Online courses directory (29)

The STEM Readiness course provides a refresher of core skills related to STEM careers. The core skills covered are Mathematics from arithmetic to beginning algebra, Workplace Communications and Professionalism. The topics of the course are presented through workplace scenarios to show learners how these skills apply to their potential careers. In reviewing these core skills students will be better prepared to be successful in post-secondary STEM related technical programs and ultimately in STEM related careers.

This is a mini-course for individuals with no proficiency or extremely limited knowledge of Arabic language and culture who are about to begin study or work in an Arabic-speaking context. The course will introduce learners to basic concepts and information to facilitate entry and engagement in an Arabic-speaking environment.

Spanish I can be adapted for a hybrid delivery system or solely distance delivery. The course is media-rich and interactive, driven by video that was shot on-site in Guadalajara, Mexico. Versions are available for low-cost use by instructor-led classes of enrolled students. To successfully use this course, you should be a motivated student with a sincere desire to learn the Spanish language and about cultures in the Spanish-speaking world, and be comfortable with computer technologies. The time commitment will typically average 8 hours per week.

An ongoing development effort in collaboration with the Software Engineering Institute’s CERT [1], this course focuses on common security issues in C and C++ development. With security expert Robert Seacord serving as lead content author, the course addresses a key need in professional education for software developers. Topics to be covered include the secure and insecure use of integers, arrays, strings, dynamic memory, formatted input/output functions, and file I/O. Continued development is being funded by partnerships with industry. [1] http://www.cert.org/

This course provides an introduction to causal and statistical reasoning. After taking this course, students will be better prepared to make rational decisions about their own lives and about matters of social policy. They will be able to assess criticallyeven if informallyclaims that they encounter during discussions or when considering a news article or report. A variety of materials are presented, including Case Studies where students are given the opportunity to examine a causal claim, and the Causality Lab, a virtual environment to simulate the science of causal discovery. Students have frequent opportunities to check their understanding and practice their skills. This course is meant to serve students in several situations. One, it is meant for students who will only take one such research methods course, and are interested in gaining basic skills that will help them to think critically about claims they come across in their daily lives, such as through a news article. Two, it is meant for students who will take a few statistics courses in service of a related field of study. Three, it is meant for students interested in the foundations of quantitative causal models: called Bayes Networks.

This course presents material in discrete mathematics and computation theory with a strong emphasis on practical algorithms and experiential learning. Discrete mathematics, also called finite mathematics or decision mathematics, is the study of mathematical structures that are fundamentally discrete in the sense of not supporting or requiring the notion of continuity. Objects studied in finite mathematics are largely countable sets such as integers, finite graphs, and formal languages. Concepts and notations from discrete mathematics are useful to study or describe objects or problems in computer algorithms and programming languages. The CDM course is currently under development and we are making the course available while it is under development. Only one of the planned fifteen modules is currently available. The module on Groups that is currently available would appear mid-way through the complete course.

In this course you will learn how to conduct research using empirical methods, which rely on observation and experimentation. This course is appropriate for those interested in using empirical research methods in their field, particularly students in the social and behavioral sciences. Topics include the formulation of the question to be investigated and the of resulting hypotheses, the collection of data and the analysis of the data collected, and the interpretation and study of analysis results. We assume that learners entering Empirical Research Methods (ERM) have taken at least a semester or year-long course in statistics and, through this or some other experience, have been exposed to the following concepts: Random Variables Population and Samples Data Tables (rows=sample units and columns=variables) Summary Statistics: Mean, Median, Variance, Covariance, Correlation Graphs: Boxplots, Barcharts, Histograms, Scatterplots Inference: standard errors, confidence intervals, hypothesis tests, etc. Models: Bivariate Regression, perhaps ANOVA If learners have not had such exposure, they can follow the appropriate links into the OLI introductory statistics course to review the required concepts.

This course teaches the core principles of economics using a collection of experiments and workbooks. In the experiments, students become traders in a market and attempt to make profitable deals with one another. At the conclusion of the experiment, the data are used to form a customized, online workbook. Each workbook guides the student through the analysis of the experiment’s outcome, while simultaneously presenting the key ideas and core principles in economics needed to gain a deeper understanding of both the experiment and economic life. In these experiments the student is both a participant and an observer. As a participant, the student experiences first hand the issues that all economic agents must confront; as an observer, the student sees how modern economic theory can explain the complex interactions that occur in both the experiments, and the economic world at large. Students often report that they learn nearly as much about economic principles from their experience as a participant as they do from their analysis of the experiment as an observer. Students learning on their own or in small classes (generally fewer than 10 students) can still use the workbooks, but will be given synthetic data. Small numbers of students participating in experiments does not yield enough data for the workbooks.

This course offers an overview of healthcare, health information technology, and health information management systems. The focus is on the role and responsibilities of entry-level health IT specialists in each phase of the health information management systems lifecycle. The curriculum is aligned to the new Certified Associate in Healthcare Information and Management Systems (CAHIMS) [1] certification administered by the Healthcare Information and Management Systems Society. This certificate is designed for students who have previous experience in IT or healthcare and it is designed to serve as a pathway into health IT careers. This course is a collaborative effort of TAACCCT grantees, in particular Bellevue Colleges and MoHealthWINs. The collaborative partners supporting the development of this course are Open Learning Initiative (OLI) at Stanford University and Carnegie Mellon University, Center for Applied Science and Technology (CAST), and Creative Commons (CC)- all funded through the Gates foundation OPEN Grant. The core development team includes content experts, learning scientists, software developers, instructional designers, universal design for learning experts and instructional technologists. [1] http://www.himss.org/health-it-certification/cahims?navItemNumber=13646