Fostering collaborative knowledge construction with visualization tools

This study investigates to what extent collaborative knowledge construction can be fostered by providing students with visualization tools as structural support. Thirty-two students of Educational Psychology took part in the study. The students were subdivided into dyads and asked to solve a case problem of their learning domain under one of two conditions: 1) with content-specific visualization 2) with content-unspecific visualization. Results show that by being provided with a content-specific visualization tool, both the process and the outcome of the cooperative effort improved. More specifically, dyads under that condition referred to more adequate concepts, risked more conflicts, and were more successful in integrating prior knowledge into the collaborative solution. Moreover, those learning partners had a more similar individual learning outcome

Learning to count with deep object features

Learning to count is a learning strategy that has been recently proposed in the literature for dealing with problems where estimating the number of object instances in a scene is the final objective. In this framework, the task of learning to detect and localize individual object instances is seen as a harder task that can be evaded by casting the problem as that of computing a regression value from hand-crafted image features. In this paper we explore the features that are learned when training a counting convolutional neural network in order to understand their underlying representation. To this end we define a counting problem for MNIST data and show that the internal representation of the network is able to classify digits in spite of the fact that no direct supervision was provided for them during training. We also present preliminary results about a deep network that is able to count the number of pedestrians in a scene.Comment: This paper has been accepted at Deep Vision Workshop at CVPR 201

Knowledge Cartography for Open Sensemaking Communities

Knowledge Cartography is the discipline of visually mapping the conceptual structure of ideas, such as the connections between issues, concepts, answers, arguments and evidence. The cognitive process of externalising one's understanding clarifies one's own grasp of the situation, as well as communicating it to others as a network that invites their contributions. This sensemaking activity lies at the heart of the Open Educational Resources movement's objectives. The aim of this paper is to describe the usage patterns of Compendium, a knowledge mapping tool from the OpenLearn OER project, using quantitative data from interaction logs and qualitative data from knowledge maps, forums and blog postings. This work explains nine roles played by maps in OpenLearn, and discusses some of the benefits and adoption obstacles, which motivate our ongoing work

A framework to maximise the communicative power of knowledge visualisations

Knowledge visualisation, in the field of information systems, is both a process and a product, informed by the closely aligned fields of information visualisation and knowledg management. Knowledge visualisation has untapped potential within the purview of knowledge communication. Even so, knowledge visualisations are infrequently deployed due to a lack of evidence-based guidance. To improve this situation, we carried out a systematic literature review to derive a number of “lenses” that can be used to reveal the essential perspectives to feed into the visualisation production process.We propose a conceptual framework which incorporates these lenses to guide producers of knowledge visualisations. This framework uses the different lenses to reveal critical perspectives that need to be considered during the design process. We conclude by demonstrating how this framework could be used to produce an effective knowledge visualisation