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How Are Students’ Emotions Associated with the Accuracy of Their Note Taking and Summarizing During Learning with ITSs?

  • Michelle TaubEmail author
  • Nicholas V. Mudrick
  • Ramkumar Rajendran
  • Yi Dong
  • Gautam Biswas
  • Roger Azevedo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10858)

Abstract

The goal of this study was to examine 38 undergraduate and graduate students’ note taking and summarizing, and the relationship between emotions, the accuracy of those notes and summaries, and proportional learning gain, during learning with MetaTutor, an ITS that fosters self-regulated learning while learning complex science topics. Results revealed that students expressed both positive (i.e., joy, surprise) and negative (i.e., confusion, frustration, anger, and contempt) emotions during note taking and summarizing, and that these emotions correlated with each other, as well as with proportional learning gain and accuracy of their notes and summaries. Specifically, contempt during note taking was positively correlated with proportional learning gain; note taking accuracy was negatively correlated with proportional learning gain; and confusion during summarizing was positively correlated with summary accuracy. These results reveal the importance of investigating specific self-regulated learning processes, such as taking notes or making summaries, with future research aimed at examining the differences and similarities between different cognitive and metacognitive processes and how they interact with different emotions similarly or differently during learning. Implications of these findings move us toward developing adaptive ITSs that foster self-regulated science learning, with specific scaffolding based on each individual student’s learning needs.

Keywords

Cognitive learning strategies Facial expressions of emotion Latent semantic analysis Process data Self-regulated learning 

Notes

Acknowledgements

This research was supported by funding from the National Science Foundation (DRL#1431552; DRL#1660878, DRL#1661202) and the Social Sciences and Humanities Research Council of Canada (SSHRC 895-2011-1006). The authors would like to thank the members from the SMART Lab at NCSU for their assistance with data collection.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Michelle Taub
    • 1
    Email author
  • Nicholas V. Mudrick
    • 1
  • Ramkumar Rajendran
    • 2
  • Yi Dong
    • 2
  • Gautam Biswas
    • 2
  • Roger Azevedo
    • 1
  1. 1.North Carolina State UniversityRaleighUSA
  2. 2.Vanderbilt UniversityNashvilleUSA

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