Natural science and engineering instructors' knowledge and practice of brain-based instruction in Ethiopian higher education institutions

Currently, the Brain-Based Instructional approach has become an alternative instructional method in the schooling system of different countries of the world. This study explored the current situation of natural science and engineering instructors' knowledge and practices of brain-based instruction in Ethiopian higher education institutions. A descriptive survey research design with concurrent mixed methods was employed. Data collection tools were developed based on the twelve principles of brain-based learning theory and confirmed their validity and reliability. Survey questions were used to gather quantitative data from 512 randomly selected instructors. Qualitative data were collected through interviews with 14 purposely selected instructors. Classroom observation was also conducted to triangulate data obtained through interviews and survey questions. Quantitative data were analyzed using descriptive statistics, whereas qualitative data were analyzed thematically. The findings of this study depict that most natural science and engineering instructors have good knowledge of brain-based instruction but not transferable knowledge and skills. There is a clear gap between instructors' knowledge and classroom practice of brain-based instruction. Thus, to improve instructional practices, higher education institutions need to work strongly to narrow the existing variation. Implications and further recommendations are also suggested.

Measuring the building blocks of everyday cognition: executive functions and relational reasoning

Measurement of the building blocks of everyday thought must capture the range of different ways that humans may train, develop, and use their cognitive resources in real world tasks. Executive function as a construct has been enthusiastically adopted by cognitive and education sciences due to its theorized role as an underpinning of, and constraint on, humans' accomplishment of complex cognitively demanding tasks in the world, such as identifying problems, reasoning about and executing multi-step solutions while inhibiting prepotent responses or competing desires. As EF measures have been continually refined for increased precision; however, they have also become increasingly dissociated from those everyday accomplishments. We posit three implications of this insight: (1) extant measures of EFs that reduce context actually add an implicit requirement that children reason using abstract rules that are not accomplishing a function in the world, meaning that EF scores may in part reflect experience with formal schooling and Western, Educated, Industrialized, Rich, Democratic (WEIRD) socialization norms, limiting their ability to predict success in everyday life across contexts, (2) measurement of relational attention and relational reasoning have not received adequate consideration in this context but are highly aligned with the key aims for measuring EFs, and may be more aligned with humans' everyday cognitive practices, but (3) relational attention and reasoning should be considered alongside rather than as an additional EF as has been suggested, for measurement clarity.

Transfer from spatial education to verbal reasoning and prediction of transfer from learning-related neural change

Current debate surrounds the promise of neuroscience for education, including whether learning-related neural changes can predict learning transfer better than traditional performance-based learning assessments. Longstanding debate in philosophy and psychology concerns the proposition that spatial processes underlie seemingly nonspatial/verbal reasoning (mental model theory). If so, education that fosters spatial cognition might improve verbal reasoning. Here, in a quasi-experimental design in real-world STEM classrooms, a curriculum devised to foster spatial cognition yielded transfer to improved verbal reasoning. Further indicating a spatial basis for verbal transfer, students' spatial cognition gains predicted and mediated their reasoning improvement. Longitudinal fMRI detected learning-related changes in neural activity, connectivity, and representational similarity in spatial cognition-implicated regions. Neural changes predicted and mediated learning transfer. Ensemble modeling demonstrated better prediction of transfer from neural change than from traditional measures (tests and grades). Results support in-school "spatial education" and suggest that neural change can inform future development of transferable curricula.

Relational Integration in the Human Brain: A Review and Synthesis

Relational integration is required when multiple explicit representations of relations between entities must be jointly considered to make inferences. We provide an overview of the neural substrate of relational integration in humans and the processes that support it, focusing on work on analogical and deductive reasoning. In addition to neural evidence, we consider behavioral and computational work that has informed neural investigations of the representations of individual relations and of relational integration. In very general terms, evidence from neuroimaging, neuropsychological, and neuromodulatory studies points to a small set of regions (generally left lateralized) that appear to constitute key substrates for component processes of relational integration. These include posterior parietal cortex, implicated in the representation of first-order relations (e.g., A:B); rostrolateral pFC, apparently central in integrating first-order relations so as to generate and/or evaluate higher-order relations (e.g., A:B::C:D); dorsolateral pFC, involved in maintaining relations in working memory; and ventrolateral pFC, implicated in interference control (e.g., inhibiting salient information that competes with relevant relations). Recent work has begun to link computational models of relational representation and reasoning with patterns of neural activity within these brain areas.