@inproceedings{fa8cfdbc74ed4dc8bedf423b3eb8cc21,
title = "Students' verbalized metacognition during computerized learning",
abstract = "Students in computerized learning environments often direct their own learning processes, which requires metacognitive awareness of what should be learned next. We investigated a novel method of measuring verbalized metacognition by applying natural language processing (NLP) to transcripts of interviews conducted in a classroom with 99 middle school students who were using a computerized learning environment. We iteratively adapted the NLP method for the linguistic characteristics of these interviews, then applied it to study three research questions regarding the relationships between verbalized metacognition and measures of 1) learning, 2) confusion, and 3) metacognitive problem-solving strategies. Verbalized metacognition was not directly related to learning, but was related to confusion and metacognitive problem-solving strategies. Results also suggested that interviews themselves may improve learning by encouraging metacognition. We discuss implications for designing computerized environments that support self-regulated learning through metacognition.",
keywords = "Afect, Confusion, Metacognition, Self-regulated learning",
author = "Nigel Bosch and Yingbin Zhang and Luc Paquette and Baker, {Ryan S.} and Jaclyn Ocumpaugh and Gautam Biswas",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021 ; Conference date: 08-05-2021 Through 13-05-2021",
year = "2021",
month = may,
day = "6",
doi = "10.1145/3411764.3445809",
language = "English (US)",
series = "Conference on Human Factors in Computing Systems - Proceedings",
publisher = "Association for Computing Machinery",
booktitle = "CHI 2021 - Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems",
address = "United States",
}