Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

In mathematically literate societies, numerical information is represented in 3 distinct codes: a verbal code (i.e., number words); a digital, symbolic code (e.g., Arabic numerals); and an analogical code (i.e., quantities; Dehaene, 1992). To communicate effectively using these numerical codes, our understanding of number must involve an…

For today's societies trying to cope with the current globally increased competition, existence of individuals who can take risks, solve problems and adopt changes an innovation has gained more importance when compared to the past. This situation brings responsibility to educational institutions for increasing the number of innovative individuals…

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy…

The phenomenon of AM (animal metaphor) can be discussed based on the class-inclusion model in cognitive linguistics. In this article, we try to prove that this kind of metaphor accords more with this model than with correspondence model of Lakoff. It does not mean that the correspondence model is not valid in this regard, but we argue that…