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From Data To Insights in CS1

Published: 02 July 2019 Publication History

Abstract

In this poster, we present some insights from student interaction data based on a year-long study on how to rethink the instructional model of a large CS1 (n=800) course. A key goal of the study was to address the increasing academic diversity in large introductory courses. The redesigned curriculum uses a combination of automation, real-time data and a better utilization of teaching staff to deliver an enhanced learning experience. The new measures demonstrated significant improvements in student engagement and over 90% course satisfaction.

References

[1]
A.D. Gunawardena, J. Barr (2010). Encouraging Reading and Collaboration using Classroom Salon. ITiCSE'10 Proceedings of the fifteenth annual conference on Innovation and technology in computer science education, ACM New York, USA ISBN: 978--1--60558--820--9.
[2]
Acurate, an online platform for curated interactive videos, http://acurate.io

Cited By

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  • (2023)The Applications of Learning Analytics to Enhance Learning and Engagement in Introductory Programming InstructionPerspectives on Learning Analytics for Maximizing Student Outcomes10.4018/978-1-6684-9527-8.ch005(89-108)Online publication date: 24-Oct-2023

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Published In

cover image ACM Conferences
ITiCSE '19: Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education
July 2019
583 pages
ISBN:9781450368957
DOI:10.1145/3304221
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

Publication History

Published: 02 July 2019

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Author Tags

  1. analytics
  2. introductory cs
  3. video-based instruction

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  • Poster

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  • Princeton University

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ITiCSE '19
Sponsor:

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

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  • (2023)The Applications of Learning Analytics to Enhance Learning and Engagement in Introductory Programming InstructionPerspectives on Learning Analytics for Maximizing Student Outcomes10.4018/978-1-6684-9527-8.ch005(89-108)Online publication date: 24-Oct-2023

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