About this course
The demand for data science and learning science skills has continued to increase as classrooms, labs, and organizations look to optimize their data and improve learning environments for students and employees. The UTArlingtonX Learning Analytics courses will give you the opportunity to gain invaluable knowledge and expertise in this growing field.
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 in RStudio and Jupyter Notebooks)
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?
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