Kiremire, A., & Cherry, K. A. (2024, June), Board 52: Work in Progress: Datastorm: Using Data-Driven Competition to Improve Student Engagement in Computer Science  Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://strategy.asee.org/47049

\bibitem{asee_peer_47049}
  Kiremire, A., \& Cherry, K. A. (2024, June), \emph{Board 52: Work in Progress: Datastorm: Using Data-Driven Competition to Improve Student Engagement in Computer Science}
  Paper presented at 2024 ASEE Annual Conference \& Exposition, Portland, Oregon.
  https://strategy.asee.org/47049

Ankunda Kiremire and Kevin A Cherry.  "Board 52: Work in Progress: Datastorm: Using Data-Driven Competition to Improve Student Engagement in Computer Science".  2024 ASEE Annual Conference & Exposition, Portland, Oregon, 2024, June.  ASEE Conferences, 2024.  https://strategy.asee.org/47049 Internet.  30 Jul, 2024

\bibitem{asee_peer_47049}
  Ankunda Kiremire and Kevin A Cherry.
  "Board 52: Work in Progress: Datastorm: Using Data-Driven Competition to Improve Student Engagement in Computer Science".
  \emph{2024 ASEE Annual Conference \& Exposition, Portland, Oregon, 2024, June}.
  ASEE Conferences, 2024.
  https://strategy.asee.org/47049 Internet.  30 Jul, 2024

@INPROCEEDINGS{asee_peer_47049
author = "Ankunda Kiremire and Kevin A Cherry"
title = "Board 52: Work in Progress: Datastorm: Using Data-Driven Competition to Improve Student Engagement in Computer Science"
booktitle = "2024 ASEE Annual Conference \& Exposition"
year = "2024"
month = "June"
address = "Portland, Oregon"
publisher = "ASEE Conferences"
note = {https://strategy.asee.org/47049}
}

TY  - CPAPER
AB  - Studies have shown that Computer Science and other computing-based courses with traditional pedagogy suffer from low student engagement, low student retention, and a lack of real time evaluation tools for the instructors of these subjects. In this paper, the authors present an innovative solution to all three problems.
“Datastorm” is a series of data-driven competitions among teams of undergraduate students in which the student teams are tasked with imagining creative solutions to real data structure problems. The student teams must build and test their solutions using data from culturally relevant sources in a collaborative and time-restricted environment.
Pilot results show that the In Class Datastorm events increase student engagement, improve student retention, and provide a viable and alternative evaluation tool for computing instructors.
This paper and the work presented therein is relevant to instructors of computer science courses at the undergraduate and high school levels who are looking for ways to increase student engagement from current Computer Science students as well as interest in Computer Science as a potential education path for students outside of the field.
Future work includes expanding its implementation to more class sections, collecting data on these results, as well as identifying and cultivating relationships with local businesses and organizations to increase the quantity and scope of culturally relevant data that can be incorporated into the Datastorm challenges. We also plan to host annual full-day Datastorm events, which should provide visibility and outreach opportunities to other undergraduate students at our institution as well as highlight the relevance of the Computer Science program to the general public.
AU  - Ankunda Kiremire
AU  - Kevin A Cherry
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Board 52: Work in Progress: Datastorm: Using Data-Driven Competition to Improve Student Engagement in Computer Science
UR  - https://strategy.asee.org/47049
ER  -