@inproceedings{bd11da45c25940b3ac9201be555d55e0,
title = "Blinded by science?: Exploring affective meaning in students{\textquoteright} own words",
abstract = "This work addresses students{\textquoteright} open responses on causal attributions of their self-reported affective states. We use qualitative thematic data analysis techniques to develop a coding scheme by identifying common themes in students{\textquoteright} self-reported attributions. We then applied this scheme to a larger set of student reports. Analysis shows that students{\textquoteright} reasons for reporting a certain affect do not always align with researchers{\textquoteright} expectations. In particular, we discovered that a sizable group of students externalize their affect, attributing perceived difficulty of the problem and their own negativity as lying outside of themselves.",
author = "Schultz, {Sarah E.} and Naomi Wixon and Danielle Allessio and Kasia Muldner and Winslow Burleson and Beverly Woolf and Ivon Arroyo",
note = "Funding Information: This research was funded by the National Science Foundation, #1324385 Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 13th International Conference on Intelligent Tutoring Systems, ITS 2016 ; Conference date: 07-06-2016 Through 10-06-2016",
year = "2016",
doi = "10.1007/978-3-319-39583-8_35",
language = "English (US)",
isbn = "9783319395821",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "314--319",
editor = "John Stamper and Alessandro Micarelli and Kitty Panourgia",
booktitle = "Intelligent Tutoring Systems - 13th International Conference, ITS 2016, Proceedings",
}