CSTANJ CSPDWeek 2026

In this presentation participants will explore steps in the data science process including statistical questions, data collection, bias, data cleaning and analysis, and graphical displays.

Participants will be given a brief introduction to steps in the data science process. These include forming good statistical research questions, collecting data, cleaning data, statistics, exploratory data analysis, and interpretation of graphical data displays. Special consideration will be given to dealing with bias in data collection and presentation, and ethical use of data. This presentation will align topics with the new NJ Computer Science standards and will provide materials for use in the classroom and/or further study.

This interactive workshop helps middle and high school educators transform foundational AI concepts into practical classroom experiences. Participants will explore selected AI tools through hands-on applications, design student-ready activities, and learn how inviting a guest AI expert can strengthen both conceptual understanding and real-world relevance. The session offers a theory-to-practice model that educators can directly adapt for engaging classroom instruction.

This workshop presents a classroom-ready model for helping middle and high school educators move from foundational AI concepts to direct classroom application. The session begins with a concise conceptual overview of how AI tools can support creativity, critical thinking, and student-centered learning across different subject areas. Participants will then engage in guided hands-on activities using selected AI tools to design student-ready classroom tasks and mini-projects.

A distinctive component of the workshop is the integration of a live guest AI expert, demonstrating how real-world voices from academia or industry can strengthen relevance, increase student motivation, and connect classroom learning with authentic applications. The session concludes with strategies for adapting this theory-to-practice model into participants’ own classrooms through reusable activity structures, guest speaker formats, and age-appropriate AI learning experiences for students ages 11–18.

Artificial Intelligence is rapidly transforming how we collect, analyze, and act on data—but how do we translate this into meaningful classroom experiences?

In this interactive session, participants will explore practical strategies for integrating AI into Data Science instruction using real-world datasets and accessible classroom tools. Artificial Intelligence is rapidly transforming how we collect, analyze, and act on data—but how do we translate this into meaningful classroom experiences?

In this interactive session, participants will explore practical strategies for integrating AI into Data Science instruction using real-world datasets and accessible classroom tools. Drawing from my immersive experience at the University of New Mexico, diving into Data Science + AI with Bootstrap as the sponsor (June 22nd-27th, 2026), this session highlights how educators can move beyond theory and empower students to:
1. Analyze real datasets using AI-supported tools
2. Identify patterns, trends, and anomalies
3. Make ethical, data-driven decisions
4. Understand bias, limitations, and responsible AI use
5. Participants will leave with ready-to-use lesson ideas, student project frameworks, and tools that support equitable and engaging AI learning experiences aligned to CSTA standards.