Learning Analytics Fundamentals (edX)

In this introductory course, you will develop a solid understanding of fundamental learning analytics theories and processes, and explore different types of educational data. You will gain experience working with educational data sets and the R programming language, and hear from a diverse set of voices in the field. Finally, you will also consider ethics and privacy issues, as well explore how to work as part of a team in a domain that is becoming increasingly cross-disciplinary.

By grasping these fundamental areas, you will have a better understanding of the field of learning analytics and be able to apply skills to any occupation that utilizes educational data.

What you'll learn

- The field of learning analytics and explore how data and information are used

- Common learning analytics methods and approaches, such as data wrangling and cleaning, structure discovery, and basic prediction modeling

- How to conduct basic data wrangling and analyses

- Ethics and privacy considerations

- Working in a collaborative, cross-disciplinary setting

- Common toolsets used in the UTArlingtonX Learning Analytics courses (R and GitHub)

Syllabus

Week 1: What are learning analytics?

Week 2: What types of data will you work with?

Week 3: What types of things will you do?

Week 4: How do you work as part of a team or within an organization?