An Introduction to Rule-Based Feature and Object Perception for Middle School Students
Daniella DiPaola, Parker Malachowsky, Nancye Blair Black, Sharifa Alghowinem, Xiaoxue Du, Cynthia Breazeal
Abstract
The Feature Detection tool is a web-based activity that allows students to detect features in images and build their own rule-based classification algorithms. In this paper, we introduce the tool and share how it is incorporated into two, 45-minute lessons. The objective of the first lesson is to introduce students to the concept of feature detection, or how a computer can break down visual input into lower-level features. The second lesson aims to show students how these lower-level features can be incorporated into rule-based models to classify higher-order objects. We discuss how this tool can be used as a "first step" to the more complex concept ideas of data representation and neural networks.
BibTeX
@article{DiPaola_Malachowsky_Blair Black_Alghowinem_Du_Breazeal_2024, title={An Introduction to Rule-Based Feature and Object Perception for Middle School Students}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/26900}, DOI={10.1609/aaai.v37i13.26900}, abstractNote={The Feature Detection tool is a web-based activity that allows students to detect features in images and build their own rule-based classification algorithms. In this paper, we introduce the tool and share how it is incorporated into two, 45-minute lessons. The objective of the first lesson is to introduce students to the concept of feature detection, or how a computer can break down visual input into lower-level features. The second lesson aims to show students how these lower-level features can be incorporated into rule-based models to classify higher-order objects. We discuss how this tool can be used as a "first step" to the more complex concept ideas of data representation and neural networks.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={DiPaola, Daniella and Malachowsky, Parker and Blair Black, Nancye and Alghowinem, Sharifa and Du, Xiaoxue and Breazeal, Cynthia}, year={2024}, month={Jul.}, pages={16004-16010} }