The University of Texas at Arlington is Connecting Learning Data to Improve Instructional Design. This course is intended for those who have a bachelor’s degree and are interested in developing learning and data science skills for employment in education, corporate, nonprofit, and military sectors.
In this three week course, applicants will learn how data is captured in learning experiences and how it is processed and analyzed to inform student support actions. This course will start on March 12, 2018.
Course At A Glance
Length: 3 weeks
Effort: 5-7 hours pw
Subject: Data Analysis & Statistics
Institution: University of Texas at Arlington and edx
Certificate Available: Yes, Add a Verified Certificate for $99
Session: Course Starts on March 12, 2018
The University of Texas at Arlington is one of the nation’s most dynamic centers of higher learning, setting the standard for educational excellence in the thriving North Texas region it calls home. An academic centerpiece in the heart of the Dallas-Fort Worth Metroplex for nearly 120 years, UT Arlington was founded in 1895 as a private liberal arts institution.
About This Course
This course will benefit educational designers, learning technology managers, and academics that are interested in how to use data to guide the design and improvements of a learning experience.
Technology has the ability to collect a large amount of data about how people participate in a learning experience. How can this data be used to increase our understanding of how learning occurs? How can data be translated into actionable knowledge? How can data help improve the overall quality of a learning experience? These are the questions that are explored during the activities in the course. You will need basic knowledge about data manipulation and statistical analysis, and you will learn how to use them to translate data into actionable knowledge to apply in a learning experience.
- How data sets are captured in learning experiences
- What basic procedures to use to manipulate these data sets
- The use of statistical models to predict student behavior
- The deployment of personalized support actions for the students
Abelardo Pardo is Associate Professor in the School of Electrical and Information Engineering at The University of Sydney, Australia.
- University highly recommend that you take the previous course in this series before beginning this course:
Feature Engineering for Improving Learning Environments
- This course is intended for those who have a bachelor’s degree and are interested in developing learning and data science skills for employment in education, corporate, nonprofit, and military sectors. Experience with programming and statistics will be beneficial to participants.
How To Join This Course
- Go to the course website link
- Create an edX account to SignUp
- Choose “Register Now” to get started.
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