Semantic visual analytics for today's programming courses

Ihan Hsiao, Sesha Kumar Pandhalkudi Govindarajan, Yi Ling Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations


We designed and studied an innovative semantic visual learning analytics for orchestrating today's programming classes. The visual analytics integrates sources of learning activities by their content semantics. It automatically processs paper-based exams by associating sets of concepts to the exam questions. Results indicated the automatic concept extraction from exams were promising and could be a potential technological solution to address a real world issue. We also discovered that indexing effectiveness was especially prevalent for complex content by covering more comprehensive semantics. Subjective evaluation revealed that the dynamic concept indexing provided teachers with immediate feedback on producing more balanced exams.

Original languageEnglish (US)
Title of host publicationLAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation
PublisherAssociation for Computing Machinery
Number of pages6
ISBN (Electronic)9781450341905
StatePublished - Apr 25 2016
Event6th International Conference on Learning Analytics and Knowledge, LAK 2016 - Edinburgh, United Kingdom
Duration: Apr 25 2016Apr 29 2016


Other6th International Conference on Learning Analytics and Knowledge, LAK 2016
Country/TerritoryUnited Kingdom


  • Auto grading
  • Dashboard
  • Intelligent authoring
  • Orchestration technology
  • Programming
  • Semantic analytics
  • Visual analytics

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software


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