@inproceedings{ee8e93d4534347169685c57e56f4e09b,
title = "“I{\textquoteright}m not a computer”: How identity informs value and expectancy during a programming activity",
abstract = "Code tracing—simulating the way the computer executes a program—is a common teaching and assessment practice in introductory programming courses. In a laboratory experiment where code tracing was encouraged, we found that some struggling novice programmers described code tracing as not only cognitively complex, but also in opposition to their self-beliefs. One participant described himself as not a computer, and therefore unfit to execute code like the computer does. Another described himself as not a programmer, and did not value an activity that was only for learning about how code works. We mapped these learners{\textquoteright} self-narratives onto the Eccles Expectancy-Value Model of Achievement Choice to understand how identity relates to the choice to not trace code. While both participants valued what they could create with code, neither valued code tracing. Alternative activities might allow students with these identities to build skills in a way that aligns with their self-beliefs.",
keywords = "Code tracing, Expectancy-value theory, Motivation, Programming identity",
author = "Kathryn Cunningham and Bejarano, {Rahul Agrawal} and Mark Guzdial and Barbara Ericson",
note = "Publisher Copyright: {\textcopyright} ISLS.; 14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020 ; Conference date: 19-06-2020 Through 23-06-2020",
year = "2020",
language = "English (US)",
series = "Computer-Supported Collaborative Learning Conference, CSCL",
publisher = "International Society of the Learning Sciences (ISLS)",
pages = "705--708",
editor = "Melissa Gresalfi and Horn, {Ilana Seidel}",
booktitle = "14th International Conference of the Learning Sciences",
}