Introduction to Computer Science and Computational Thinking
LEVEL: Introductory - Any K-8 educator who is new to teaching computer science
RECOMMENDED GRADES: K - 8
FACILITATORS: Northern Lights Collaborative Staff
The Intro to CS/CT professional development will allow educators to expand their understanding of computer science and computational thinking. Specifically, the PD will seek to build agency within educators to teach computer science and computational thinking in their classrooms. In addition, the PD will aim to increase pedagogical content knowledge by addressing issues of equity in CS and demonstrating effective CS teaching. Lastly, this PD will provide teachers with the skills to include and engage all students in computer science by utilizing culturally responsive-sustaining pedagogy and Universal Design for Learning (UDL) principles. Lessons in various grade bands and subject areas will be available for educators. Educators will also have the opportunity to customize and create their own lessons.
Learning Objectives:
- Explain what computer science (CS) and computational thinking (CT) are and why all K-12 students should learn them
- Utilize CS/CT education frameworks, resources, and tools
- Align CS learning activities to the Minnesota CS State Strategic Plan and CS-integrated benchmarks
CS Integration with Physical Computing
LEVEL: Intermediate - some CS experience; participants should be comfortable using a computer to navigate websites. Familiarity with block-based programming languages like Scratch and MakeCode will be helpful.
RECOMMENDED GRADES: 3 - 10
FACILITATORS: Northern Lights Collaborative Staff
This workshop provides hands-on experience integrating physical computing into grades 4-10 classrooms using Makey Makey and micro:bit. Participants will use Microsoft MakeCode for block-based and text-based coding to build functional projects like assistive game controllers, moving dioramas, AI models, and sensor-based interactive displays. Throughout the sessions, educators will develop standards-aligned lesson plans that meet MDE Integrated CS and CSTA standards. Every participant will finish the workshop with a tested physical prototype and a documented implementation strategy tailored to their specific grade level and subject area.
Learning Objectives:
- Create, test, and troubleshoot physical computing projects using micro:bit and Makey Makey by applying hardware and software problem-solving processes.
- Design and integrate effective instructional practices that align physical computing activities with Grade 3-10 Science, Math, and Arts curricula and with CSTA and Minnesota standards.
- Explain how hardware and software components of a computing system work together to perform input and output (I/O), processing, and storage.
- Support confident and successful physical computing experiences and engagement for students.
Experience CS
LEVEL: Introductory - no CS experience required
RECOMMENDED GRADES: 3 - 8
FACILITATOR: Raspberry Pi Foundation Staff
In this session, we will showcase Experience CS, the Raspberry Pi Foundation’s new integrated computer science units designed to foster a joyful learning community through cross-curricular projects. We will discuss how educators can adapt these resources to build on student strengths, interests, and backgrounds and make CS relevant and meaningful. We will explore how integrating CS elevates collaboration, leadership, and student agency in the classroom and show lessons that helped build student confidence through creative expression and computational thinking.
Learning Objectives:
- Identify opportunities to bring CS to my students.
- Recognize practical opportunities to integrate CS into my classroom.
- Adapt existing computing resources to meet my students’ needs.
Introduction to Artificial Intelligence
LEVEL: Introductory - No previous CS or AI experience required
RECOMMENDED GRADES: K - 12
FACILITATOR: Northern Lights Collaborative Staff
This workshop helps educators build foundational AI literacy and develop human-centered approaches for using AI in teaching and learning. Participants will explore what Generative AI is, how it works at a conceptual level, and how to make thoughtful decisions about when to use AI tools in educational settings. Through guided discussion, scenario-based analysis, and hands-on exploration of accessible AI tools and classroom examples, participants will examine issues such as bias, accuracy, privacy, ethics, and responsibility when using AI. Educators will leave with practical strategies for supporting responsible AI use and helping students think critically about AI in everyday life. This workshop does not require prior computer science experience or programming knowledge.
Learning Objectives:
- Explain foundational concepts of AI literacy.
- Evaluate the benefits, risks, and ethical implications of AI tools used in educational settings.
- Apply human-centered principles to determine when AI tools are appropriate for classroom tasks.
- Adapt a classroom activity that helps students engage with AI in informed, ethical, and reflective ways.
Telling Stories with Data: CS Thinking Through Human Data
LEVEL: Intermediate - some CS or statistics experience
RECOMMENDED GRADES: 6 - 12
FACILITATOR: Kate Lockwood and Madeline Burton, Northern Lights Collaborative
In this three-day workshop, CS teachers explore how data investigations become more powerful and accessible when they're built around real stories that matter to students. Participants will explore data science as an onramp to computational thinking, using unplugged activities and Jupyter notebooks to build a teaching toolkit that puts concepts before code. They will visualize datasets to tell the stories of their communities. Drawing on the Data 6 curriculum from UC Berkeley, participants move between doing data investigations as learners and breaking them down as teachers, picking up replicable moves for bringing CS ideas to life through story and real-world sensemaking.
Learning Objectives:
- Explore the story behind a data set based on data moves that create visualizations and summary statistics
- Select the most meaningful and impactful way to present data about their communities
- Interpret what those visualizaitons reveal (and what they hide) about the people and context behind the data
- Connect data in meaningful ways to curriculum in multiple subjects
- Design a data investigation built around a story that matters to their students, sequenced from human question to computational answer.
Cybersecurity Standards & Curricula
LEVEL: Introductory - No prior experience in cybersecurity or computer science is required; we will discuss different methods of teaching cyber themes depending on students' past experience.
RECOMMENDED GRADES: 6 - 12
FACILITATOR: Jessica Brent and Derek Babb, Northern Lights Collaborative
We will explore core themes in cybersecurity, including encryption, risks and threats, networking basics, introductory command line labs, social engineering, and physical security. Sessions will emphasize hands-on, practical experiences that teachers can immediately bring into their classrooms. Educators will examine a range of developmentally appropriate curricula, from middle school Intro to Technology courses to high school pathways such as AP Cybersecurity and other CTE-aligned programs. We will focus on inclusive teaching strategies that engage diverse learners and broaden participation in cybersecurity. Participants will leave with ready-to-use resources, adaptable lesson ideas, and a clear understanding of how cybersecurity concepts align with CSTA standards and state guidelines.
Learning Objectives:
- Summarize major themes in Cybersecurity.
- Critique multiple Cybersecurity curricula.
- Develop a plan to teach Cybersecurity in your context.
AI in CS Education
LEVEL: Intermediate - This workshop is intended for educators who have previously taught computer science, are comfortable reading and discussing code, and have helped students complete programming tasks; participants do not need prior experience teaching AI or machine learning.
RECOMMENDED GRADES: K - 12
FACILITATOR: Northern Lights Collaborative Staff
This workshop is designed for educators who already have foundational CS teaching experience and want to deepen their understanding of AI and machine learning as computer science content. Across three days, participants will engage in hands-on investigations related to machine learning models and training data, while also examining how AI can support programming work and where AI-generated code can fail. Participants will analyze AI-generated code for accuracy, usability, and reliability. Additionally, they will explore strategies for prompting, reviewing, and refining AI-assisted programming outputs. Throughout the workshop, educators will work within a human-centered and ethical frame and will have structured time to review, adapt, or create standards-aligned lessons and activities they can use in their own classrooms.
Learning Objectives: to be added