A Mixed-Methods Study of Novice Programmer Interaction with Python Error Messages
The ability to interpret error messages in order to find and fix bugs is an essential skill for novice programmers. Unfortunately, the technical language of most error messages can hinder the progress of CS1 students and can lead to feelings of confusion and frustration. A potential intervention for CS educators is the use of enhanced error messages that utilise natural-language geared towards novice learners, but the current discourse in CS Education regarding benefits of such messages is inconclusive. In this paper, we describe a planned, semi-controlled experiment running parallel to a CS1 course at the University of Toronto Scarborough. The study aims to build upon existing work in quantifying the effects of enhanced error messages by incorporating additional quantitative metrics, usability surveys, student feedback, and semi-structured interviews. The additional methods serve to measure not only the effects on error recovery, but student satisfaction, sense of frustration and overall attitude towards error messages and debugging.
Error Message Readability and Novice Debugging Performance
It is well known that programming error messages can be notoriously difficult for novices to understand, hampering progress and leading to frustration. In response, researchers have explored various approaches for enhancing such messages, yet results from this active strand of research are currently mixed. Direct comparisons of results between studies is challenging as these typically investigate different kinds of message enhancements and report results using different metrics. In addition, many prior studies have involved code writing tasks. In such cases, not all students encounter the same errors and messages, and it is difficult to isolate the time spent interpreting messages and resolving errors from the time spent writing code. In this research, we explore the effects of presenting novices with compiler error messages designed using the most recent collection of published guidelines - specifically, more easily readable, short, positive messages containing resolution hints. To accurately determine the time and effort required to read and respond to the messages, we utilise a debugging task where all students are presented the same code and therefore encounter the same errors. We present results of a randomised controlled experiment (n > 700) which shows that, compared to standard error messages, the messages we tested resulted in significantly shorter debugging times and higher self-reported scores of message usefulness for students in the very early stages of learning a new language.
Programming, Problem Solving, and Self-Awareness: Effects of Explicit Guidance
More people are learning to code than ever, but most learning opportunities do not explicitly teach the problem solving skills necessary to succeed at open-ended programming problems. In this paper, we present a new approach to impart these skills, consisting of: 1) explicit instruction on programming problem solving, which frames coding as a process of translating mental representations of problems and solutions into source code, 2) a method of visualizing and monitoring progression through six problem solving stages, 3) explicit, on-demand prompts for learners to reflect on their strategies when seeking help from instructors, and 4) context-sensitive help embedded in a code editor that reinforces the problem solving instruction. We experimentally evaluated the effects of our intervention across two 2-week web development summer camps with 48 high school students, finding that the intervention increased productivity, independence, programming self-efficacy, metacognitive awareness, and growth mindset. We discuss the implications of these results on learning technologies and classroom instruction.