Meetings Stub Page [mx-stub]
The Application of Analytics in Instructional Design
7:30am - 9:00am Registration and Coffee
9:00am - Introduction and Welcome
9:15am - 10:30am Implications of Learning Analytics for Instructional Design
Speakers:
Erin DeSilva, Instructional Designer, Dartmouth College
Scott Millspaugh, Instructional Designer, Dartmouth College
Karen Storin Lintz, Associate Dean of Library & Learning Resources, Emmanuel College
Question: How can data from the LMS inform instructional design decisions? Answer: Ask the right questions! These short case studies will outline how a particular course or program modification was made based on student data from the LMS.
- Group discussions in a large introductory course
- Quantitative and qualitative analyses of discussion boards in a large introductory course over three years
- Collaborating across institutional difference - working with data from six schools using three different LMS’s to gain insights into best practices.
10:30am - 10:45am Break
10:45am - 11:45am Table Discussions
Discussion Leaders:
Erin DeSilva, Instructional Designer, Dartmouth College
Scott Millspaugh, Instructional Designer, Dartmouth College
Karen Storin Lintz, Associate Dean of Library & Learning Resources, Emmanuel College
Presenters will then lead small, break-out discussions on topics relevant to the material presented. Participants can choose which break-out discussion to contribute to.
Table 1 - Individual vs. Group assignments: how to structure for success
Table 2 - Instructional Design interventions with faculty to promote discussion-board participation
Table 3 - High impact practices - what we’ve learned so far from Colleges of the Fenway data analysis.
11:45am - 12:45pm Lunch
12:45pm - 1:45pm Tools and Techniques for Harvesting Learning Data
Speakers:
Hong Chau, Instructional Designer, Brown University
Jing Qi, Learning Analytic and LMS Specialist, Dartmouth College
Esin Sile, Partner & CEO, MIndBridge Partners
-Three presentations and demonstrations of tools and techniques that are used to harvest and analyze learning data.
-Demonstration of a self-service tool we built that gathers and analyzes discussion interaction data
-Leveraging Canvas Data Service to run institutional level Canvas data analysis
-Tools for Cross-Platform analysis
1:45pm-2:00pm Break
2:00 pm - 2:45pm Table Discussions-What are the common learning data collected by an LMS? How can we collect data to help answer common instructional design questions related to student engagement in an LMS? What are the methods used to gather and analyze learning data to address the questions?
Discussion Leaders:
Hong Chau, Instructional Designer, Brown University
Jing Qi, Learning Analytic and LMS Specialist, Dartmouth College
Esin Sile, Partner & CEO, MIndBridge Partners
Table 1 - Tools for cross-platform analysis (Esin)
Table 2 - Leveraging Canvas data services- Leveraging Canvas data services: getting your head wrapped around institutional data, what questions to ask, and who should be involved in the conversation
Table 3 - Analyzing and visualizing the learning data using a Shiny app
2:45pm - 3:00pm Wrap up