Please review the course outline to familiarize yourself with weekly topics, tools used during the course, learning outcomes, and assignments.
The growth of "big data" and analytics has captured the interest of corporations in the form of "business intelligence," governments in the form of "open data." A new discipline is emerging in the form of "learning analytics" focusing on the educational sector that has its unique demands and needs. Learning institutions and corporations make little use of the data learners "throw off" in the process of accessing learning materials, interacting with educators and peers, and creating new content. In an age where educational institutions are under growing pressure to reduce costs and increase efficiency, analytics promises to be an important lens through which to view and plan for change at course and institutions levels. Corporations face pressure for increased competitiveness and productivity, a challenge that requires important contributions in organizational capacity building from work place and informal learning. Learning analytics can play a role in highlighting the development of employees through their learning activities.
This course will focus on the analytics techniques, technologies, and personnel (data scientists or analysts) in both educational sector and corporate learning, and will provide an overview to the field and equip learners with a theoretical and conceptual base for additional study in data mining, analytics, and machine learning.
Over the next 12 weeks, we will explore different analytic techniques and different tools researchers and educators can use to understand the activity of learners. In the process, we'll cover topics such as big data, intelligent curriculum, linked data and the Semantic Web, models for analytics use, dashboards and visualization, as well as the role of leaders in planning for and deploying analytics.
Live (optional) weekly meetings will be held on Sundays at 2:00 pm Mountain time at a session created by Dr. Graf at Microsoft Teams. These sessions will be recorded and will be made available for later viewing.
I can be contacted via email at sabineg@athabascau.ca. I will reply to course-related inquiries within 48 hours. Office hours or individual consultations will be arranged at the request of students. If you have any concerns or questions related to the course content, format, or instructional approaches and technologies, please let me know. I'll be happy to meet (Skype or Microsoft Teams) to assist or discuss in more detail.
Technologies used: This course will introduce you to various tools and techniques for analyzing data, discourse, and social networks. Several analytics tools will be covered in this course. For instructional purposes, we will use the following tools: Moodle (where you are now), Athabasca Landing (use your AU ID and password to log in just as you do with Moodle), Microsoft Teams (for weekly meetings), and Skype of one-on-one conversations.
Updated September 13 2021 by FST Course Production Staff