Learn about learning analytics tools, resources, processes, and workflows currently available at the University of Minnesota.
The aim of this practical guide is to introduce learning analytics to educators in higher education. To this end, we define learning analytics, provide some background to how learning analytics work, explore successful learning analytics implementations, and present findings from an exploratory study of perceptions of the users of learning analytics—educators, students, and advisors—of common metrics and visualizations from learning management system analytic tools at an Ontario university to provide a practical guide to learning analytics.
The Little Book of Semaphores is a free (in both senses of the word) textbook that introduces the principles of synchronization for concurrent programming.In most computer science curricula, synchronization is a module in an Operating Systems class. OS textbooks present a standard set of problems with a standard set of solutions, but most students don't get a good understanding of the material or the ability to solve similar problems.The approach of this book is to identify patterns that are useful for a variety of synchronization problems and then show how they can be assembled into solutions. After each problem, the book offers a hint before showing a solution, giving students a better chance of discovering solutions on their own.The book covers the classical problems, including "Readers-writers," "Producer-consumer", and "Dining Philosophers." In addition, it collects a number of not-so-classical problems, some written by the author and some by other teachers and textbook writers. Readers are invited to create and submit new problems.
This is an overview of how to use MLA citations for college papers. It is an introduction with examples of works cited and in-text citations.
A survey course in mathematics for students in the liberal arts and other non-science majors. Topics are selected from areas such as management science, statistics, social choice, the geometry of size and shape, and computers and their applications. Emphasizes the application of mathematics to the problems of contemporary society and the critical role these applications play in economic, political and personal life.
Course Outcomes:
1. Formulate questions that can be addressed with data, then organize, display and analyze relevant data to address these questions and communicate results.
2. Apply the basic principles of study design to develop and analyze the validity of simple experiments.
3. Demonstrate numeric and algebraic reasoning skills to support statistical analysis and financial literacy.
4. Construct, use, and interpret mathematical models, specifically linear, quadratic, logarithmic, and exponential functions, to represent relationships in quantitative data.
This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.
This class introduces elementary programming concepts including variable types, data structures, and flow control. After an introduction to linear algebra and probability, it covers numerical methods relevant to mechanical engineering, including approximation (interpolation, least squares and statistical regression), integration, solution of linear and nonlinear equations, ordinary differential equations, and deterministic and probabilistic approaches. Examples are drawn from mechanical engineering disciplines, in particular from robotics, dynamics, and structural analysis. Assignments require MATLAB programming.
We intend this book to act as a guide writ large for would-be champions of OER, that anyone—called to action by the example set by our chapter authors—might serve as guides themselves. The following chapters tap into the deep experience of practitioners who represent a meaningful cross section of higher education institutions in North America. It is our hope that the examples and discussions presented by our authors will facilitate connections among practitioners, foster the development of best practices for OER adoption and creation, and more importantly, lay a foundation for novel, educational excellence.
Your action plan is an internal planning document for how you will convince key internal and external constituents to support for the work that you are doing. It is intended as a living document that you can revisit as you review the results of your advocacy activities and refine your advocacy strategy. Think of it as a skeleton you can work to fill in.
In 2017, The Rebus Foundation embarked on a research and development project to prototype an open, web-based reading system, with funding from the Andrew W. Mellon Foundation. Our main goals with this project were to clearly identify and understand the different players involved in the publication, distribution and consumption of scholarly monographs, and to explore how Open Web technologies could improve scholars’ access to, and interaction with, scholarly monographs. We've summarized our research findings in this report.
This course is intended to provide a foundation in the skills and knowledge you'll need to create, remix, adopt, or update open educational resources (OER). Specifically, by the end of the course you'll be able to:
Apply backward design in order to plan learning goals, assessment, and appropriate scaffolding/support,
Describe the meaning of open educational resources,
Locate open educational resources relevant to course learning outcomes,
Properly attribute works offered under a Creative Commons license,
Identify and create works that are accessible to all students,
Add a Creative Commons license to your own work and share back with your disciplinary community.
This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world's fastest machines. We will make prominent use of the Julia Language software project.
The course purpose is to provide the substance and skill necessary to make sound business decisions relating to information systems, and to work with senior line managers in the resolution of issues and problems in this area. Categories of issues which will be addressed in the course include: How do IT and its various manifestations in business, such as the Internet, affect current and future competitiveness? How do we align business strategy and plans with IT strategy and IT plans? How can we engage executives in learning and leading IT-related change? How do we implement new systems, change work behavior, manage projects? How should we organize and govern IT in an organization.
"This course provides a thorough introduction to the C programming language, the workhorse of the UNIX operating system and lingua franca of embedded processors and micro-controllers. The first two weeks will cover basic syntax and grammar, and expose students to practical programming techniques. The remaining lectures will focus on more advanced concepts, such as dynamic memory allocation, concurrency and synchronization, UNIX signals and process control, library development and usage. Daily programming Assignments and Labs and weekly laboratory exercises are required. Knowledge of C is highly marketable for summer internships, UROPs, and full-time positions in software and embedded systems development."
Principles of Computer System Design: An Introduction is published in two parts. Part I, containing chapters 1-6, is a traditional printed textbook published by Morgan Kaufman, an imprint of Elsevier. Part II, containing chapters 7-11, is available here as an open educational resource. This textbook, an introduction to the principles and abstractions used in the design of computer systems, is an outgrowth of notes written for 6.033 Computer System Engineering over a period of 40-plus years. Individual chapters are also used in other EECS subjects. There is also a Web site for the current 6.033 class with a lecture schedule that includes daily Assignments and Labs, lecture notes, and lecture slides. The 6.033 class Web site also contains a thirteen-year archive of class Assignments and Labs, design projects, and quizzes. Technical Requirements: Special software is required to use some of the files in this resource: .key, .ppt, and .zip.
Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example: The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of "The Ten Things Everyone Should Know About Science". A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions. Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget. The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.
This course is an introduction to quantum computational complexity theory, the study of the fundamental capabilities and limitations of quantum computers. Topics include complexity classes, lower bounds, communication complexity, proofs, advice, and interactive proof systems in the quantum world. The objective is to bring students to the research frontier.
This course examines quantum computation and quantum information. Topics include quantum circuits, quantum Fourier transform and search algorithms, physical implementations, the quantum operations formalism, quantum error correction, stabilizer and Calderbank-Shor-Steans codes, fault tolerant quantum computation, quantum data compression, entanglement, and proof of the security of quantum cryptography. Prior knowledge of quantum mechanics and basic information theory is required.
Advanced seminar extends computer and analytic skills developed in the other subjects in this sequence into a research environment. Students present a structured discussion of a journal article representative of current research in Planning Decision Support Systems, and complete an approved short research project. Suggested research projects include topics related to ongoing research projects of the Computer Resource Laboratory. Seminar participants and invited guests will lead critical discussions of current literature and ongoing research. Each student will be responsible for identifying, reviewing, and presenting one structured discussion of articles from the current literature that are relevant to their research topic. The remaining time will be spent working on individual projects or thesis proposals. This fall, the seminar will focus on the following core issues that underlie most implementations of urban information systems and decision support tools: the sustainable acquisition and representation of urban knowledge; the emergent technological infrastructure for supporting metropolitan decision-making; and the innovative organizational and institutional arrangements that can take advantage of modern urban information systems.
Upon completion of this course, students will be able to: develop and research a topic of global significance; recognize authorsŰŞ arguments and the political, social and economic motivations behind their work; demonstrate the ability to locate, interpret and cite the relevant and appropriate information resources on a topic; and, demonstrate an understanding of the information research process.Login: guest_oclPassword: ocl