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Abstract: Intelligent tutoring systems often make use of students’ answers to adapt instruction or feedback on a task. In this paper, we explore the alternative possibility of adapting a system based on the perceived affective and cognitive state of a student. A system can potentially better adapt to the needs of each individual student by using non-verbal behavior. We used a new experimental paradigm inspired by ‘brain training’ software to collect primary school children’s answers to easy and difficult arithmetic problems and made audiovisual recordings of their answers. Adult observers rated these films on perceived difficulty level. Results showed that adults were able to correctly interpret children’s perceived level of difficulty, especially if they saw their face (compared to hearing their voice). They paid attention to features such as ‘looking away’, and ‘frowning’. Then we checked whether we could also automatically predict if the posed problem was either easy or difficult based on the first second of their response. This ‘thin-slice analysis’ could correctly predict the difficulty level in 71% of all cases. When trained on sufficiently many recordings, Adaptive Tutoring Systems should be able to detect children’s state and adapt the difficulty level of their learning materials accordingly. [Copyright &y& Elsevier]

Abstract: Cognitive Robotics can be defined as the study of cognitive phenomena by their modeling in physical artifacts such as robots. This is a very lively and fascinating field which has already given fundamental contributions to our understanding of natural cognition. Nonetheless, robotics has to date addressed mainly very basic, low-level cognitive phenomena like sensory-motor coordination, perception, and navigation, and it is not clear how the current approach might scale up to explain high-level human cognition. In this paper we argue that a promising way to do that is to merge current ideas and methods of ‘embodied cognition’ with the Russian tradition of theoretical psychology which views language not only as a communication system but also as a cognitive tool, that is by developing a Vygotskyan cognitive robotics. We substantiate this idea by discussing several domains in which language can improve basic cognitive abilities and permit the development of high-level cognition: learning, categorization, abstraction, memory, voluntary control, and mental life. [Copyright &y& Elsevier]

Abstract: The majority of previous computational models of high-order human cognition incorporate gradient descent algorithms for their learning mechanisms and strict error minimization as the sole objective of learning. Recently, however, the validity of gradient descent as a descriptive model of real human cognitive processes has been criticized. In the present paper, we introduce a new framework for descriptive models of human learning that offers qualitatively plausible interpretations of cognitive behaviors. Specifically, we apply a simple multi-objective evolutionary algorithm as a learning method for modeling human category learning, where the definition of the learning objective is not based solely on the accuracy of knowledge, but also on the subjectively and contextually determined utility of knowledge being acquired. In addition, unlike gradient descent, our model assumes that humans entertain multiple hypotheses and learn not only by modifying a single existing hypothesis but also by combining a set of hypotheses. This learning-by-combination has been empirically supported, but largely overlooked in computational modeling research. Simulation studies show that our new modeling framework successfully replicated important observed psychological phenomena. [Copyright &y& Elsevier]

This paper argues that expertise can be used as an indicator of consciousness in humans and other animals. The argument is based on the following observations: (1) expertise and skill acquisition require deliberate practice; and (2) the characteristics of deliberate practice such as performance evaluation against a more proficient model, retention of voluntary control over actions, self-monitoring, goal-setting, error-detection and correction, and the construction of hierarchically organized retrieval structures are outside of the currently understood bounds of unconscious processing. Thus, to the extent that evidence of expertise exists in an organism, evidence of conscious experience is also present. Two important implications arise from this conclusion: (1) evidence of expertise can be used as the basis for cross-species comparisons of consciousness; and (2) the evolution of human consciousness can be assessed using fossil evidence of skilled behavior as a measure of consciousness. [Copyright &y& Elsevier]