Talks. Free Online Course Materials. MAS.965 Social Visualization, Fall 2004. CourseWiki - CS 448B. The world is awash with increasing amounts of data, and we must keep afloat with our relatively constant perceptual and cognitive abilities.
Visualization provides one means of combating information overload, as a well-designed visual encoding can supplant cognitive calculations with simpler perceptual inferences and improve comprehension, memory, and decision making. Furthermore, visual representations may help engage more diverse audiences in the process of analytic thinking.
In this course we will study techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science. The course is targeted both towards students interested in using visualization in their own work, as well as students interested in building better visualization tools and systems. There are no prerequisites for the class and the class is open to graduate students as well as advanced undergraduates. Schedule Fri Nov 2: Data Visualization Theory & Practice. In this course you will explore the question of what visualization is, and why you should use visualizations for quantitative data.
In doing so, you will address theoretical concepts and examine case studies that show the importance of effective visualizations in real world settings. Image courtesy of Ryan Harris Course Description You will also look at how to interpret meanings in visualizations. Elements of cognitive science theory are addressed, and you will practice techniques to help with your interpretations. In the lab portion of the course the main objective is to expose you to a variety of common and different digital visualization software tools. Technical Requirements Although software availability may change slightly, lab assignments will utilize the following software: Interested in a degree?
This course was created by faculty in the Department of Instructional Technology and Learning Sciences at Utah State University . E-learning and Digital Cultures. Events.blackboard.com/open?elqCampaignId=1605. Description: Motivating students and creating community within blended and online learning environments is crucial to academic achievement and success.
This open course will provide both theoretical concepts and practical tools for instructors to improve motivation, retention, and engagement within blended and online courses. Course Objectives: Identify and apply relevant motivational strategies and instructional techniquesConstruct thinking skill options for different types of learners and subjectsDesign and share innovative thinking skill activities as well as unique cooperative learningMap and apply instructional models and ideas to online learning toolsCourse Duration: April 30th- June 4th ( A total of 5 weeks) Announcing a Free, Open Course With Dr.
Curtis Bonk. Free Online Course Materials. Gamification. About the Course Gamification is the application of digital game design techniques to non-game contexts, such as business, education, and social impact challenges.
Video games are the dominant entertainment form of modern times because they powerfully motivate behavior. Game mechanics can be applied outside the immersive environments of games themselves, to create engaging experiences as well as assign rewards and recognition. Over the past few years, gamification adoption has skyrocketed. Companies use game thinking for employee motivation in human resources, team building, productivity enhancement, training, health and wellness, sustainability, and innovation. Game thinking means more than dropping in badges and leaderboards to make an activity fun or addicting. Subtitles forall video lectures available in: English, Russian (provided by Digital October), Turkish (Koc University), and Ukrainian (provided by Bionic University) Web Intelligence and Big Data. Social Network Analysis. About the Course Everything is connected: people, information, events and places, all the more so with the advent of online social media.
A practical way of making sense of the tangle of connections is to analyze them as networks. In this course you will learn about the structure and evolution of networks, drawing on knowledge from disciplines as diverse as sociology, mathematics, computer science, economics, and physics. Online interactive demonstrations and hands-on analysis of real-world data sets will focus on a range of tasks: from identifying important nodes in the network, to detecting communities, to tracing information diffusion and opinion formation. Course Syllabus Week 1: What are networks and what use is it to study them? Concepts: nodes, edges, adjacency matrix, one and two-mode networks, node degree Activity: Upload a social network (e.g. your Facebook social network into Gephi and visualize it ). Week 2: Random network models: Erdos-Renyi and Barabasi-Albert Week 4: Community.
Social Media. Dr.
Maria H. Andersen is the Director of Learning and Research for Instructure, where she acts as a translator and anthropologist to help bridge the gap between technologists who build Canvas and the education tribe who use it. She is also tasked with using existing research to improve student success through the design of features in Canvas and using data from Canvas for research about the Scholarship of Teaching and Learning.