of difficulties within, and overlap between, the diagnostic categories.

Dr Duncan Astle from the MRC Cognition and Brain Sciences Unit at the University of Cambridge, who led the study said: “Receiving a diagnosis is an important landmark for parents and children with learning difficulties, which recognises the child’s difficulties and helps them to access support. But parents and professionals working with these children every day see that neat labels don’t capture their individual difficulties – for example one child’s ADHD is often not like another child’s ADHD.

“Our study is the first of its kind to apply machine learning to a broad spectrum of hundreds of struggling learners.”

The team did this by supplying the computer algorithm with lots of cognitive testing data from each child, including measures of listening skills, spatial reasoning, problem solving, vocabulary, and memory. Based on these data, the algorithm suggested that the children best fit into four clusters of difficulties.

These clusters aligned closely with other data on the children, such as the parents’ reports of their communication difficulties, and educational data on reading and maths. But there was no correspondence with their previous diagnoses. To check if these groupings corresponded to biological differences, the groups were checked against MRI brain scans from 184 of the children. The groupings mirrored patterns in connectivity within parts of the children’s brains, suggesting that that the machine learning was identifying differences that partly reflect underlying biology.

Two of the four groupings identified were: difficulties with working memory skills, and difficulties with processing sounds in words.

Difficulties with working memory – the short-term retention and manipulation of information – have been linked with struggling with maths and with tasks such as following lists. Difficulties in processing the sounds in words, called phonological skills, has been linked with struggling with reading.

Dr Astle said: “Past research that’s selected children with poor reading skills has shown a tight link between struggling with reading and problems with processing sounds in words. But by looking at children with a broad range of difficulties we found unexpectedly that many children with difficulties with processing sounds in words don’t just have problems with reading – they also have problems with maths.

“As researchers studying learning difficulties, we need to move beyond the diagnostic label and we hope this study will assist with developing better interventions that more specifically target children’s individual cognitive difficulties.”

Dr Joni Holmes, from the MRC Cognition and Brain Sciences Unit at the University of Cambridge, who was senior author on the study said: “Our work suggests that children who are finding the same subjects difficult could be struggling for very different reasons, which has important implications for selecting appropriate interventions.”

The other two clusters identified were: children with broad cognitive difficulties in many areas, and children with typical cognitive test results for their age. The researchers noted that the children in the grouping that had cognitive test results that were typical for their age may still have had other difficulties that were affecting their schooling, such as behavioural difficulties, which had not been included in the machine learning.

Dr Joanna Latimer, Head of Neurosciences and Mental Health at the MRC, said: “These are interesting, early-stage findings which begin to investigate how we can apply new technologies, such as machine learning, to better understand brain function. The MRC funds research into the role of complex networks in the brain to help develop better ways to support children with learning difficulties.”

Abstract of the paper:

Our understanding of learning difficulties largely comes from children with specific diagnoses or individuals selected from community/clinical samples according to strict inclusion criteria. Applying strict exclusionary criteria overemphasizes within group homogeneity and between group differences, and fails to capture comorbidity. Here, we identify cognitive profiles in a large heterogeneous sample of struggling learners, using unsupervised machine learning in the form of an artificial neural network. Children were referred to the Centre for Attention Learning and Memory (CALM) by health and education professionals, irrespective of diagnosis or comorbidity, for problems in attention, memory, language, or poor school progress (n = 530). Children completed a battery of cognitive and learning assessments, underwent a structural MRI scan, and their parents completed behavior questionnaires. Within the network we could identify four groups of children: (a) children with broad cognitive difficulties, and severe reading, spelling and maths problems; (b) children with age‐typical cognitive abilities and learning profiles; (c) children with working memory problems; and (d) children with phonological difficulties. Despite their contrasting cognitive profiles, the learning profiles for the latter two groups did not differ: both were around 1 SD below age‐expected levels on all learning measures. Importantly a child’s cognitive profile was not predicted by diagnosis or referral reason. We also constructed whole‐brain structural connectomes for children from these four groupings (n = 184), alongside an additional group of typically developing children (n = 36), and identified distinct patterns of brain organization for each group. This study represents a novel move toward identifying data‐driven neurocognitive dimensions underlying learning‐related difficulties in a representative sample of poor learners.

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6 studies and insights every student needs to know!

Today Filip Raes shared these 6 tweets with the world – and I helped him with some of them:

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More research on how to dispel myths: redirect

As professional myth busters, Paul, Casper and myself are always interested in how to beat them. This new study confirms and at the same time nuances a previous insight: those on the fence about an idea can be swayed after hearing facts related to the misinformation. Do note that as often is the case: this study was on a relatively small sample.

From the press release:

After conducting an experimental study, the researchers found that listening to a speaker repeating a belief does, in fact, increase the believability of the statement, especially if the person somewhat believes it already. But for those who haven’t committed to particular beliefs, hearing correct information can override the myths.

For example, if a policymaker wants people to forget the inaccurate belief that “Reading in dim light can damage children’s eyes,” they could instead repeatedly say, “Children who spend less time outdoors are at greater risk to develop nearsightedness.” Those on the fence are more likely to remember the correct information and, more importantly, less likely to remember the misinformation, after repeatedly hearing the correct information. People with entrenched beliefs are likely not to be swayed either way.

The sample was not nationally representative, so the researchers urge caution when extrapolating the findings to the general population, but they believe the findings would replicate on a larger scale. The findings, published in the academic journal Cognition, have the potential to guide interventions aimed at correcting misinformation in vulnerable communities.

“In today’s informational environment, where inaccurate information and beliefs are widespread, policymakers would be well served by learning strategies to prevent the entrenchment of these beliefs at a population level,” said study co-author Alin Coman, assistant professor of psychology at Princeton’s Woodrow Wilson School of Public and International Affairs and Department of Psychology.

Coman and Madalina Vlasceanu, a graduate student at Princeton, conducted a main study, with a final total of 58 participants, and a replication study, with 88 participants.

In the main study, a set of 24 statements was distributed to participants. These statements, which contained eight myths and 16 correct pieces of information in total, fell into four categories: nutrition, allergies, vision and health.

Myths were comprised of statements commonly endorsed by people as true, but that are actually false, such as “Crying helps babies’ lungs develop.” The correct and related piece of information would be: “Pneumonia is the prime cause of death in children.”

First, the participants were asked to carefully read these statements, which were described as statements “frequently encountered on the internet.” After reading, participants rated whether they believed the statement was true on a scale from one to seven (one being “not at all” to seven being “very much so.”) Next, they listened to an audio recording of a person remembering some of the beliefs the participants had read initially. In the recording, the speaker spoke naturally, as someone would recalling information. The listeners were asked to determine whether the speakers were accurately remembering the original content. Each participant listened to an audio recording containing two of the correct statements from each of two categories.

Participants were then given the category name — nutrition, allergies, vision, or health — and were instructed to recall the statements they first read. Finally, they were presented with the initial statements and asked to rate them based on accuracy and scientific support.

The researchers found that listeners do experience changes in their beliefs after listening to information shared by another person. In particular, the ease with which a belief comes to mind affects its believability.

If a belief was mentioned by the person in the audio, it was remembered better and believed more by the listener. If, however, a belief was from the same category as the mentioned belief (but not mentioned itself), it was more likely to be forgotten and believed less by the listener. These effects of forgetting and believing occur for both accurate and inaccurate beliefs.

The results are particularly meaningful for policymakers interested in having an impact at a community level, especially for health-relevant inaccurate beliefs. Coman and his collaborators are currently expanding upon this study, looking at 12-member groups where people are exchanging information in a lab-created social network.

Abstract of the study:

Belief endorsement is rarely a fully deliberative process. Oftentimes, one’s beliefs are influenced by superficial characteristics of the belief evaluation experience. Here, we show that by manipulating the mnemonic accessibility of particular beliefs we can alter their believability. We use a well-established socio-cognitive paradigm (i.e., the social version of the selective practice paradigm) to increase the mnemonic accessibility of some beliefs and induce forgetting in others. We find that listening to a speaker selectively practicing beliefs results in changes in believability. Beliefs that are mentioned become mnemonically accessible and exhibit an increase in believability, while beliefs that are related to those mentioned exrience mnemonic suppression, which results in decreased believability. Importantly, the latter effect occurs regardless of whether the belief is scientifically accurate or inaccurate. Furthermore, beliefs that are endorsed with moderate-strength are particularly susceptible to mnemonically-induced believability changes. These findings, we argue, have the potential to guide interventions aimed at correcting misinformation in vulnerable communities.

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Another take on bilingualism: children take longer to learn two languages at once compared to just one

You can often read about the benefits of being bilingual from a young age. This study does take another turn and show it’s a bit more complicated than that for sure also for migrant children. How complicated?

Bilingual children from immigrant families often lag monolingual children in the development of the majority language while also having poor skills in their heritage language, even when SES is controlled. This may reflect, in part, internal limits to how rapidly children can learn two languages simultaneously, but the circumstances in which children are exposed to two languages in the immigrant context are far from a perfect test of that internal capacity. Monolingual children with native parents and bilingual children in immigrant families differ in ways besides the number of languages they hear. In bilingual environments, children hear less of each language, and the quality of their exposure to the majority language is often less because their sources of that language may have limited proficiency. In addition, bilingual children in bilingual environments can choose the language they speak, and when one language is more prestigious than the other, they choose the more prestigious language.

From the press release:

Worldwide immigration patterns are increasing the number of children who grow up exposed to two languages, a circumstance that provides numerous benefits as well as some challenges. Because bilingual children’s input is divided between two languages – the majority language of the country where they reside and their family’s heritage language – on average, they receive less input in each language compared to children who receive all of their input in just one language. As a result, bilingual children develop each language at a slower pace because their learning is spread across two languages.

A leading psychologist and language development expert at Florida Atlantic University says, “Don’t worry,” and reassures parents, teachers and clinicians that it is perfectly normal for bilingually developing children to take longer because they are learning more. In a review published in the journal Child Development Perspectives, Erika Hoff, Ph.D., a psychology professor and director of the Language Development Laboratory in FAU’s Charles E. Schmidt College of Science, examined research on the course of dual language growth among children in immigrant families. She focused on children exposed to two languages from birth and identified quantity of input, quality of input, and children’s use of language as factors that influence language growth.

Hoff’s review of the research shows strong evidence that the rate of language growth is influenced by the quantity of language input. Her findings challenge the belief, held in and out of scientific circles that children are linguistic sponges who quickly absorb the language or languages they hear and will become proficient speakers of two languages so long as they are exposed to both at an early age.

“One clear implication of studies of bilingual children is that we should not expect them to be two monolinguals in one,” said Hoff. “The bilingual child, like the bilingual adult, will develop competencies in each language ‘to the extent required by his or her needs and those of the environment.'”

The findings indicate that the quality of language exposure is also important. Hoff argues that immigrant parents should use the language they are most comfortable speaking when they interact with their children. They should not be told to use English just because it is the language of the host country if their own English proficiency is limited.

“To support bilingual development fully, children’s exposure to each language should come from highly proficient speakers,” Hoff said.

The research shows that children also need to use a language in order to acquire it. In bilingual environments, children can choose the language they speak, and when one language is more prestigious than the other, they choose the more prestigious language. Bilingual development is supported when both the host and heritage languages are valued by society and children have opportunities that encourage them to use both languages.

Prior research has shown that French-English bilingualism is achieved more successfully in Canada than is Spanish-English bilingualism in the United States, and that the equal prestige of the two languages in Canada plays a role. In Canada, children also may have greater access to highly proficient speakers of both languages because both languages are national languages.

“Children from immigrant families need strong skills in the majority language to succeed in school, and they need skills in the heritage language to communicate well with their parents and grandparents,” said Hoff. “Bilingualism is an asset for interpersonal, occupational, and cognitive reasons. Children who hear two languages from birth can become bilingual, even if that outcome is not guaranteed.”

Hoff’s findings suggest that bilingual children’s competencies, in addition to reflecting their communicative needs, also reflect the quantity and quality of their exposure to each language.

“These findings repeat conclusions from studies of monolingual development that language acquisition depends on the quantity and quality of language experience and the opportunity to participate in conversation,” said Hoff.

Abstract of the study:

Early exposure to two languages is widely thought to guarantee successful bilingual development. Contradicting that belief, children in bilingual immigrant families who grow up hearing a heritage language and a majority language from birth often reach school age with low levels of skill in both languages. This outcome cannot be explained fully by influences of socioeconomic status. In this article, I summarize research that helps explain the trajectories of observed dual language growth among children in immigrant families in terms of the amount and quality of their language exposure as well as their own language use.

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A small but positive effect size of enquiry-based STEM-program (best evidence in brief)

There is a new Best Evidence in Brief and this study may surprise some:

With the increasing interest in STEM (science, technology, engineering, and math) curricula comes the need for evidence backing these programs. One such science program is The BSCS Inquiry Approach, a comprehensive high school science approach based on three key concepts: constructivism, coherence, and cohesiveness. The materials are built around the 5E process (engage, explore, explain, elaborate, and evaluate). Teaching focuses on evaluating students’ current understanding and using inquiry methods to move them to higher understandings. Each of the science disciplines (physical science, life science, earth science, and science and society) is composed of four chapters that repeat common themes, which advance over a three-year period. Designing and carrying out experiments in small groups is important in all topics. Teachers receive seven days of professional development each year, including a three-day summer institute and four one-day sessions, enabling sharing of experiences and introducing new content over time.
To determine the effects of The BSCS Inquiry Approach on student achievement, BSCS conducted a two-year cluster-randomized study of the intervention that compared students in grades 10-11 in nine experimental (n=1,509 students) and nine control high schools (n=1,543 students) in Washington State. A total of 45% of students qualified for free or reduced-price lunches. At the end of two years, the BSCS students scored higher than controls (effect size=+0.09, p<.05) on the Washington State Science Assessments.
I checked the actual approach and it’s 3underpinnings:
  • Students come to the classroom with preconceptions that shape their learning,
  • student competence requires a deep foundation of knowledge, as well as an understanding of how this knowledge relates to a framework,
  • and that students benefit from explicitly monitoring and taking control of their own learning

And if you look closer it is anything but enquiry with minimal guidance:

This study does show that there is much more possible between sometimes extreme poles in educational discussions.

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