Enriching programming content semantics: An evaluation of visual analytics approach

Ihan Hsiao; Yi Ling Lin

doi:10.1016/j.chb.2016.10.012

Enriching programming content semantics: An evaluation of visual analytics approach

Ihan Hsiao, Yi Ling Lin

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

In this work, we present an intelligent classroom orchestration technology to capture semantic learning analytics from paper-based programming exams. We design and study an innovative visual analytics system, EduAnalysis, to support programming content semantics extraction and analysis. EduAnalysis indexes each programming exam question to a set of concepts based on the ontology. It utilizes automatic indexing algorithm and interactive visualization interfaces to establish the concepts and questions associations. We collect the indexing ground truths of the targeted set from teachers and experts from the crowd. We found that the system significantly extracted more and diverse concepts from exams and achieved high coherence within exam. We also discovered that indexing effectiveness was especially prevalent for complex content. Overall, the semantic enriching approach for programming problems reveals systematic learning analytics from the paper exams.

Original language	English (US)
Journal	Computers in Human Behavior
DOIs	https://doi.org/10.1016/j.chb.2016.10.012
State	Accepted/In press - May 1 2016

Keywords

Automatic indexing
Interactive visualization
Learning analytics
Programming learning
Semantic indexing
Visual analytics

ASJC Scopus subject areas

Arts and Humanities (miscellaneous)
Human-Computer Interaction
Psychology(all)

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10.1016/j.chb.2016.10.012

Cite this

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title = "Enriching programming content semantics: An evaluation of visual analytics approach",

abstract = "In this work, we present an intelligent classroom orchestration technology to capture semantic learning analytics from paper-based programming exams. We design and study an innovative visual analytics system, EduAnalysis, to support programming content semantics extraction and analysis. EduAnalysis indexes each programming exam question to a set of concepts based on the ontology. It utilizes automatic indexing algorithm and interactive visualization interfaces to establish the concepts and questions associations. We collect the indexing ground truths of the targeted set from teachers and experts from the crowd. We found that the system significantly extracted more and diverse concepts from exams and achieved high coherence within exam. We also discovered that indexing effectiveness was especially prevalent for complex content. Overall, the semantic enriching approach for programming problems reveals systematic learning analytics from the paper exams.",

keywords = "Automatic indexing, Interactive visualization, Learning analytics, Programming learning, Semantic indexing, Visual analytics",

author = "Ihan Hsiao and Lin, {Yi Ling}",

year = "2016",

month = may,

day = "1",

doi = "10.1016/j.chb.2016.10.012",

language = "English (US)",

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T1 - Enriching programming content semantics

T2 - An evaluation of visual analytics approach

AU - Hsiao, Ihan

AU - Lin, Yi Ling

PY - 2016/5/1

Y1 - 2016/5/1

N2 - In this work, we present an intelligent classroom orchestration technology to capture semantic learning analytics from paper-based programming exams. We design and study an innovative visual analytics system, EduAnalysis, to support programming content semantics extraction and analysis. EduAnalysis indexes each programming exam question to a set of concepts based on the ontology. It utilizes automatic indexing algorithm and interactive visualization interfaces to establish the concepts and questions associations. We collect the indexing ground truths of the targeted set from teachers and experts from the crowd. We found that the system significantly extracted more and diverse concepts from exams and achieved high coherence within exam. We also discovered that indexing effectiveness was especially prevalent for complex content. Overall, the semantic enriching approach for programming problems reveals systematic learning analytics from the paper exams.

AB - In this work, we present an intelligent classroom orchestration technology to capture semantic learning analytics from paper-based programming exams. We design and study an innovative visual analytics system, EduAnalysis, to support programming content semantics extraction and analysis. EduAnalysis indexes each programming exam question to a set of concepts based on the ontology. It utilizes automatic indexing algorithm and interactive visualization interfaces to establish the concepts and questions associations. We collect the indexing ground truths of the targeted set from teachers and experts from the crowd. We found that the system significantly extracted more and diverse concepts from exams and achieved high coherence within exam. We also discovered that indexing effectiveness was especially prevalent for complex content. Overall, the semantic enriching approach for programming problems reveals systematic learning analytics from the paper exams.

KW - Automatic indexing

KW - Interactive visualization

KW - Learning analytics

KW - Programming learning

KW - Semantic indexing

KW - Visual analytics

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SN - 0747-5632

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JF - Computers in Human Behavior

ER -

Enriching programming content semantics: An evaluation of visual analytics approach

Abstract

Keywords

ASJC Scopus subject areas

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