In this blog post, the last post of my post series, I intend to outline, by means of concrete examples, how findings from neuroscience can contribute practically to the improvement of education. As a prior teacher in moral education in Korean secondary schools, I was interested in how to effectively promote students’ motivation to engage in prosocial behavior, such as voluntary service activity, through classroom activities.
Given that many sections of moral education textbooks featured stories of moral exemplars, morally great people, to elevate and inspire students and let them emulate presented exemplary behavior, I decided to examine how to improve the effectiveness of the aforementioned exemplar-applied educational method. In fact, unfortunately, when I introduced such stories, especially historic moral figures, such as Mother Teresa and Martin Luther King Jr., in my classes, students did not seem to be strongly elevated or motivated. So, I planned to work on an educational intervention study in a classroom setting to find a way to address this issue associated with the utilization of moral exemplars in moral education.
I designed my classroom intervention to effectively promote motivation to engage in voluntary service activities based on what I had found from my neuroimaging studies. As I reviewed in my previous blog post, I meta-analyzed previous fMRI studies of moral functioning and conducted an fMRI experiment examining the interaction between self-related and morality-related brain regions. Findings demonstrated that self-related psychological processes are closely involved in moral functioning in general. Given these findings, I hypothesized that the perceived closeness of presented exemplars from students’ perspectives, in other words, the perceived connectivity between the exemplars and the students’ selfhood, would influence the motivational impact of the exemplars. Following a previous social psychological study examining the effectiveness of different types of non-moral exemplars, I examined whether attainable and relevant exemplars, such as peers, friends, and family members, more effectively motivated students to engage in voluntary service activities when compared with unattainable and irrelevant models, such as historic figures that had been frequently presented in textbooks. Students were presented with different types of exemplars for eight weeks, and their service engagement was measured before and after the intervention period. As I hypothesized, students assigned to the peer exemplar group showed significantly greater improvement in service engagement compared with their counterparts assigned to the historic figure group. This result was consistent with what I found in my neuroimaging study, that selfhood matters in moral functioning. It may suggest that moral educators and school teachers consider introducing moral exemplars who are close to the students to effectively promote their moral motivation, since these exemplars are likely to be perceived as attainable and relevant.
Some educators and educational policy-makers may also be interested in how neuroscience can inform the improvement of education in practice at the macroscopic level. Educational interventions can influence students’ developmental trajectories for the long-term. Thus, even if small-scale interventions, such as the aforementioned classroom intervention, are found to produce positive outcomes, scaling up such intervention programs should be done very carefully. Of course, the best way to address this question is to conduct multiple long-term, large-scale experiments at the district level or even the national level, to examine whether the developed interventions effectively work in diverse environments. However, doing so might not be realistic in many cases due to the limitations in time, money and resources, and potential ethical issues. To deal with these limitations, computer simulation based on data collected from relatively small-scale studies can be informative. My computer simulation articles introduced how to estimate long-term effects of different types of educational interventions using the data collected from my classroom experiment. My computer simulation model was developed to examine what type of intervention can produce the best outcome and how often the intervention should be conducted to produce meaningful effects over the long term. Thanks to the rapid development of computer science, now it is possible to make a more precise simulation model based on deep learning, which is originally inspired by neuroscience. Compared with the traditional model, the accuracy of the deep learning-applied model is greater than 6% when predicting the outcomes of educational interventions. Given these considerations, methodologies in computer science and neuroscience can help us better simulate outcomes of educational interventions based on small datasets before the actual application of developed interventions in wider settings. Such methodological advances will be able to assist educational policy making processes.
So far, I discussed how we, educators, can learn from neuroscience to improve education in practice. My blog post series started with an overview of neuroscience and education, I then offered an introduction to how to identify using neuroscientific evidence the core psychological processes associated with learning. Finally I have now discussed the application of neuroscience to education in practice and to educational policy making. Although the studies introduced in the series are somehow preliminary, the methodologies used in the studies might inform researchers and educators who want to apply findings in neuroscience to education.
Image: Cuban schoolchildren in a classroom in the province of Guantánamo. Photo by Mikhail Evstafiev, Source Wikipedia