Laptops in Class are the New Second-Hand Smoke

3-Star learning experiences

Paul A. Kirschner

laptops1

OK; I’ve covered taking notes with or without laptops and whether people learn better if they read from paper or screen. This is the third blog in an apparent, unplanned, trilogy.

Disclaimer: Let’s sketch/frame the situation so there are no misunderstandings. Yes, I know that using a computer (e.g., laptop, tablet, smartphone) can be effective in certain situations so this blog isn’t plea for pure lecture or totally banning the use of laptops in schools. Yes, of course, there are situations where it’s necessary to use a laptop in the class, so add this to the previous. And finally, yes, some teachers can be boring but that’s not a reason to do something else in the class than learn.

Let’s start with an analogy. You’re a non-smoker and you go out to eat in a restaurant, catch a ride with someone in a car, or are…

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New study on smartphone use and academic performance (spoiler: it’s bad)

This morning big news in our Belgian media about a new study by Stijn Baert and his colleagues in which they checked the impact of smartphone usage on the academic performance of the students:

In this study, we contributed to recent literature concerning the association between smartphone use and educational performance by providing the first causal estimates of the effect of the former on the latter. To this end, we analysed unique data on 696 first-year university students in Belgium. We found that a one-standard-deviation increase in their overall smartphone use yields a decrease in their average exam score of about one point (out of 20). This negative relationship is robust to the use of alternative indicators of smartphone use and academic performance. As our results add to the literature evidence for heavy smartphone use not only being associated with lower exam marks but also causing lower marks, we believe that policy-makers should at least invest in information and awareness campaigns to highlight this trade-off.

I have to admit that I do think that while the researchers have taken a lot into account, there always still can be something else maybe causing this differences. The researchers have attempted to bypass this:

This study is the first to attempt to measure the causal impact of (overall) smartphone use on educational performance. To this end, we exploit data from 696 first-year students at two Belgian universities, who were surveyed in December 2016 using multiple scales on smartphone use as well as predictors of this smartphone use and a battery of questions concerning (potential) other drivers of success at university. This information is merged with the students’ scores on their first exams, taken in January 2017. We analyse the merged data by means of instrumental variable estimation techniques. More concretely, to be able to correctly identify the influence of smartphone use on academic achievement, in a first stage, the respondents’ smartphone use is predicted by diverging sets of variables that are highly significantly associated with smartphone use, but not directly associated with educational performance. In a second stage, the exam scores are regressed on this exogenous prediction of smartphone use and the largest set of control variables used in the literature to date.

In the interview this morning on the radio, the researchers didn’t plea for a total ban of smartphones, but still think it can be a very important element for students to take into consideration.

Abstract of the study:

After a decade of correlational research, this study is the first to measure the causal impact of (general) smartphone use on educational performance. To this end, we merge survey data on general smartphone use, exogenous predictors of this use, and other drivers of academic success with the exam scores of first-year students at two Belgian universities. The resulting data are analysed with instrumental variable estimation techniques. A one-standard-deviation increase in daily smartphone use yields a decrease in average exam scores of about one point (out of 20). When relying on ordinary least squares estimations, the magnitude of this effect is substantially underestimated.

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Funny on Sunday: Little did we know… (+ 2 extra)

I have this great cartoon for you, but also 2 extra’s

I also tweeted something myself in reaction to stable genius gate:

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Interesting interview with John Hattie: “I’m a statistician, I’m not a theoretician”

This Hattie-interview by Hanne Knudsen is very interesting although I think some statisticians will frown if they read the quote used as title “I’m a statistician, I’m not a theoretician”.

It advice to read the full article, but this excerpt explains the quote more in dept:

…if I had known that it would go to an audience larger than just researchers, I probably would have had a whole lot more of theory in it. I had never dreamed it would catch on like this, so you are right, it is quite devoid of theory in terms of how it is written. I am a measurement researcher, I am a statistician, I am not a theoretician, so I haven’t written a lot of theory. But of course I have a very strong model of teaching. I have worked for many years with some of the more well-known people on the theoretical side of teaching around the world. But you are right, it did not come through, and sometimes I think I should write a book about teaching as a profession – which indeed I am doing right now. I get accused more of not taking into account sociology, and the background of kids. Of course I think that is very critical, but the book was never written for that kind of general notion. You are right, it is a criticism, and maybe I should write something more theoretical, but it is not really my strength. I do have some very strong theories on how theory works and the concept of teaching. It just didn’t come through in the book

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Does VR help to learn? Well, this app doesn’t seem to.

I have to admit: despite the fact that I get sick every time I’m using virtual reality goggles, I really think VR and augmented reality (AR) is just impressive. But… does it help learning. It is too early to tell, but this study by Makransky et al that I found via a tweet by Paul Kirschner is pretty clear: in this study VR doesn’t improve learning . The study is extra interesting as it looks at some important principles for learning such as the redundancy principle (Mayer was involved in the study), and while the students did get more motivated, the learning was not better (even worse). Do note that the the amount of participants was pretty low: 52 (22 males and 30 females) students from a large European university.

Also interesting is to know what application the researchers were using:

The virtual simulation used in this experiment was on the topic of mammalian transient protein expression and was developed by the simulation development company, Labster. It was designed to facilitate learning within the field of biology at a university level by allowing the user to virtually work through the procedures in a lab by using and interacting with the relevant lab equipment and by teaching the essential content through an inquiry-based learning approach.

In short:

 

  • The consequences of adding immersive virtual reality to a simulation was examined.
  • The impact of the level of immersion on the redundancy principle was investigated.
  • EEG was used to obtain a direct measure of cognitive processing during learning.
  • Students reported higher presence but learned less in the immersive VR condition.
  • Students also had higher cognitive load based on EEG in the immersive VR condition.

Abstract of the study:

Virtual reality (VR) is predicted to create a paradigm shift in education and training, but there is little empirical evidence of its educational value. The main objectives of this study were to determine the consequences of adding immersive VR to virtual learning simulations, and to investigate whether the principles of multimedia learning generalize to immersive VR. Furthermore, electroencephalogram (EEG) was used to obtain a direct measure of cognitive processing during learning. A sample of 52 university students participated in a 2 × 2 experimental cross-panel design wherein students learned from a science simulation via a desktop display (PC) or a head-mounted display (VR); and the simulations contained on-screen text or on-screen text with narration. Across both text versions, students reported being more present in the VR condition (d = 1.30); but they learned less (d = 0.80), and had significantly higher cognitive load based on the EEG measure (d = 0.59). In spite of its motivating properties (as reflected in presence ratings), learning science in VR may overload and distract the learner (as reflected in EEG measures of cognitive load), resulting in less opportunity to build learning outcomes (as reflected in poorer learning outcome test performance).

 

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Funny on Sunday: your horoscope for 2018

Have a great year!

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The power of families eating together

It’s very hard to examine if the correlation between families eating together and a better life for children and adolescents later on is a causal relation. It could well be that other elements play a role that cause both the better health and the chance of eating together. This new Canadian study doesn’t deliver the smoking gun, but does add some weight to the idea that eating together as a family can be very powerful.

From the press release:

“There is a handful of research suggesting positive links between eating family meals together frequently and child and adolescent health,” Pagani said. “In the past, researchers were unclear on whether families that ate together were simply healthier to begin with. And measuring how often families eat together and how children are doing at that very moment may not capture the complexity of the environmental experience.”

The study looked at chilldren who had been followed by researchers since they were 5 months old as part of the Quebec Longitudinal Study of Child Development. At age 6, their parents started reporting on whether or not they had family meals together. At age 10, parents, teachers and the children themselves provided information on the children’s lifestyle habits and their psycho-social well-being.

“We decided to look at the long-term influence of sharing meals as an early childhood family environment experience in a sample of children born the same year,” Pagani said, “and we followed-up regularly as they grew up. Using a birth cohort, this study examines the prospective associations between the environmental quality of the family meal experience at age 6 and child well-being at age 10.”

When the family meal environment quality was better at age 6, higher levels of general fitness and lower levels of soft-drink consumption were observed at age 10. These children also seemed to have more social skills, as they were less likely to self-report being physical aggressive, oppositional or delinquent at age 10.

“Because we had a lot of information about the children before age 6 — such as their temperament and cognitive abilities, their mother’s education and psychological characteristics, and prior family configuration and functioning — we were able to eliminate any pre-existing conditions of the children or families that could throw a different light on our results,” said Harbec. “It was really ideal as a situation.”

Added Pagani: “The presence of parents during mealtimes likely provides young children with firsthand social interaction, discussions of social issues and day-to-day concerns, and vicarious learning of prosocial interactions in a familiar and emotionally secure setting. Experiencing positive forms of communication may likely help the child engage in better communication skills with people outside of the family unit. Our findings suggest that family meals are not solely markers of home environment quality, but are also easy targets for parent education about improving children’s well-being.”

“From a population-health perspective, our findings suggest that family meals have long-term influences on children’s physical and mental well-being,” said Harbec.

At a time when fewer families in Western countries are having meals together, it would be especially opportune now for psycho-social workers to encourage the practice at home — indeed, even make it a priority, the researchers believe. And family meals could be touted as advantageous in public-information campaigns that aim to optimize child development.

Abstract of the study:

Objective:

Past research suggests a positive link between family meals and child and adolescent health. Although researchers have often relied on how often families eat together, this may not capture the complexity of the experience. Using a birth cohort, this study examines the prospective associations between the environmental quality of the family meal experience at age 6 years and child well-being at age 10.

Methods:

Participants are 1492 children of the Quebec Longitudinal Study of Child Development. When children were age 6, parents reported on their typical family meal environment quality. At age 10, parents, teachers, and children themselves provided information on lifestyle habits, academic achievement, and social adjustment, respectively. The relationship between early family meal environment quality and later child outcomes was analyzed using a series of multivariate linear regression.

Results:

Family meal environment quality at age 6 predicted higher levels of general fitness and lower levels of soft drink consumption, physical aggression, oppositional behavior, nonaggressive delinquency, and reactive aggression at age 10. These relationships were adjusted for child characteristics (sex, temperament problems and cognitive abilities, and baseline body mass index [BMI]) and family characteristics (family configuration and functioning, maternal education, depression, and BMI).

Conclusion:

From a population-health perspective, our findings suggest that family meals have long-term influences on children’s biopsychosocial well-being. At a time when family meal frequency is on a natural decline in the population, this environmental characteristic can become a target of home-based interventions and could be featured in information campaigns that aim to optimize child development.

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Funny on Sunday: Stanley, the spare reindeer

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by | December 24, 2017 · 9:31 am

An antidote to a paper warning you for wifi (and other examples of junk science)

I really like science, I like the self-correcting part of science even more.

Check this paper that was published by Sage and Burgio earlier this year:

Mobile phones and other wireless devices that produce electromagnetic fields (EMF) and pulsed radiofrequency radiation (RFR) are widely documented to cause potentially harmful health impacts that can be detrimental to young people. New epigenetic studies are profiled in this review to account for some neurodevelopmental and neurobehavioral changes due to exposure to wireless technologies. Symptoms of retarded memory, learning, cognition, attention, and behavioral problems have been reported in numerous studies and are similarly manifested in autism and attention deficit hyperactivity disorders, as a result of EMF and RFR exposures where both epigenetic drivers and genetic (DNA) damage are likely contributors. Technology benefits can be realized by adopting wired devices for education to avoid health risk and promote academic achievement.

Sounds pretty alarming, no? Should we worry? Well, no.

The respected journal Child Development recently published a commentary that attributed a number of negative health consequences to RF radiation, from cancer to infertility and even autism (Sage Burgio, 2017). It is our view that this piece has potential to cause serious harm and should never have been published. But how do we justify such damning verdict? In considering our responses, we
realized that this case raised more general issues about distinguishing scientically valid from invalid views when evaluating environmental impacts on physical and psychological health, and we offer here some more general guidelines for editors and reviewers who may be confronted with similar issues. As shown in Table 1, we identify seven questions that can be asked about causal claims, using the Sage and Burgio (2017) article to illustrate these.
That’s right David Grimes and Dorothy Bischop took a closer look to the alarming article, and well…

Abstract of the paper by David Grimes and Dorothy Bischop that can be downloaded here:

Exposure to nonionizing radiation used in wireless communication remains a contentious topic in the public mindwhile the overwhelming scientic evidence to date suggests that microwave and radio frequencies used in modern communications are safe, public apprehension remains considerable. A recent article in Child Development has caused concern by alleging a causative connection between nonionizing radiation and a host of conditions, including autism and cancer. This commentary outlines why these claims are devoid of merit, and why they should not have been given a scientic veneer of legitimacy. The commentary also outlines some hallmarks of potentially dubious science, with the hope that authors, reviewers, and editors might be better able to avoid suspect scientic claims.

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How useful are twin studies for measuring heritability of educational achievement? More than one might think!

I posted already several studies that linked heritability to study success, check e.g. here and here. The way this kind of research is conducted is that the researchers look at twin studies, comparing monozygotic and dizygotic twins. But how useful is this approach? This new study wanted to examine precisely this by (re)examining Dutch data, and maybe surprising: very. Check this quote from the conclusion:

In the Netherlands, the results of a national educational achievement test, the Eindtoets basisonderwijs, partly determine the level of secondary education suitable for a child. Several twin studies have looked at the heritability of individual indifferences on this test, but due to self-selection bias and possible differences in singletons and twins, these results might not generalize to the general population of Dutch pupils. Here we determined the heritability of test scores using population-wide census data. For the estimation, pedigree-based mixed models were used, a method borrowed from the field of animal genetics. We found a heritability of 0.94. When corrected for several school-related covariates, this estimate dropped to 0.85. How does this fairly high heritability estimate compare to that based on twin studies?

A few studies have been done on the same phenotype in the same birth cohort of Dutch children. For example, Bartels et al. (2002) conducted a twin study of 1,495 Dutch twins from the NTR from the birth cohorts 1998–2001 on the sum scores of the same test investigated here at age 12 (Eindtoets basisonderwijs). They found that genetic influences explained 57% of the variance in test scores and environmental influences 43%. Twenty-seven percent of the environmental variance could be explained by common-environmental influences and 16% by unique-environmental influences. Schwabe et al. (2016) analyzed the sum scores of 990 Dutch twin pairs from a similar birth cohort (1997–2000) from the NTR but also investigated the effect of the sex of a twin and specific covariates (i.e., school denomination, pedagogical philosophy, school size). Similar to the findings of Bartels et al. (2002), the results suggested that differences in test scores can be explained mainly by genetic influences (66%). Interestingly, while the heritability estimate dropped from 0.94 to 0.85 in the census-based analysis, including covariates did not change the heritability estimate in the Schwabe et al. (2016) study. This might be explained by the lower statistical power of the Schwabe et al. (2016) study, leading also to a lower variance of the covariate distribution: For example, 74% of the twins followed regular education and the school’s denomination was Roman-Catholic for 31% of the twins.

Overall, the results of twin studies imply that individual differences in the scores on the Eindtoets Basisonderwijstest can be largely explained by genetic differences: Estimated heritability ranges from 60% (Bartels et al., 2002) up to 74% (de Zeeuw et al., 2016). Earlier research furthermore suggests that the finding of a high heritability can be generalized not only to the total score of the Eindtoets Basisonderwijs, but also to its subscales (see e.g., de Zeeuw et al., 2016Schwabe et al., 2017). When we compare these heritability estimates to the estimate of 85% in this study, we can conclude that the high estimates resulting from the twin method are not simply an artifact of self-selection or because of any important difference between twins and singletons. Twin-based heritability estimates are not inflated, since an estimate based on a sample from the entire population (including twins and singletons) is even higher.

Of course there are limitations to this study, as always, and also as always more research is needed, but this seems an important element to the discussion. (H/T @SteveStuWill)

Abstract of the study:

As for most phenotypes, the amount of variance in educational achievement explained by SNPs is lower than the amount of additive genetic variance estimated in twin studies. Twin-based estimates may however be biased because of self-selection and differences in cognitive ability between twins and the rest of the population. Here we compare twin registry based estimates with a census-based heritability estimate, sampling from the same Dutch birth cohort population and using the same standardized measure for educational achievement. Including important covariates (i.e., sex, migration status, school denomination, SES, and group size), we analyzed 893,127 scores from primary school children from the years 2008–2014. For genetic inference, we used pedigree information to construct an additive genetic relationship matrix. Corrected for the covariates, this resulted in an estimate of 85%, which is even higher than based on twin studies using the same cohort and same measure. We therefore conclude that the genetic variance not tagged by SNPs is not an artifact of the twin method itself.

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