Personalized Information Seeking Assistant (PiSA): from programming information seeking to learning

Yihan Lu, Ihan Hsiao

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Online programming discussion forums have grown increasingly and formed sizable repositories of problem-solving solutions. In this paper, we investigate programming learners’ information seeking behaviors in online discussion forums, and provide visual navigational support to facilitate information seeking. We design engines to collect students’ information seeking behaviors, and model these behaviors with sequence pattern mining techniques. The results show that programming learners indeed seek for information from discussion forums by actively search and read progressively according to course schedule topics. Advanced students consistently perform query refinements, examine search results and commit to read, however, novices do not. Finally, according to the lessons learned, we propose, design and evaluate Personalized Information Seeking Assistant system to help query refinement by summarizing the search results and to provide social-based browsing history. Findings suggest that paying attention to the query history may lead to further reading events, which subsequently resulting in potential learning activities.

Original languageEnglish (US)
Pages (from-to)1-23
Number of pages23
JournalInformation Retrieval Journal
DOIs
StateAccepted/In press - May 9 2017

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assistant
information-seeking behavior
programming
Students
learning
behavior model
history
Engines
student
event

Keywords

  • Behavior modeling
  • Computing education
  • Information seeking behavior
  • Novice programming learning

ASJC Scopus subject areas

  • Information Systems
  • Library and Information Sciences

Cite this

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abstract = "Online programming discussion forums have grown increasingly and formed sizable repositories of problem-solving solutions. In this paper, we investigate programming learners’ information seeking behaviors in online discussion forums, and provide visual navigational support to facilitate information seeking. We design engines to collect students’ information seeking behaviors, and model these behaviors with sequence pattern mining techniques. The results show that programming learners indeed seek for information from discussion forums by actively search and read progressively according to course schedule topics. Advanced students consistently perform query refinements, examine search results and commit to read, however, novices do not. Finally, according to the lessons learned, we propose, design and evaluate Personalized Information Seeking Assistant system to help query refinement by summarizing the search results and to provide social-based browsing history. Findings suggest that paying attention to the query history may lead to further reading events, which subsequently resulting in potential learning activities.",
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