Marina Bakalova

Assuming that music can be expressive, I try to answer the question whether musical expressiveness has epistemic value. The article has six parts. In the first part, I provide examples of what music can express. I suggest that it can express inner states with phenomenal character. In the second part, I build up an argument in favor of the claim that, granted its expressiveness, music can convey conceptual content which is not verbal, and which cannot be expressed verbally. This conclusion is limited to concepts like lyrical, nostalgic, melancholy, joyful, distressful etc. In the third part, I explain what musical expressive content is, in contrast and by analogy to, propositional content. In the fourth part, I apply Mitchell Green’s multi- space model of artistic expression to music. I argue that Green’s theory of expression provides a powerful explanation of how a musical sequence can express states with phenomenal character. In the fifth part, I use that model to define adequacy conditions for musical expressive ascriptions. In the last part, I attempt to explain musical knowledge by combining Green’s multi-space model with Sosa-style virtue epistemology.

Whitehead believed that education must give us ideas that are usable in our actual lives. This line of thought is naturally provoked by the significant abundance of inert ideas that people pile up though education. The main reason for that, I claim, is the wrong focus of traditional education. It aims at producing individuals that would deliver high results on exams and tests. I take Whitehead’s claim the education must put emphasis on usable ideas as my starting point. I give a specific interpretation of useable ideas as abilities or functions. This provides a ground for connecting Whiteheadian thought to an already existing educational platform, offered by Nel Noddings. Noddings develops a cognitive theory of education which places cognitive structures (I assume a robust analogy between structures, functions, and abilities) in the center of educational concern. At the end of the paper, I estimate some consequences from adopting the terminology of functions for connecting between human and machine learning.

This paper reveals the importance of learning emotion concepts due to the efficiency of emotional granularity during the categorization of emotions. There are two ways of learning emotion concepts that can contribute to emotional granularity. First, we can learn emotion words. Second, we can learn the implicit content of our emotion concepts, i.e. how emotions feel to us. In order to complete the second task, we need to acquire vivid awareness and vivid memory of the implicit content of our emotion concept. I claim that only after completing the second task can we learn emotion words in a way that is efficient for the categorization of emotions. The problem with that claim is that we do not know how to study the implicit content of our emotions, and how to obtain vivid awareness of it. In this article, I sketch a basic solution to this problem. The article has three parts. In the first part, I outline Lisa Barrett’s Conceptual Act View in order to reveal the functional role of emotion concepts in our brains. In the second part, I explain Anna Wierzbicka’s classical attempt to define emotion concepts. In the third part, I suggest how it is possible to study the fine-grained details of our emotional experience in a scientific way. The goal of developing the integrative model is to realize the learner's potential in personalized knowledge formation in an intelligent learning environment and to enhance the efficiency of learning.