About This Webinar
Looking for a professional learning community to expand your AP CSP knowledge and teaching repertoire? Join us for discussion-based, small-group quarterly meetings where we'll cover College Board and CodeHS resources for teaching and test-prep for the AP CSP course. Participants will share their experiences and resources, and will be given time to network with other CSP teachers across the nation.
Discover creative project ideas and Create Performance Task strategies for APCSP. This CodeHS webinar transcript covers image filters, linear search activities, and expert tips on meeting College Board rubrics to help your students excel on the AP exam.
Full Transcript
Read the complete transcript of this webinar
Welcome everyone to our APCSP professional learning community meeting. Tonight we are joined by Chauffen, who is here to share her years of experience in all things AP Computer Science Principles. I will get the document link in the chat for you where we can share ideas, resources, and feedback as we talk about the APCSP course materials available on CodeHS. We want to gather feedback for the curriculum team on a potential course refresh and answer any questions you have.
The goal of this PLC is to foster a collaborative environment where educators can share resources, discuss assessments and test prep strategies, and refine pacing plans to improve student outcomes using CodeHS tools. On the docket today, we are discussing course updates, specifically a refresh of the Python course and several activities in the JavaScript course.
To start, let's introduce ourselves. Chauffen is teaching in Charlotte, North Carolina. Her favorite part of the course is the creativity side, focusing on the five Big Ideas and computational practice skills. James from Jeffersonville, Indiana, shared his love for the image filter exercises, such as grayscale and invert. He even showed students how to build colorblind simulators and adjust the alpha channel for transparency.
This led to a technical discussion about the Create Performance Task requirements. Thomas mentioned the difficulty of using a 2D grid of pixels for the Create Task since the grid isn't managed as a standard list. However, James noted that in Python, the get pixel method returns a list type, which should satisfy the College Board's requirement for using a list or data structure. Chauffen emphasized that as long as the student can explain the iteration through the 2D array and the selection logic used to modify pixels, it counts as a complex data structure suitable for the task.
Thomas shared a "darken and invert" diagonal filter project. He noted that for the performance task, students should avoid relying solely on built-in methods like math.max for their primary algorithm. Instead, they should write out the selection logic (using if-statements) to ensure they meet the rubric requirements for student-developed logic.
Chauffen shared a "Birthday Search" activity used to teach linear search. By having students physically act out searching for a classmate with a specific birthday, they learn to translate real-world actions into code. This helps students grasp the core concept of traversing a list, applying selection logic, and returning a result. She recommended strengthening Unit 7 (Lists) by guiding students through various linear search applications, such as finding specific items in a shopping list or identifying blood type compatibility.
James shared a project about blood types where a function iterates through a list to check donor compatibility. This is a great example of narrowing down possibilities using selection logic. The meeting concluded with a discussion on the value of these PLC meetings. While the format or timing can be a barrier for some, the ability to share specialized projects—like image filters or vocabulary practice videos—is incredibly beneficial for classroom efficiency. We wish everyone and their students the best of luck on the AP test next month.
The goal of this PLC is to foster a collaborative environment where educators can share resources, discuss assessments and test prep strategies, and refine pacing plans to improve student outcomes using CodeHS tools. On the docket today, we are discussing course updates, specifically a refresh of the Python course and several activities in the JavaScript course.
To start, let's introduce ourselves. Chauffen is teaching in Charlotte, North Carolina. Her favorite part of the course is the creativity side, focusing on the five Big Ideas and computational practice skills. James from Jeffersonville, Indiana, shared his love for the image filter exercises, such as grayscale and invert. He even showed students how to build colorblind simulators and adjust the alpha channel for transparency.
This led to a technical discussion about the Create Performance Task requirements. Thomas mentioned the difficulty of using a 2D grid of pixels for the Create Task since the grid isn't managed as a standard list. However, James noted that in Python, the get pixel method returns a list type, which should satisfy the College Board's requirement for using a list or data structure. Chauffen emphasized that as long as the student can explain the iteration through the 2D array and the selection logic used to modify pixels, it counts as a complex data structure suitable for the task.
Thomas shared a "darken and invert" diagonal filter project. He noted that for the performance task, students should avoid relying solely on built-in methods like math.max for their primary algorithm. Instead, they should write out the selection logic (using if-statements) to ensure they meet the rubric requirements for student-developed logic.
Chauffen shared a "Birthday Search" activity used to teach linear search. By having students physically act out searching for a classmate with a specific birthday, they learn to translate real-world actions into code. This helps students grasp the core concept of traversing a list, applying selection logic, and returning a result. She recommended strengthening Unit 7 (Lists) by guiding students through various linear search applications, such as finding specific items in a shopping list or identifying blood type compatibility.
James shared a project about blood types where a function iterates through a list to check donor compatibility. This is a great example of narrowing down possibilities using selection logic. The meeting concluded with a discussion on the value of these PLC meetings. While the format or timing can be a barrier for some, the ability to share specialized projects—like image filters or vocabulary practice videos—is incredibly beneficial for classroom efficiency. We wish everyone and their students the best of luck on the AP test next month.
