Teaching with infographics: practising new digital competencies and visual literacies

This position paper examines the use of infographics as a teaching assignment in the online college classroom. It argues for the benefits of adopting this type of creative assignment for teaching and learning, and considers the pedagogic and technical challenges that may arise in doing so. Data and insights are drawn from two case studies, both from the communications field, one online class and a blended one, taught at two different institutions. The paper demonstrates how incorporating a research-based graphic design assignment into coursework challenges and encourages students' visual digital literacies. The paper includes practical insights and identifies best practices emerging from the authors' classroom experience with the infographic assignment, and from student feedback. The paper suggests that this kind of creative assignment requires students to practice exactly those digital competencies required to participate in an increasingly visual digital culture

Motivational Social Visualizations for Personalized E-Learning

A large number of educational resources is now available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produces at least two problems: how to help students find the most appropriate resources, and how to engage them into using these resources and benefiting from them. Personalized and social learning have been suggested as potential methods for addressing these problems. Our work presented in this paper attempts to combine the ideas of personalized and social learning. We introduce Progressor + , an innovative Web-based interface that helps students find the most relevant resources in a large collection of self-assessment questions and programming examples. We also present the results of a classroom study of the Progressor +  in an undergraduate class. The data revealed the motivational impact of the personalized social guidance provided by the system in the target context. The interface encouraged students to explore more educational resources and motivated them to do some work ahead of the course schedule. The increase in diversity of explored content resulted in improving students’ problem solving success. A deeper analysis of the social guidance mechanism revealed that it is based on the leading behavior of the strong students, who discovered the most relevant resources and created trails for weaker students to follow. The study results also demonstrate that students were more engaged with the system: they spent more time in working with self-assessment questions and annotated examples, attempted more questions, and achieved higher success rates in answering them

The other side of the social web: A taxonomy for social information access

The power of the modern Web, which is frequently called the Social Web or Web 2.0, is frequently traced to the power of users as contributors of various kinds of contents through Wikis, blogs, and resource sharing sites. However, the community power impacts not only the production of Web content, but also the access to all kinds of Web content. A number of research groups worldwide explore what we call social information access techniques that help users get to the right information using "collective wisdom" distilled from actions of those who worked with this information earlier. This invited talk offers a brief introduction into this important research stream and reviews recent works on social information access performed at the University of Pittsburgh's PAWS Lab lead by the author. Copyright © 2012 by the Association for Computing Machinery, Inc. (ACM)

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

Perspectives on blended learning through the on-line platform, LabLessons, for Chemistry

The effectiveness of blended learning was evaluated through the integration of an online chemistry platform, LabLessons. Two modules, Formation of Hydrogen and Titration, were designed by college mentors alongside classroom chemistry teachers to engage and allow high school students to better comprehend these scientific topics. The pre-lab modules introduced the students to experiments they were expected to perform in class the following day. The modules consisted of an introduction as well as either a visualization and/or simulation specific to each topic. Students and teachers who utilized LabLessons were surveyed to establish a preliminary research on the use of technology in classrooms. Student and teacher surveys demonstrated LabLessons to be an interactive and helpful tool to improve students' understanding of conceptual ideasPeer Reviewe

A Data Science Course for Undergraduates: Thinking with Data

Data science is an emerging interdisciplinary field that combines elements of mathematics, statistics, computer science, and knowledge in a particular application domain for the purpose of extracting meaningful information from the increasingly sophisticated array of data available in many settings. These data tend to be non-traditional, in the sense that they are often live, large, complex, and/or messy. A first course in statistics at the undergraduate level typically introduces students with a variety of techniques to analyze small, neat, and clean data sets. However, whether they pursue more formal training in statistics or not, many of these students will end up working with data that is considerably more complex, and will need facility with statistical computing techniques. More importantly, these students require a framework for thinking structurally about data. We describe an undergraduate course in a liberal arts environment that provides students with the tools necessary to apply data science. The course emphasizes modern, practical, and useful skills that cover the full data analysis spectrum, from asking an interesting question to acquiring, managing, manipulating, processing, querying, analyzing, and visualizing data, as well communicating findings in written, graphical, and oral forms.Comment: 21 pages total including supplementary material

Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles

In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who think differently have not worked well. In this paper, we hypothesize, first, that previous approaches have not worked because they have been direct -- they have tried to explicitly connect people with those having opposing views on sensitive issues. Second, that neither recommendation or presentation of information by themselves are enough to encourage behavioral change. We propose a platform that mixes a recommender algorithm and a visualization-based user interface to explore recommendations. It recommends politically diverse profiles in terms of distance of latent topics, and displays those recommendations in a visual representation of each user's personal content. We performed an "in the wild" evaluation of this platform, and found that people explored more recommendations when using a biased algorithm instead of ours. In line with our hypothesis, we also found that the mixture of our recommender algorithm and our user interface, allowed politically interested users to exhibit an unbiased exploration of the recommended profiles. Finally, our results contribute insights in two aspects: first, which individual differences are important when designing platforms aimed at behavioral change; and second, which algorithms and user interfaces should be mixed to help users avoid cognitive mechanisms that lead to biased behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User Interfaces 201