Organizational Analysis About the Course Best MBA Mooc in 2013 as per review in the Financial Times! "The best [MBA Mooc] was Organizational Analysis taught by Stanford's Dan McFarland" - Philip D. Broughton MBA It is hard to imagine living in modern society without participating in or interacting with organizations. Each case is full of details and complexity. Through this self-paced course you will come to see that there is nothing more practical than a good theory. Join your future classmates and course alumni on Facebook! Course Syllabus Module 1: Introduction Module 2: Decisions by rational and rule-based procedures Module 3: Decisions by dominant coalitions Module 4: Decisions in organized anarchies Module 5: Developing organizational learning and intelligence Module 6: Developing an organizational culture Module 7: Managing resource dependencies Module 8: Network forms of organization Module 9: Institutions and organizational legitimacy Module 10: Summary Suggested Readings Course Format
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. Over the past few years, gamification adoption has skyrocketed. 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) Course Syllabus The course is divided into 12 units. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. Recommended Background This course is designed as an introduction to gamification as a business practice. Suggested Readings The course is designed to be self-contained. Course Format The class will consist of video lectures, which are between 7 and 12 minutes in length. Yes. • Who should take this course?
Design: Creation of Artifacts in Society About the Course This is a course aimed at making you a better designer. The course marries theory and practice, as both are valuable in improving design performance. Lectures and readings will lay out the fundamental concepts that underpin design as a human activity. Weekly design challenges test your ability to apply those ideas to solve real problems. Student Testimonials from Earlier Sessions of the Course:"An amazing course - a joy to take. "When I signed up for this course I didn't know what to expect; the experience was so good and rewarding. See examples of student projects: here Recommended Background No specific background is required. Suggested Readings To get a feel for the style of the instructor and the material in the course, this book is a good place to start: Ulrich, K.T. 2010. The free digital book is available at Design: Creation of Artifacts in Society. Other highly recommended reading is the textbook: Product Design and Development by Karl T. Course Format
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. Prior to this position, Maria served as faculty at a community college for a decade, teaching social media, chemistry, and math and designing learning experiences for both traditional and online formats. Maria has worked extensively with faculty development and is also an internationally-known learning futurist.
Model Thinking This course will consist of twenty sections. As the course proceeds, I will fill in the descriptions of the topics and put in readings. Section 1: Introduction: Why Model? In these lectures, I describe some of the reasons why a person would want to take a modeling course. To be an intelligent citizen of the worldTo be a clearer thinkerTo understand and use dataTo better decide, strategize, and design There are two readings for this section. The Model Thinker: Prologue, Introduction and Chapter 1 Why Model? Section 2: Sorting and Peer Effects We now jump directly into some models. In this second section, I show a computational version of Schelling's Segregation Model using NetLogo. NetLogo The Schelling Model that I use can be found by clicking on the "File" tab, then going to "Models Library". The readings for this section include some brief notes on Schelling's model and then the academic papers of Granovetter and Miller and Page. Notes on Schelling Granovetter Model Miller and Page Model
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. Course Title: Instructional Ideas and Technology Tools for Online Success Enrollment is Now Open
Introduction to Sustainability About the Course This course introduces the academic approach of Sustainability and explores how today’s human societies can endure in the face of global change, ecosystem degradation and resource limitations. The course focuses on key knowledge areas of sustainability theory and practice, including population, ecosystems, global change, energy, agriculture, water, environmental economics and policy, ethics, and cultural history. This subject is of vital importance, seeking as it does to uncover the principles of the long-term welfare of all the peoples of the planet. As sustainability is a cross-disciplinary field of study, this foundation requires intellectual breadth: as I describe it in the class text, understanding our motivations requires the humanities, measuring the challenges of sustainability requires knowledge of the sciences (both natural and social), and building solutions requires technical insight into systems (such as provided by engineering, planning, and management).
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 .
Data Analysis About the Course You have probably heard that this is the era of “Big Data”. Stories about companies or scientists using data to recommend movies, discover who is pregnant based on credit card receipts, or confirm the existence of the Higgs Boson regularly appear in Forbes, the Economist, the Wall Street Journal, and The New York Times. But how does one turn data into this type of insight? The answer is data analysis and applied statistics. Data analysis is the process of finding the right data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to have the biggest possible impact. This course is an applied statistics course focusing on data analysis. Recommended Background Some familiarity with the R statistical programming language ( and proficiency in writing in English will be useful. Course Format
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. In addition to participating in class discussions, students will have to complete several short programming and data analysis assignments as well as a final project. There are no prerequisites for the class and the class is open to graduate students as well as advanced undergraduates. Schedule Th Oct 25: Animation ( Slides )