abstract

Understanding the Effects of Lecturer Intervention on Computer Science Student Behaviour

Authors:

Francesco MaioranaAuthors Info & Claims

ITiCSE '17: Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education

Page 391

https://doi.org/10.1145/3059009.3081330

Published: 28 June 2017 Publication History

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Abstract

A key challenge for computer science educators worldwide is providing effective feedback and support to students, to ensure they are engaged with the course. This includes online feedback on discussion forums as well as feedback on programming assignments. Due to the significant problems of scale that need to be addressed, effective lecturer intervention is difficult, and at the same time the effect of intervention in online discussion forums is challenging to measure accurately. The same problem occurs when marking programming assignments, where detailed, in-depth feedback is often replaced with output from failed testcases, which the students sometimes proceed to address without giving thought to the quality of their overall solutions.

The working group will (1) identify and survey existing literature on quantifying lecturer intervention in online discussion forums and on assignment feedback, (2) identify existing datasets that could be used to study intervention in depth, (3) identify key data characteristics and associated tools that can be used to effectively process the data, and (4) identify and outline key recommendations for effective lecturer intervention. The outcome of this working group will be a report but the working group will also bring together researchers focused on understanding effective lecturer intervention, thus contributing to the growth of the community.

Cited By

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de Freitas ACoffman Jde Freitas MWilson JWeingart TDoyle MStephenson BDorn BSoh LBattestilli L(2023)FalconCode: A Multiyear Dataset of Python Code Samples from an Introductory Computer Science CourseProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569822(938-944)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569822

Index Terms

Understanding the Effects of Lecturer Intervention on Computer Science Student Behaviour
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education

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Published In

ITiCSE '17: Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education

June 2017

412 pages

ISBN:9781450347044

DOI:10.1145/3059009

Conference Chairs:
Renzo Davoli
University of Bologna, Italy
,
Michael Goldweber
Xavier University, USA
,
Program Chairs:
Guido Rößling
Technische Universität Darmstadt, Germany
,
Irene Polycarpou
University of Central Lancashire, Cyprus

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 28 June 2017

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ITiCSE '17

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SIGCSE

ITiCSE '17: Innovation and Technology in Computer Science Education

July 3 - 5, 2017

Bologna, Italy

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ITiCSE '17 Paper Acceptance Rate 56 of 175 submissions, 32%;

Overall Acceptance Rate 552 of 1,613 submissions, 34%

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ITiCSE '25

Sponsor:
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Innovation and Technology in Computer Science Education

June 27 - July 2, 2025

Nijmegen , Netherlands

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de Freitas ACoffman Jde Freitas MWilson JWeingart TDoyle MStephenson BDorn BSoh LBattestilli L(2023)FalconCode: A Multiyear Dataset of Python Code Samples from an Introductory Computer Science CourseProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569822(938-944)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569822

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