TY - GEN
T1 - Students' verbalized metacognition during computerized learning
AU - Bosch, Nigel
AU - Zhang, Yingbin
AU - Paquette, Luc
AU - Baker, Ryan S.
AU - Ocumpaugh, Jaclyn
AU - Biswas, Gautam
N1 - Funding Information:
This research was supported by the National Science Foundation (NSF) Award #1561676.
Publisher Copyright:
© 2021 ACM.
PY - 2021/5/6
Y1 - 2021/5/6
N2 - 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.
AB - 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.
KW - Afect
KW - Confusion
KW - Metacognition
KW - Self-regulated learning
UR - http://www.scopus.com/inward/record.url?scp=85106749284&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85106749284&partnerID=8YFLogxK
U2 - 10.1145/3411764.3445809
DO - 10.1145/3411764.3445809
M3 - Conference contribution
AN - SCOPUS:85106749284
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2021 - Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2021 CHI Conference on Human Factors in Computing Systems: Making Waves, Combining Strengths, CHI 2021
Y2 - 8 May 2021 through 13 May 2021
ER -