Integrating Programming Learning Analytics Across Physical and Digital Space

I. Han Hsiao, Po Kai Huang, Hannah Murphy

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In this work, we study students' learning effectiveness through their use of a homegrown innovative educational technology, Web Programming Grading Assistant (WPGA), which facilitates grading and feedback delivery of paper-based assessments. We designed a lab study and a classroom study from a lower-division blended-instruction computer science course. We evaluated a partial credit assignment algorithm. We tracked and modeled students' learning behaviors through their use of WPGA. Results showed that students demonstrated an effort and desire to review assessments regardless of if they were graded for academic performance or for attendance. Diligent students achieved higher exam scores on average and were found to review their exams and the correct questions frequently. Additionally, student cohorts exhibited similar initial reviewing patterns, but different in-depth reviewing and reflecting strategies. Ultimately, the work contributes to multidimensional learning analytics aggregation across the physical and cybersphere.

Original languageEnglish (US)
Article number7918521
Pages (from-to)206-217
Number of pages12
JournalIEEE Transactions on Emerging Topics in Computing
Volume8
Issue number1
DOIs
StatePublished - Jan 1 2020

Keywords

  • behavior modeling
  • blended instruction classes
  • Learning analytics
  • multimodal analytics
  • orchestration technology
  • programming learning

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications

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