Connecting Levels of Analysis in Educational Neuroscience: A Review of Multi-level Structure of Educational Neuroscience with Concrete Examples

Han, Hyemin; Soylu, Fırat; Anchan, Mona

doi:10.31234/osf.io/czf2j

Cited by 3 publications

(4 citation statements)

References 19 publications

(20 reference statements)

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“…However, the responsibility for this effort has created issues of agency. When researchers assume the responsibility, we characterize the effort as “researcher-initiated.” Han et al (2019) model this approach by assembling interdisciplinary research teams representing multiple perspectives to find where and how neuroscience can inform educators. In contrast, when the responsibility shifts to teachers for finding applications, we characterize this effort as “teacher-initiated,” which increases their agency.…”

Section: Discussionmentioning

confidence: 99%

Neuroscience Concepts Changed Teachers’ Views of Pedagogy and Students

et al. 2021

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Advances in neuroscience reveal how individual brains change as learning occurs. Translating this neuroscience into practice has largely been unidirectional, from researchers to teachers. However, how teachers view and incorporate neuroscience ideas in their classroom practices remains relatively unexplored. Previously fourteen non-science teachers participated in a 3-week three credit graduate course focusing on foundational ideas in neuroscience. The current work was undertaken to gain insight into if and how individual teachers choose to later apply the proposed set of educational neuroscience concepts (ENCs) in their classrooms. This qualitative follow-up study examined commonalities in how teachers of diverse ages and subjects utilized their new neuroscience understandings. To this end, a year after the course, all participants assessed their perceived usefulness of the ENCs in a survey. Six of those teachers permitted classroom observations and participated in interviews that focused on how the ENCs may have influenced their lesson planning and teaching. The survey revealed that irrespective of subject areas or grade levels taught, teachers found the ENCs useful as organizing principles for their pedagogy now and in the future. Overall teachers estimated that the ENCs’ influence on lesson design had increased from 51% prior to the course to an estimated 90% for future lessons. A cross-case analysis of classroom observations and interviews revealed how teachers used ENCs to inform their pedagogical decisions, organize actions in their classroom, influence their understanding of students, and respond to individual contexts. Teachers recognized the importance of student agency for engaging them in the learning process. The ENCs also offered teachers explanations that affirmed known practices or helped justify exploring untried techniques. The foundational neuroscience concepts offered a small group of teachers a lens to reconsider, re-envision and re-design their lessons. Some teachers applied these ideas more broadly or frequently than others. This case study provided insights into how teachers can directly apply neuroscience knowledge to their practice and views of students.

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Section: Discussionmentioning

confidence: 99%

Neuroscience Concepts Changed Teachers’ Views of Pedagogy and Students

et al. 2021

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“…This concrete example in moral education may demonstrate how findings from neuroimaging studies can inform the development of interventions to promote moral values in educational settings. As shown, neuroscientific research focusing on psychological processes associated with values and virtues can inform us, who are interested in developing effective interventions, which processes should be aimed in the interventions (Han et al, 2019;Kelly & O'Connell, 2020). Likewise, at the practical level, neuroscience can make significant contributions to designing educational programs and policies to promote desirable public value with empirical evidence (Han et al, 2019).…”

Section: Potential Contributions Of Neuroscientific Studies To Research On Public Valuementioning

confidence: 99%

Public Value, Psychology, and Neuroscience

Han¹

2021

Korea Assoc Public Value

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Research on public value is inevitably interdisciplinary in its nature due to its aim and purpose. Both philosophical and empirical approaches are necessary to conduct such research in a successful manner. In the present paper, I intend to discuss the importance of empirical approaches in research on public values, particularly psychological and neuroscientific approaches, with concrete examples. I proposed that such empirical approaches are essential in better understanding the processes and mechanisms associated with how people address issues associated with public value in the modern society. Also, I overviewed how the psychological and neuroscientific approaches contribute to practical aspects related to public value, such as policy making and education. Based on the aforementioned points, I briefly discussed directions for future research in research on public value as an interdisciplinary field.

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“…Related to the improvement of smart cities, which is the main focus of the current edited volume, examining the developmental trajectories of political purpose with an advanced computational method, the deep learning method, will provide scholars, educators, and policy makers with useful insights [6,13]. We are primarily interested in how to improve citizens' quality of life by implementing smart city solutions based on computational methods, including but not limited to, smart transportation, smart surveillance, smart health solutions, smart infrastructure, and smart energy.…”

Section: Introductionmentioning

confidence: 99%

“…educators and policy makers who are interested in predicting future outcomes with the aforementioned methodological benefits [13]. Furthermore, by more accurately modeling data, the deep learning method will be able to contribute to future follow-up research projects.…”

mentioning

confidence: 99%

Applying Deep Learning to Predict Civic Purpose Development: Within the Smart City Context

Han¹

2021

Preprint

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We applied the deep learning method, which has been developed in the fields of computer and data science for accurate prediction, to predict political purpose development during emerging adulthood. We tested whether deep learning more accurately predicted Wave 2 political purpose with Wave 1 predictors compared with traditional regression. A convolutional neural network consisting of two dense and dropout layers was trained to predict the outcome variable. For comparison, we also estimated a multinomial logistic regression model. The result demonstrated that deep learning outperformed traditional regression in general while effectively minimizing overfitting. Moreover, from exploratory analysis, we found that deep learning might be able to model the non-linear relationship between the predictors and outcome variable. Based on the findings, we discussed the implications of the present study within the context of improving citizens’ lives in smart cities.

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Connecting Levels of Analysis in Educational Neuroscience: A Review of Multi-level Structure of Educational Neuroscience with Concrete Examples

Cited by 3 publications

References 19 publications

Neuroscience Concepts Changed Teachers’ Views of Pedagogy and Students

Neuroscience Concepts Changed Teachers’ Views of Pedagogy and Students

Public Value, Psychology, and Neuroscience

Applying Deep Learning to Predict Civic Purpose Development: Within the Smart City Context

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