Sorry about the formatting.
First I will relay some points from a few other blogs that have been talking about Metacognition.
Then I will relate these to some Neuroscientific findings and some behavioural research.
I will make the point that Metacognition may be part heritable and affected by environment.
Metacognition is thinking about thinking, also called introspection.
It is useful in learning because it allows a learner to assess what they need to know in order to meet course goals or internal motivations. In a few blogs Metacognition has been talked about in depth. Duncan reported: “Craig et al (2006) found that
students who were asked “deep-level-reasoning questions” (questions based on
possibilities, such as hypothetical reasoning questions “If we change/do this, what
happens?”, and those asking for explanation of information “How does this work?”
rather than just recall) significantly outperformed those who were not asked any
questions when studying new material.” He explains this as increased mental
representation of the material gained from deeper processing, evidenced by longer
retention in long term memory (Craik & Lockhart, 1972).
Chris posted: “Knight and Wood (2005) looked into improving their biology
undergraduate course. To do this they used an hour less for lectures a week and
instead used that time for interactive learning and cooperative problem solving. They
found that this gave the students significantly higher learning gains (the difference
between pre and post-tests) and better conceptual understanding.”
A study by Fleming et al. (2010) looked at how well people judged whether they were
correct at guessing which of two light patches was the brighter. The task was adjusted
for individual ability, so that only the individual’s awareness of the accuracy of their
decision making ability was being measured. The researchers used MRI scans to find
that this metacognitive or introspective ability significantly correlated with the
amount of grey matter and the structure of the neighbouring white matter in a small
area of the anterior prefrontal cortex. This result could be due to innate differences in
brain function or the effects of experience and learning.
Knight and Wood observed that marking students on a curve discouraged them from working collaboratively. In addition,
students in ethnic minorities achieved a slightly lower average, but this was not significant.
Thinking of this, Metacognition may be one mediator of academic success but that it may be moderated by social factors.
Chris also stated that a course involving “practice with problem-solving, data analysis, and other
higher-order cognitive skills improved the performance of all students, but
particularly those from a disadvantaged background” (Haak, HilleRisLambers, Pitre, & Freeman, 2011).
This suggests that Metacognition could be more-or-less moderated by an environment-gene interaction similar to
that being researched in the fields of intelligence and personality.
Research reported in Science Daily by Baird et al. (2013) found that there are multiple
brain systems within the prefrontal cortex supporting Metacognition – “The ability to accurately reflect on perception is
associated with enhanced connectivity between the lateral region of the anterior
prefrontal cortex and the anterior cingulate, a region involved in coding uncertainty
and errors of performance.
In contrast, the ability to accurately reflect on memory is linked to enhanced
connectivity between the medial anterior prefrontal cortex and two areas of the brain:
the precuneus and the lateral parietal cortex, regions prior work has shown to be
involved in coding information pertaining to memories.”
Metacognitive systems in the prefrontal cortex could be functionally linked to systems of memory. A study by Tine (2013)
found that children who grew up in rural poverty scored lower on visual working
memory tests than those growing up in urban poverty. In contrast, urban poverty gave
a slightly lower score on verbal working memory. These differences were explained
by the researcher as relating to differences in the lives of the children. Rural areas
lacked visual stimuli such as traffic, crowds and signs, whereas noise pollution in
cities was cited as slightly hindering verbal working memory.
Metacognition is necessary for social behaviour. This extract of an abstract of a recent
meta-analysis explains the role of rest and non-attention in Metacognition:
“When people wakefully rest in the functional MRI scanner, their minds wander, and
they engage a so-called default mode (DM) of neural processing that is relatively
suppressed when attention is focused on the outside world. Accruing evidence
suggests that DM brain systems activated during rest are also important for active,
internally focused psychosocial mental processing, for example, when recalling
personal memories, imagining the future, and feeling social emotions with moral
connotations. Here the authors review evidence for the DM and relations to
psychological functioning, including associations with mental health and cognitive
abilities like reading comprehension and divergent thinking.”
Immordino-Yang et al, (2012).
Immordino-Yang’s review states quite a few things: that in people with stronger DM activity at rest there are higher scores on divergent thinking, reading comprehension and memory Li et al., 2009; Song et al., 2009; van den Heuvel, Stam, Kahn, & Hulshoff Pol, 2009; Wig et al., 2008), performance ability on cogntively-demanding attentional tasks. The level of long range and overall neural DM activity has been shown to be greater in those of high than average intelligence. Suggested is that children without adequate opportunity to play and teenagers without opportunity to quietly reflect may not do as well as others on these skills. That there is a gap still between disadvantaged students and others in the studies aforementioned alludes to this. Level of DM activity has also been shown to be lower in autistic and depressed people and higher in Schizophrenia. Schizophrenia and depression are linked to social factors.
References
Craik, F. I., & Lockhart, R. S. (1972). Levels of processing: A framework for memory
research. Journal of verbal learning and verbal behavior, 11(6), 671-684.
Fleming, S. M., Weil, R. S., Nagy, Z., Dolan, R. J., & Rees, G. (2010). Relating introspective accuracy
to individual differences in brain structure. Science, 329(5998), 1541-1543.
Immordino-Yang, M. H., Christodoulou, J. A., & Singh, V. (2012). Rest Is Not Idleness Implications
of the Brain’s Default Mode for Human Development and Education. Perspectives on Psychological
Science, 7(4), 352-364.
Knight, J. K., & Wood, W. B. (2005). Teaching more by lecturing less. Cell Biology Education, 4, 298-310. DOI: 10.1187/05–06–0082.
Tine, M. (2013). Working Memory Differences Between Children Living in Rural and Urban Poverty. Journal of Cognition and Development, (just-accepted).
University of California – Santa Barbara (2013, October 16). Brain connections underlying accurate introspection revealed. ScienceDaily. Retrieved October 25, 2013, from http://www.sciencedaily.com/releases/2013/10/131016100432.htm