Ucar, M., & Hsieh, S. (2018, June), Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python  Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--29934

\bibitem{asee_peer_29934}
  Ucar, M., \& Hsieh, S. (2018, June), \emph{Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python}
  Paper presented at 2018 ASEE Annual Conference \& Exposition , Salt Lake City, Utah.
  10.18260/1-2--29934

Mehmet Ucar and Sheng-Jen Hsieh.  "Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python".  2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah, 2018, June.  ASEE Conferences, 2018.  https://216.185.13.174/29934 Internet.  05 May, 2024

\bibitem{asee_peer_29934}
  Mehmet Ucar and Sheng-Jen Hsieh.
  "Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python".
  \emph{2018 ASEE Annual Conference \& Exposition , Salt Lake City, Utah, 2018, June}.
  ASEE Conferences, 2018.
  https://216.185.13.174/29934 Internet.  05 May, 2024

@INPROCEEDINGS{asee_peer_29934
author = "Mehmet Ucar and Sheng-Jen Hsieh"
title = "Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python"
booktitle = "2018 ASEE Annual Conference \& Exposition "
year = "2018"
month = "June"
address = "Salt Lake City, Utah"
publisher = "ASEE Conferences"
note = {https://216.185.13.174/29934}
number = {10.18260/1-2--29934}
}

TY  - CPAPER
AB  - High school students sometimes have difficulty understanding the concept of an algorithm in computer programming.  This paper describes a facial feature detection library and instructional procedures to teach beginning-level programmers about algorithms. Writing programs to detect facial features such as ears, nose, and eyes can be motivating but challenging. An interactive graphical user interface was designed to simplify this task. The interface includes icons for facial features such as ears, nose, and eyes. Each icon corresponds to a set of feature detection algorithms. Student can select a feature icon, import an image, and run the program. The program will show detection results for the selected feature icon. After reviewing the results, students can open the code window of the selected feature and review and revise the code to improve the feature detection performance. Through this process, students can improve both their understanding of algorithms and their programming skills. Results suggest that the instructional module is effective and the task is enjoyable for students.
AU  - Mehmet Ucar
AU  - Sheng-Jen Hsieh
CY  - Salt Lake City, Utah
DA  - 2018/06/23
PB  - ASEE Conferences
TI  - Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python
UR  - https://216.185.13.174/29934
DO  - 10.18260/1-2--29934
ER  -