Osgood, L. E., & Bressan, N., & McBurney, A. H. (2023, June), Using Machine Learning to Assess Breadboardia: a Technical Storybook  Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44579

\bibitem{asee_peer_44579}
  Osgood, L. E., \& Bressan, N., \& McBurney, A. H. (2023, June), \emph{Using Machine Learning to Assess Breadboardia: a Technical Storybook}
  Paper presented at 2023 ASEE Annual Conference \& Exposition, Baltimore , Maryland.
  10.18260/1-2--44579

Libby (Elizabeth) Osgood, Nadja Bressan, and Aiden Hender McBurney.  "Using Machine Learning to Assess Breadboardia: a Technical Storybook".  2023 ASEE Annual Conference & Exposition, Baltimore , Maryland, 2023, June.  ASEE Conferences, 2023.  https://peer.asee.org/44579 Internet.  14 Apr, 2025

\bibitem{asee_peer_44579}
  Libby (Elizabeth) Osgood, Nadja Bressan, and Aiden Hender McBurney.
  "Using Machine Learning to Assess Breadboardia: a Technical Storybook".
  \emph{2023 ASEE Annual Conference \& Exposition, Baltimore , Maryland, 2023, June}.
  ASEE Conferences, 2023.
  https://peer.asee.org/44579 Internet.  14 Apr, 2025

@INPROCEEDINGS{asee_peer_44579
author = "Libby (Elizabeth) Osgood, Nadja Bressan, and Aiden Hender McBurney"
title = "Using Machine Learning to Assess Breadboardia: a Technical Storybook"
booktitle = "2023 ASEE Annual Conference \& Exposition"
year = "2023"
month = "June"
address = "Baltimore , Maryland"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/44579}
number = {10.18260/1-2--44579}
}

TY  - CPAPER
AB  - This paper documents the continuation of a long-term study on the use of storytelling to deliver technical electronics content. Stories have the ability to capture our attention and improve our retention. A particularly dry technical topic becomes engaging when introduced with a personal story. Lessons become more obvious, understood more fully, and retained for longer when delivered in the narrative form. A storybook was developed to introduce first-year engineering students to breadboards. The right-hand pages contain a narrative story about bringing light to a town, and the left-hand pages contain the corresponding technical information instructing students to build a simple LED circuit. The previous study found that a storybook is as effective as a lecture at delivering technical content, and participants who were exposed to the storybook were able to complete the activity faster than those who received the lecture. This paper proposes a revised instrument and protocol that employs machine learning for data analysis to assess technical learning objectives, retention of the material, and anxiety levels related to technology.
AU  - Libby (Elizabeth) Osgood
AU  - Nadja Bressan
AU  - Aiden Hender McBurney
CY  - Baltimore , Maryland
DA  - 2023/06/25
PB  - ASEE Conferences
TI  - Using Machine Learning to Assess Breadboardia: a Technical Storybook
UR  - https://peer.asee.org/44579
DO  - 10.18260/1-2--44579
ER  -