- Title: CS Frontiers: AI and Machine Learning
- Subject: AI Literacy
- Web page: https://csfrontiers.org/ai-and-machine-learning.html
Description (from website):
Machine learning is a cutting-edge topic in industry and academia. This module is guided by the emergent AI4K12 framework, which includes ideas for how to teach machine learning. Early activities include exploring and classifying real Twitter data using the already-familiar block-based programming environment. Students examine data features from several demo Twitter accounts and use this information to develop their own classification rules. As a class, students can group by certain data features (tweets, vs retweets, etc.) to see how that affects the presence of bots in clusters. Once familiar with classification, students build simple classifiers using datasets of 100s of Twitter accounts. An important component of this module is ethics in ML and biases perpetuated from the pre-existing datasets on which algorithms are trained. Articles and stories from the news are incorporated into these discussions. The second machine learning unit takes a deeper look at classifiers. Students work with ML services, such as IBM Watson, classifying text to detect sentiment such as bullying or not bullying. Students are able to modify the training sets to see how that influences the effectiveness of the algorithm. Students then make modifications to the ML algorithm parameters, and eventually design their own learning systems.
