Board 137: MAKER: Facial Feature Detection Library for Teaching Algorithm Basics in Python
Mehmet Fatih Uçar, Sheng‐Jen Hsieh · 2020
Abstract 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.