Analyzing Fine-Grained Skill Development across Computer Science Course ProgressionsGlobal
Although ample research has focused on computing skill development over a single course or specific programming language, relatively little attention is paid to how computing skills evolve across a program. Our work aims to understand how specific skills develop throughout a progression of CS courses. We use qualitative content analysis to catalog common errors in assignment submissions from four computing courses forming a prerequisite chain: CS1, CS2, Systems Programming (SP), and Operating Systems (OS). We focus on three fine-grained skills encountered in some form in all four courses: (S1) opening and reading data from a file, (S2) storing or organizing data in data structures, and (S3) using the data to implement a solution for a well-defined task. We study how the commonly observed errors or issues evolve across the prerequisite chain, thus analyzing how these skills develop. We notice successful development in most skills, evidenced by a reduction of common errors over the course progression. However, we also notice variability in skill development corresponding to the expected challenges, in working with new techniques (OOP), new languages (C), or concepts (binary files). We also observe an overall lower prevalence of common errors in CS1 and CS2 among students who progress to SP and OS in close succession. We believe that analyzing the evolution of common errors across course progressions would enable educators to gain insight into skills development and if certain outcomes are met more seamlessly than others.
Sat 21 FebDisplayed time zone: Central Time (US & Canada) change
10:40 - 12:00 | |||
10:40 26mTalk | An Empirical Evaluation of Active Live Coding in CS1 Journal First Anshul Shah University of California, San Diego, Thomas Rexin University of California, San Diego, Fatimah Alhumrani University of California, San Diego, William Griswold UC San Diego, Leo Porter University of California San Diego, Adalbert Gerald Soosai Raj University of California, San Diego DOI | ||
11:06 26mTalk | Analyzing Fine-Grained Skill Development across Computer Science Course ProgressionsGlobal Journal First Bogdan Simion University of Toronto Mississauga, Lisa Zhang University of Toronto Mississauga, Giang Bui University of Toronto Mississauga, Robin Huang University of Toronto, Ramzi Abu-Zeineh , Shrey Vakil University of Toronto DOI | ||
11:33 26mTalk | Teaching Algorithm Design: A Literature Review Journal First Jonathan Liu University of Chicago, Seth Poulsen Utah State University, Erica Goodwin University of Chicago, Hongxuan Chen University of Illinois at Urbana-Champaign, Grace Williams University of Chicago, Yael Gertner University of Illinois Urbana-Champaign, Diana Franklin University of Chicago DOI | ||