Technology and the brain

There has been a lot of press coverage recently on how computer usage affects the brain. One of the main proponents of the view that there are negative effects is Baroness Susan Greenfield who believes that the predilection for online living causes shallow, fragmented thinking, “Computer use could be cutting attention spans, stifling imagination and hampering empathy, as a result, the parts of the brain involved in these traits will not develop properly.” Critics argue that her assertions are no more than speculative, with no scientific evidence to support it. A recent paper in Neuron written by cognitive scientists provides an overview of the evidence. They point out that "'technology is damaging the brain / eating our children / harming our culture’ stories are over-simplified to the point of absurdity. No-one could get away with a scare story about the whole of ‘transport’ but you can with ‘technology’ because it plays to our anxious stereotypes". It will be interesting to watch the debate unfold.

Children, Wired: For Better and for Worse

Daphne Bavelier, C. Shawn Green, Matthew W.G. Dye

Summary

Children encounter technology constantly at home and in school. Television, DVDs, video games, the Internet, and smart phones all play a formative role in children's development. The term technology subsumes a large variety of somewhat independent items, and it is no surprise that current research indicates causes for both optimism and concern depending upon the content of the technology, the context in which the technology immerses the user, and the user's developmental stage. Furthermore, because the field is still in its infancy, results can be surprising: video games designed to be reasonably mindless result in widespread enhancements of various abilities, acting, we will argue, as exemplary learning tools. Counterintuitive outcomes like these, besides being practically relevant, challenge and eventually lead to refinement of theories concerning fundamental principles of brain plasticity and learning.

Turn off the TV

Dynamic Treatment Effect Analysis of TV Effects on Child Cognitive Development
Fali Huang & Myoung-jae Lee

We investigate whether TV watching at ages 6-7 and 8-9 affects cognitive development measured by math and reading scores at ages 8-9 using a rich childhood longitudinal sample from NLSY79. Dynamic panel data models are estimated to handle the unobserved child-specific factor, endogeneity of TV watching, and dynamic nature of the causal relation. A special emphasis is put on the last aspect where TV watching affects cognitive development which in turn affects the future TV watching. When this feedback occurs, it is not straightforward to identify and estimate the TV effect. We adopt estimation methods available in the biostatistics literature which can deal with the feedback feature; we also apply the standard econometric panel data IV approaches. Overall, for math score at ages 8-9, we find that watching TV for more than two hours per day during ages 6-9 has a negative total effect
http://d.repec.org/n?u=RePEc:eab:develo:1532&r=cbe

Do Cognitive Skills Depend on Non-Cognitive Skills? And If So, What Does the Labour Market Reward?

In a previous post, I mentioned research on behavioural determinents of earnings by Bowles et al. (2001); these authors report that cognitive skills represent less than a fifth of the return to schooling. They suggest that the remaining 82% of the return to schooling could either be associated with more advanced cognitive skills that are not captured by basic measures, or with noncognitive skills. More recently, Pasche (2008) finds that over half the return to schooling is constituted of basic cognitive skills. Either way, the bias of non-cognitive personality traits is important when estimating the returns to education.

Research by Borghans, Meijers and ter Weel (reported at the AEA meeting earlier this month), examines the role of noncognitive skills in explaining cognitive test scores. They measure noncognitive skills both by personality traits and economic preference parameters; and the idea is that noncognitive skills might affect the effort people put into a test to obtain good results.

The authors experimentally varied the rewards for questions in a cognitive test to measure to what extent people are sensitive to financial incentives. To distinguish increased mental effort from extra time investments, they also varied the questions’ time constraints. Favourable personality traits such as high performance-motivation and an internal locus of control are associated with high test scores in the absence of rewards; which the authors say is consistent wiith trying as hard as possible.

In contrast, favourable economic preference parameters (low discount rate, low risk aversion) are associated with increases in time investments when incentives are introduced, consistent with a rational economic model in which people only invest when there are monetary returns.

The main conclusion of the research is that individual behavior in cognitive tests depends on noncognitive skills. This means that de-compositions of the returns to schooling may be biased towards cognitive skills in ways that have not been considered before. This underscores further the need to consider the bias of non-cognitive personality traits when estimating the returns to education.

Do Younger Students Do Better?

In a recent IZA working paper, Billari and Pellizzari show that the youngest students in an Italian university perform better compared to their oldest peers, particularly in the most technical subjects. They also find that the youngest students perform slightly better in cognitive tests and also appear to have less active social lives: they are less likely to do sports, go to discos and have romantic relationships. Based on this, Billari and Pellizzari suggest:

(i) a profile of cognitive development that might be decreasing already around age 20; (ii) psychological relative age effects that lead the youngest in a cohort to develop social skills (self-esteem, leadership) at a slower pace

Their conclusion is that younger students have less active social lives and devote more time to studying (which they say is backed up by additional evidence from the PISA study).