Parsons Problems and Beyond

2022 · 50 citations

• Computer Science
• Computer Science
• Artificial Intelligence

Programming is a complex task that requires the development of many skills including knowledge of syntax, problem decomposition, algorithm development, and debugging. Code-writing activities are commonly used to help students develop these skills, but the difficulty of writing code from a blank page can overwhelm many novices. Parsons problems offer a simpler alternative to writing code by providing scrambled code blocks that must be placed in the correct order to solve a problem. In the 16 years since their introduction to the computing education community, an expansive body of literature has emerged that documents a range of tools, novel problem variations and makes numerous claims of benefits to learners. In this work, we track the origins of Parsons problems, outline their defining characteristics, and conduct a comprehensive review of the literature to document the evidence of benefits to learners and to identify gaps that require exploration. To facilitate future work, we design empirical studies and develop associated resources that are ready for deployment at a large scale. Collectively, this review and the provided experimental resources will serve as a focal point for researchers interested in advancing our understanding of Parsons problems and their benefits to learners.

Avoiding the Turing Tarpit: Learning Conversational Programming by Starting from Code’s Purpose

2021 · 43 citations

• Computer Science
• Computer Science
• Artificial Intelligence

Conversational programmers want to learn about code primarily to communicate with technical co-workers, not to develop software. However, existing instructional materials don’t meet the needs of conversational programmers because they prioritize syntax and semantics over concepts and applications. This mismatch results in feelings of failure and low self-efficacy. To motivate conversational programmers, we propose purpose-first programming, a new approach that focuses on learning a handful of domain-specific code patterns and assembling them to create authentic and useful programs. We report on the development of a purpose-first programming prototype that teaches five patterns in the domain of web scraping. We show that learning with purpose-first programming is motivating for conversational programmers because it engenders a feeling of success and aligns with these learners’ goals. Purpose-first programming learning enabled novice conversational programmers to complete scaffolded code writing, debugging, and explaining activities after only 30 minutes of instruction.