interconnecting and enriching higher education programs using linked data
TRANSCRIPT
INTERCONNECTING AND
ENRICHING HIGHER EDUCATION
PROGRAMS USING LINKED DATA
Fouad ZablithAmerican University of Beirut
Problem
• Higher education programs are often designed around
courses that follow a specific sequence
• Courses are usually described at high levels in the form of
syllabi and program catalogues
• This text-based representation creates hard knowledge
boundaries around courses that tend to be delivered and
analyzed mostly in isolation
Approach
• In this work, we aim to de-blackbox the representation of a
higher education curriculum
• We rely on linked data to generate and represent the
conceptual connections around the courses in a higher
education program
• We deploy a Semantic Mediawiki platform to collaboratively
build the knowledge graph around the courses
• We highlight the value of this linked data layer through two use
cases to (1) enrich online learning environments and (2)
support the program review process
Data Model
Data Model
Building the Linked Data Graph
• Phase 1: Creating Courses Information
• Course syllabi are used to identify the high level course information
(e.g. course name, description, topics, etc.)
• Phase 2: Identifying Concepts Taught
• This was the most time consuming task, where course material
(mainly textbooks) were used to identify taught concepts in courses
• Phase 3: Anchoring Learning Material to Courses
• This is the ongoing enrichment step using a semantic bookmarklet
to connect external material to courses
Course
Topic
Course
Topic
Concept
Course
Topic
Concept
Learning Material
Phase 1: Creating Courses Information
Phase 1: Creating Courses Information
http://linked.aub.edu.lb/collab
Phase 1: Creating Courses Information
http://linked.aub.edu.lb/collab
Phase 2: Identifying Concepts Taught
Conceptual Linking
Phase 3: Anchoring Learning Material to
Courses
Learning Material Bookmarklet
http://linked.aub.edu.lb/docs/tutorial_material_bookmark/
Example:
https://www.youtube.com/watch?v=f60dheI4ARg
Students Expanding the Data Graph
http://www.capgemini.com/resources/the-deciding-factor-big-data-decision-making
Learning Material
Students Expanding the Data Graph
http://www.capgemini.com/resources/the-deciding-factor-big-data-decision-making
BigData
Operations Decisions
Social Media
Automated Process
Organizational Silos
Decision
Internet Services
Business Process
Reengineering
Intuitive Decision Making
Learning Material Concepts
Current Data Available
• So far we have captured the following data around the
school’s higher education program:
Category Number
Courses 20
Topical coverage 171
Taught concepts 2,684
Learning Material 75
Using the Linked Data Graph:
Enriching Moodle Environments
Using the Linked Data Graph:
Enriching Moodle Environments
Impact of Student’s Input
http://www.capgemini.com/resources/the-deciding-factor-big-data-decision-making
Information
Systems
Management
Operations
Management
BigData
Operations Decisions
Social Media
Automated Process
Organizational Silos
Decision
Internet Services
Business Process
Reengineering
Intuitive Decision Making
Learning Material Concepts Moodle Courses
Impact of Student’s Input
http://www.capgemini.com/resources/the-deciding-factor-big-data-decision-making
Information
Systems
Management
Operations
Management
BigData
Operations Decisions
Social Media
Automated Process
Organizational Silos
Decision
Internet Services
Business Process
Reengineering
Intuitive Decision Making
Learning Material Moodle Courses
Indirectly interlinking
courses’ content
Concepts
Using the Linked Data Graph:
Program Review Concepts Graph
http://linked.aub.edu.lb/collab/index.php/Learning_Concepts_Graph
Using the Linked Data Graph:
Program Review Concepts Table
http://linked.aub.edu.lb/apps/tablebrowser/table.php
Future Directions
• Develop further data-driven applications to support
learning experiences
• Capture social interactions around the linked data graph
to have more granular insights on students’ behavior
around the concepts delivered
• Capitalize on the data graph to boost analytics and further
support the curriculum review process
Future Directions: Capturing Social
Interactions
Future Directions: Boosting Analytics
Future Directions: Boosting Analytics
Future Directions: Boosting Analytics
Conclusions
• We presented our efforts on collaboratively building a
linked data graph to capture concepts exchanged in
higher education programs
• We highlighted the value of this linked data layer at two
levels:
• First at the level of enriching learning environments and breaking
the knowledge boundaries around courses
• Second at the analytics level by building tools that provide new and
unprecedented curriculum visualizations
