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Are you having difficulty?

Published: 06 February 2010 Publication History

Abstract

It would be useful if software engineers/instructors could be aware that remote team members/students are having difficulty with their programming tasks. We have developed an approach that tries to automatically create this semantic awareness based on developers' interactions with the programming environment, which is extended to log these interactions and allow the developers to train or supervise the algorithm by explicitly indicating they are having difficulty. Based on the logs of six programmers, we have found that our approach has high accuracy.

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Y. Sharon. Eclipseye-spying on eclipse. Bachelor's thesis, University of Lugano, 2007.

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cover image ACM Conferences
CSCW '10: Proceedings of the 2010 ACM conference on Computer supported cooperative work
February 2010
468 pages
ISBN:9781605587950
DOI:10.1145/1718918
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 February 2010

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Author Tags

  1. context aware computing
  2. help
  3. machine learning

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CSCW '10
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CSCW '10: Computer Supported Cooperative Work
February 6 - 10, 2010
Georgia, Savannah, USA

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Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

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  • (2021)ProLog2vec: Detecting Novices’ Difficulty in Programming Using Deep LearningIEEE Access10.1109/ACCESS.2021.30675059(53243-53254)Online publication date: 2021
  • (2019)Leveraging the Integrated Development Environment for Learning AnalyticsThe Cambridge Handbook of Computing Education Research10.1017/9781108654555.024(679-706)Online publication date: 15-Feb-2019
  • (2019)The Cambridge Handbook of Computing Education Research10.1017/9781108654555Online publication date: 15-Feb-2019
  • (2018)Contextualizing inferred programming difficultiesProceedings of the 3rd International Workshop on Emotion Awareness in Software Engineering10.1145/3194932.3194937(32-38)Online publication date: 2-Jun-2018
  • (2017)Blending Measures of Programming and Social Behavior into Predictive Models of Student Achievement in Early Computing CoursesACM Transactions on Computing Education10.1145/312025917:3(1-20)Online publication date: 28-Aug-2017
  • (2016)Using (bio)metrics to predict code quality onlineProceedings of the 38th International Conference on Software Engineering10.1145/2884781.2884803(452-463)Online publication date: 14-May-2016
  • (2016)Inferred Awareness to Support Mixed-Activity Collaboration2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC)10.1109/CIC.2016.052(339-348)Online publication date: Nov-2016
  • (2015)Improving Multilingual Collaboration by Displaying How Non-native Speakers Use Automated Transcripts and Bilingual DictionariesProceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems10.1145/2702123.2702498(3463-3472)Online publication date: 18-Apr-2015
  • (2015)Scalable Mixed-Focus Collaborative Difficulty ResolutionProceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing10.1145/2685553.2702686(53-56)Online publication date: 28-Feb-2015
  • (2015)Mining Programming Activity to Promote HelpECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work, 19-23 September 2015, Oslo, Norway10.1007/978-3-319-20499-4_2(23-42)Online publication date: 29-Jul-2015
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