The SIGCSE (the ACM Special Interest Group for Computer Science Education) Technical Symposium is the largest computing education conference worldwide. While the majority of sessions target higher education, there is a growing focus on K-12 education. I’m excited to share some learnings and research nuggets relevant to K-12 CS teachers from SIGCSE 2019.

EFFECTIVE TEACHING PRACTICES

In his keynote, Mark Guzdial made several recommendations for improving computing education:

• Teach CS in other courses/contexts. Mark used an analogy of visiting a foreign country: how much language do you need to know to get by? It’s better to know more, but you don’t need to be fluent to enjoy your time. There is amazing learning power even knowing a small subset of CS.
• Ask students to make predictions during live code demos. Get them to explicitly commit to a prediction, then test, and prompt reflection.
• You don’t have to write code to learn from code.
• Subgoal labeling improves understanding, retention, and transfer, in both blocks- and text-based programming, for both high school and undergraduate students. In fact, just adding text labels to video tutorials makes a significant difference.
• Do what works: pair programming, worked examples, Parsons problems, media computation.

Helen Hu presented a POGIL (process oriented guided inquiry learning) lesson that guides teams of students in constructing their own style conventions for naming variables and writing expressions. See full activity and role cards. See also additional POGIL activities for CS Principles courses.

David Weintrop and colleagues presented research comparing high school students’ performance on blocks-based and text-based questions (similar to the formats used on the AP CS Principles exam). Students across all racial and gender groups performed better on the questions presented in blocks-based form, for all of the concepts studied.

Reading and tracing code is useful in understanding how program code actually works. PRIMM is an approach to planning programming lessons and activities and includes the following stages: Predict, Run, Investigate, Modify, and Make. See sample PRIMM activity sheets.

INCLUSION

In her keynote, Marie desJardin identified five pernicious myths that impede diversity in CS:

1. “He was born to be a computer scientist”
2. “Computer scientists are… {Insert Stereotype Here}”
3. “Anybody can be a computer scientist – girls just don’t want to”
4. “It’s just a joke – don’t you have a sense of humor?”
5. “ ‘Diversity programs’ are just political correctness”

Colleen Lewis created an Apples to Apples-like game for teachers to identify opportunities for inclusive teaching strategies and practice responding to microaggressions. View the printable cards and instructions. See also the critical listening guide from NCWIT (National Center for Women in Information Technology).

The 2018 National Survey of Science and Mathematics Education (NSSME+) surveyed over 2,000 U.S. schools and asked targeted questions about computer science for the first time. A key finding is that most current PD efforts focus on deepening teachers’ CS content knowledge, and there needs to be a greater focus on pedagogy and supporting students from diverse backgrounds. See detailed report and slide deck.

DEBUGGING

An interesting panel on debugging included several useful tidbits:

• Deborah Fields suggested that teachers celebrate a “favorite mistake of the day” to create in-time teaching moments and encourage students to ask questions and share their mistakes. This can lower the stakes of failure and normalize mistakes as part of the process.
• Colleen Lewis encouraged educators to live code in front of classes and explain their thinking, testing, and debugging processes. Model immediate and frequent testing, and promote growth mindset by learning from mistakes. See CS Teaching Tips for debugging.
• Gary Lewandowski synthesized common types of bugs in programs:

The Everyday Computing team presented their newest K-8 learning trajectory on debugging. (See other learning progressions on sequence, repetition, conditionals, and decomposition).

UNPLUGGED LESSONS

Stan Kurkovsky and Stephanie Ludi have developed many hands-on lessons for teaching software engineering principles using LEGOs.

Zack Butler and Ivona Bezakova have curated many different pencil puzzle types and ideas that can be used as context for many high school CS concepts such as arrays, loops, recursion, GUIs, inheritance, and graph traversal. View a sample of puzzles.

TeachingSecurity.org introduces foundational ideas of cybersecurity, built on threat modeling and the human-centered nature of authentication. The lessons are designed to meet the cybersecurity learning objectives in the AP CS Principles (CSP) framework, but they are flexible enough to be used in any high school CS class.

Shuchi Grover and SRI developed a series of unplugged and non-programming, computer-based activities to develop conceptual strong understanding of variables, expressions, loops, and abstraction.

PROGRAMMING ENVIRONMENTS & CURRICULA

p5.js is a Processing JavaScript library and web editor. Processing is a programing language developed specifically for visual artists; p5.js enables web-based programming in Processing. The New York City Department of Education has developed an introduction to media computation course using p5.js.

MYR is an online editor for editing and viewing virtual 3-dimensional worlds. The Engaging Computing Group’s goal is to make programming virtual reality (VR) accessible to beginners. Real-time sync allows users to program and enjoy their work almost instantaneously on a VR headset.

EarSketch is a programming environment that teaches (JavaScript or Python) coding through composing and remixing music in a format similar to Garage Band. The environment enables students to create studio-quality music using over 4,000 samples created by professionals (including Jay Z’s DJ!).

MakeCode from Microsoft is an online, blocks- and text-based programming environment for micro:bits. It has an ever-increasing number of tutorials and course, including a new set of science experiments designed by Carl Lyman to help middle and early high school grade students better understand the forces and behavior of the physical world. Another course uses micro:bits to teach the basics of computer networks.

BlockPy is a web-based, blocks- and text-based Python environment designed for data science and to allow users to authentically solve real-world problems.

The Exploring Computer Science (ECS) team recently published a new e-textiles unit and resources called Stitching the Loop. Students learn to create paper circuits, wristbands, a collaborative mural, and wearables with sensors.

ARTIFICIAL INTELLIGENCE (AI)

The AI4K12 Initiative is joint project of CSTA and AAAI (Association for the Advancement of Artificial Intelligence) to develop national guidelines for teaching AI in K-12. The working group has developed five big ideas in AI and has begun developing a curated AI resource directory for K-12 teachers. See slide deck.

One example of an 11th/12th grade resource in the directory: TensorFlow allows users to tinker with neural networks in the browser.

Of course, this is only a small glimpse of the content presented at SIGCSE 2019. If you want to learn more, view the ACM Digital Library and consider joining SIGCSE in Portland next year.