Hingle, A., & Johri, A. (2023, March), A Research Study on Student Conceptions of Artificial Intelligence  Paper presented at ASEE Southeast Section Conference, Arlington, Virginia. 10.18260/1-2--44979

\bibitem{asee_peer_44979}
  Hingle, A., \& Johri, A. (2023, March), \emph{A Research Study on Student Conceptions of Artificial Intelligence}
  Paper presented at ASEE Southeast Section Conference, Arlington, Virginia.
  10.18260/1-2--44979

Ashish Hingle and Aditya Johri.  "A Research Study on Student Conceptions of Artificial Intelligence".  ASEE Southeast Section Conference, Arlington, Virginia, 2023, March.  ASEE Conferences, 2023.  https://peer.asee.org/44979 Internet.  13 May, 2024

\bibitem{asee_peer_44979}
  Ashish Hingle and Aditya Johri.
  "A Research Study on Student Conceptions of Artificial Intelligence".
  \emph{ASEE Southeast Section Conference, Arlington, Virginia, 2023, March}.
  ASEE Conferences, 2023.
  https://peer.asee.org/44979 Internet.  13 May, 2024

@INPROCEEDINGS{asee_peer_44979
author = "Ashish Hingle and Aditya Johri"
title = "A Research Study on Student Conceptions of Artificial Intelligence"
booktitle = "ASEE Southeast Section Conference"
year = "2023"
month = "March"
address = "Arlington, Virginia"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/44979}
number = {10.18260/1-2--44979}
}

TY  - CPAPER
AB  - Artificial Intelligence (AI), algorithms, and machine learning are foundational concepts in media, tech, and public policy, and the knowledge of these concepts generally contributes to a benchmark for AI literacy. However, these concepts have ambiguous meanings due to sources defining these concepts with varying levels of expertise, understanding, and imagination. These definitions are also ever-changing due to the ever-moving pace of technology, and public AI literacy is currently at surface level at best. For students, the exposure to different sources of formal and informal information may influence their understanding of these topics. Many AI literacy initiatives have focused on pre-college interventions to develop AI literacy and build student competencies from a younger age. However, these interventions may not be reaching every student by the time they enter higher education, resulting in even technology students missing a proper understanding of these foundational concepts. This research explores how first- and second-year technology students define the concepts of artificial intelligence, algorithms, and machine learning, and the sources that have influenced their understanding of these concepts. We collected student survey responses from 61 students representing technology majors such as cybersecurity, application development, telecommunications, networking, and databases. A thematic analysis was conducted on the student responses, and representative themes generated. Overall, we found that students had trouble differentiating between these three concepts. Additionally, the sources of information for each were largely different. For AI, books, movies, and media were often cited, for algorithms, math and computational classes were cited, and for machine learning, personal interest and discipline skills development was highly cited. This work highlights the continued need to explore deficiencies in AI literacy interventions for incoming higher education students and address some possible reasons for students preconceived notions of AI.
AU  - Ashish Hingle
AU  - Aditya Johri
CY  - Arlington, Virginia
DA  - 2023/03/12
PB  - ASEE Conferences
TI  - A Research Study on Student Conceptions of Artificial Intelligence
UR  - https://peer.asee.org/44979
DO  - 10.18260/1-2--44979
ER  -