Teaching computer programming to K-12 learners is widely recognized as important for invoking interest in computing in college and beyond. Specifically, with respect to middle school students, several computing education efforts do an excellent job of making the curricula engaging through block-based and multimedia project-based content. However, the programming concepts covered are notably and understandably simpler than those covered in college-level AP CS or CS1. We instead believe that today's college-level CS1 curricula can and should be taught to middle school and early high school students. In this paper, we discuss our efforts in adapting the CS1 course offered at a large public university, for teaching programming to this age group. Over the course of 15 months, we designed and taught the adapted 16-lecture course to multiple sections of middle and early high school students (ranging from 6th to 10th grade and beyond). Our adaptations included persistent use of memory diagrams, extensive practice, and engaging reviews. Analysis of the final course assessment and surveys showed that these students were able to learn CS1 concepts in depth. Our results held regardless of grade level, mathematics knowledge, and acceleration level, but varied with students absences and gender. We urge the CS education community to adopt our approach widely.

Enrollments in computer science courses and majors are at or exceeding capacity at the college level. This context drives local innovations that may benefit individuals across the SIGCSE community. The panelists will share how, in the context of booming enrollments and COVID, they strive to protect faculty time, engage students in larger classes, take advantage of scale, improve student-TA interactions, motivate faculty to teach larger classes, and better monitor students in large classes. During the panel Q&A, attendees will be invited to share additional strategies live on Course.Care, which will then be disseminated through CSTeachingTips.org.

Current computing education efforts do an excellent job of designing engaging curricula for middle school students through block-based platforms and multimedia project-based content. However, the programming concepts covered are notably and understandably simpler than those covered in college-level AP CS or CS1. In this paper, we present a new position that today's college-level CS1 curricula can and should be taught to middle school and early high school students. We discuss our efforts in teaching Python programming to this age group by adapting the pedagogical techniques of the CS1 course offered at a public university. Preliminary observations from an 8-week summer pilot study involving 7th - 10th grade students suggest that these students can learn CS1 concepts in depth when memory diagrams, extensive practice, and engaging reviews are relied upon.

This poster investigated the data from the past year of CS1 and found overwhelming evidence that students who have taken calculus are significantly more likely to succeed and less likely to fail that those who do not. On a Fall 2016 CS1 final exam, students who had not earned credit for a first course in college-level calculus were 2.8 times more likely to fail it than those who had (p=<0.0001,N=844). The mean final score for students with calculus was an 84, and those without was 61 (p=<0.0001). The result surprised the instructor, course staff, and faculty familiar with the course because the course itself does not emphasize mathematical or scientific computing. The course was Java-based, objects-early, and introduces both object-oriented and imperative programming fundamentals. The effect was evident across a range of problems, none seemingly requiring beyond basic algebra. In the Spring of 2017, the instructor and course staff set forth to explore these questions and close the math gap discovered in the Fall of 2016. This poster further proposes to develop interventions to aid those with a lower math maturity level through introducing a specialized CS1 to better accommodate those with a lower math maturity level by reducing the pace and installing prerequisites for the established CS1. Prospective Computer Science students at liberal arts colleges and universities enter with a wide range of mathematical backgrounds. Failing to acknowledge these disparities is demoralizing to students during their first course in CS and is counter-productive to inclusivity.