Investigating the Utility of Self-explanation Through Translation Activities with a Code-Tracing Tutor

Abstract

Code tracing is a foundational programming skill that involves simulating a program’s execution line by line, tracking how variables change at each step. To code trace, students need to understand what a given program line means, which can be accomplished by translating it into plain English. Translation can be characterized as a form of self-explanation, a general learning mechanism that involves making inferences beyond the instructional materials. Our work investigates if this form of self-explanation improves learning from a code-tracing tutor we created using the CTAT framework. We created two versions of the tutor. In the experimental version, students were asked to translate lines of code while solving code-tracing problems. In the control condition students were only asked to code trace without translating. The two tutor versions were compared using a between-subjects study (N = 44). The experimental group performed significantly better on translation and code-generation questions, but the control group performed significantly better on code-tracing questions. We discuss the implications of this finding for the design of tutors providing code-tracing support.