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Achieving "A's for All (as Time and Interest Allow)"

Published: 01 June 2022 Publication History

Abstract

The SIGCSE-MEMBERS mailing list of the ACM Special Interest Group in Computer Science Education is the main forum for educators worldwide to discuss computing education research, pedagogy, and curriculum. In early 2022 it was abuzz with several connected movements: growth mindset, proficiency (aka mastery) learning, grading for equity, and specifications grading. Each of these is an important step toward the Holy Grail: A's for All (as time and interest allow); the "A" line doesn't move, but every student should be given an opportunity to achieve proficiency and earn it, as long as they are willing to put in the time and effort it might take. The mantra is not "fixed time, variable learning", but "fixed learning, variable time". The goal of this full-day workshop is to provide educators and administrators with tools to achieve it in their courses and institutions.
One useful analogy is that enrolling in a course is like taking a trip by bus: there is one speed for everyone, it lasts 10 or 15 weeks, and at the end of the trip a calculation is made regarding what percentage of the pile of points has been earned, and an A-F grade is assigned. What happens when someone needs (or wants) to travel slower, and as a result will get off the bus? Do they wait a whole term for the next bus? Can they work on their own? Do they get on the "local" bus that goes slower, perhaps with a supportive cohort who also needed to go slower? This is typically not allowed by our assembly-line model of learning, yet there are many ways that an institution can support these students, which we will address.
From ten miles up, what are all the elements that have to align to allow it to happen? It helps to have a leader who is passionate about equity, supported by their administration, and willing to put in a significant amount of work up front. Many in this Learning@Scale community who have already moved their traditional University class to a MOOC will find those efforts bearing fruit here. If the course is the first through the gate to adopt this model, there may be socialization among colleagues that is needed.

Supplementary Material

MP4 File (Workshop FINAL.mp4)
Learning @ Scale 2022 Workshop: Achieving "A's for All (as Time and Interest Allow)", narrated and presented by Dan Garcia

References

[1]
Andrew Berns, J. Philip East, and J. Ben Schafer. 2021. Grading for Equity: A Curriculum Development and Grading Process to Enhance Instruction. Association for Computing Machinery, New York, NY, USA, 1351. https://doi.org/10.1145/3408877.3432503
[2]
Benjamin S. Bloom. 1968. Learning for Mastery. Instruction and Curriculum. Regional Education Laboratory for the Carolina and Virginia, Topical Papers and Reprints, Number 1. Evaluation comment 1, 2 (1968), n2.
[3]
Benjamin S. Bloom. 1984. The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring. Educational Researcher 13, 6 (1984), 4--16. https://doi.org/10.3102/0013189X013006004 arXiv:https://doi.org/10.3102/0013189X013006004
[4]
C.S. Dweck. 2006. Mindset: The New Psychology of Success. Random House Publishing Group. https://books.google.com/books?id=fdjqz0TPL2wC
[5]
J. Feldman. 2018. Grading for Equity: What It Is, Why It Matters, and How It Can Transform Schools and Classrooms. SAGE Publications. https://books.google.com/books?id=ORhoDwAAQBAJ
[6]
Sarah Hug. 2021. How Do Faculty Convey Growth Mindset in Computer Science Teaching? A Preliminary Qualitative Study. Association for Computing Machinery, New York, NY, USA, 1285. https://doi.org/10.1145/3408877.3439663
[7]
David MacKay. 2005. Everyone Should Get an A. https://www.inference.org.uk/mackay/exams.pdf
[8]
L.B. Nilson and C.J. Stanny. 2015. Specifications Grading: Restoring Rigor, Motivating Students, and Saving Faculty Time. Stylus Publishing. https://books.google.com/books?id=UrCpCwAAQBAJ
[9]
ACM SIGCSE. 2022. Mailing Lists. https://sigcse.org/membership/mailinglists.html
[10]
TED. 2010. Sir Ken Robinson: Changing education paradigms. https://www.ted.com/talks/sir_ken_robinson_changing_education_paradigms
[11]
Matthew West, Geoffrey L. Herman, and Craig Zilles. 2015. Prairie Learn: Mastery-based Online Problem Solving with Adaptive Scoring and Recommendations Driven by Machine Learning. In 2015 ASEE Annual Conference & Exposition. ASEE Conferences, Seattle, Washington.
[12]
Ursula Wolz, Gail Carmichael, Dan Garcia, Bonnie MacKellar, and Nanette Veilleux. 2020. To Grade or Not To Grade. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (Portland, OR, USA) (SIGCSE '20). Association for Computing Machinery, New York, NY, USA, 479--480. https://doi.org/10.1145/3328778.3366978
[13]
Craig Zilles, Matthew West, Geoffrey Herman, and Timothy Bretl. 2019. Every University Should Have a Computer-Based Testing Facility. In Proceedings of the 11th International Conference on Computer Supported Education (CSEDU).

Cited By

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  • (2024)Automated Support for Flexible ExtensionsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3635628(1810-1811)Online publication date: 14-Mar-2024
  • (2024)Supporting Mastery Learning with Flexible ExtensionsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3635615(1834-1835)Online publication date: 14-Mar-2024
  • (2023)Does the Availability of Reattempts and Video Solutions Affect Learners' Voluntary Engagement with Mastery Learning Activities?Proceedings of the Tenth ACM Conference on Learning @ Scale10.1145/3573051.3596201(421-425)Online publication date: 20-Jul-2023

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    L@S '22: Proceedings of the Ninth ACM Conference on Learning @ Scale
    June 2022
    491 pages
    ISBN:9781450391580
    DOI:10.1145/3491140
    This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 01 June 2022

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    Author Tags

    1. assessment
    2. communities of practice
    3. pedagogy
    4. scalable

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    • California Education Learning Lab

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    L@S '22
    L@S '22: Ninth (2022) ACM Conference on Learning @ Scale
    June 1 - 3, 2022
    NY, New York City, USA

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    Overall Acceptance Rate 117 of 440 submissions, 27%

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    View all
    • (2024)Automated Support for Flexible ExtensionsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3635628(1810-1811)Online publication date: 14-Mar-2024
    • (2024)Supporting Mastery Learning with Flexible ExtensionsProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 210.1145/3626253.3635615(1834-1835)Online publication date: 14-Mar-2024
    • (2023)Does the Availability of Reattempts and Video Solutions Affect Learners' Voluntary Engagement with Mastery Learning Activities?Proceedings of the Tenth ACM Conference on Learning @ Scale10.1145/3573051.3596201(421-425)Online publication date: 20-Jul-2023

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