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09-05-2017 | Search as Learning

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

Authors: Yihan Lu, I-Han Hsiao

Published in: Discover Computing | Issue 5/2017

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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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Title: Personalized Information Seeking Assistant (PiSA): from programming information seeking to learning
Authors: Yihan Lu
I-Han Hsiao
Publication date: 09-05-2017
Publisher: Springer Netherlands
Published in: Discover Computing / Issue 5/2017
Print ISSN: 2948-2984
Electronic ISSN: 2948-2992
DOI: https://doi.org/10.1007/s10791-017-9305-y

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Other articles of this Issue 5/2017

Online searching and learning: YUM and other search tools for children and teachers

The role of domain knowledge in cognitive modeling of information search

Introduction to the special issue on search as learning

There’s a creepy guy on the other end at Google!: engaging middle school students in a drawing activity to elicit their mental models of Google

The orchestration of a collaborative information seeking learning task

Optimizing search results for human learning goals

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