Facilitating peer knowledge modeling: Effects of a knowledge awareness tool on collaborative learning outcomes and processes
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In an empirical study, we provided (or not) pairs of students working in a remote collaborative learning situation with a knowledge awareness tool that provided learner A with learner B’s level of knowledge measured through a pre-test. We analyzed the effe ...
Using each other's knowledge and expertise in learning - what we call cooperation in learning- is one of the major existing methods to reduce the number of learning trials, which is quite crucial for real world applications. In situated systems, robots bec ...
Facial expressions are probably the most visual method to convey emotions and one of the most powerful means to relate to each other. A typical automatic system for the recognition of facial expressions is based on a representation of the expression, learn ...
With an ever-increasing understanding of the brain mechanisms associated with core human attributes and values, there is an increasing public interest in the results of neuroscience research and the ways in which that new knowledge will be used. Here, we p ...
Learners benefit from collaboration because it triggers effective interaction processes such as externalization, elicitation and negotiation of knowledge. In order to communicate effectively, learners need to have a certain representation of their peers' k ...
New firms are endowed with knowledge and experience at birth through the human capital of their founder(s). Existing empirical research suggests that this pre-entry knowledge and experience will influence the firm's chances of survival; however, the mechan ...
Learning a category from few examples is a challenging task for vision algorithms, while psychological studies have shown that humans are able to generalise correctly even from a single instance (one-shot learning). The most accredited hypothesis is that h ...
This paper presents an SVM-based algorithm for the transfer of knowledge across robot platforms aiming to perform the same task. Our method exploits efficiently the transferred knowledge while updating incrementally the internal representation as new infor ...
This paper presents an SVM--based algorithm for the transfer of knowledge across robot platforms aiming to perform the same task. Our method exploits efficiently the transferred knowledge while updating incrementally the internal representation as new inf ...
The present study is part of a project aiming at empirically investigating the process of modeling the partner’s knowledge (Mutual Knowledge Modeling or MKM) in Computer-Supported Collaborative Learning (CSCL) settings. In this study, a macro-collaborative ...