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Grit and learning: Understanding the sequential learning behaviours in snap!

Authors :
Gao, Ming
Zhang, Jingjing
Lu, Yu
Kahn, Ken
Winters, Niall
Source :
Journal of Computer Assisted Learning; Apr2023, Vol. 39 Issue 2, p603-616, 14p
Publication Year :
2023

Abstract

Background: As a non‐cognitive trait, grit plays an important role in human learning. Although students higher in grit are more likely to perform well on tests, how they learn in the process has been underexamined. Objectives: This study attempted to explore how students with different levels of grit behave and learn in an exploratory learning environment. Methods: In this study, 66 students participated in seven exploratory tasks in Snap! for approximately 60 min after a 30‐min lecture. Students were categorized into a high grit group and low grit group using a grit scale. The Mann–Whitney U test, epistemic network analysis and lag sequential analysis were used to explore the differences between groups in learning performance, technology acceptance and behavioural patterns. Results: Students with different levels of grit engaged in explorative tasks in a short period of time might not present significantly different learning performance, perceptions of usefulness and ease of use, but students higher in grit, actively engaging more different types of activities, tended to put greater sustained effort to solve the challenging task. Take Away: Although grit was not significantly correlated with learning performance when students engage in classroom‐based explorative activities, grit did predict whether students are more likely to explore and put greater sustained effort into solving the challenging task. Lay Description: Students higher in grit are likely to be actively engaging more different types of activities.Students higher in grit tend to put greater sustained effort to solve the challenging task.Grit was not significantly correlated with learning performance in classroom‐based explorative activities. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02664909
Volume :
39
Issue :
2
Database :
Complementary Index
Journal :
Journal of Computer Assisted Learning
Publication Type :
Academic Journal
Accession number :
162203188
Full Text :
https://doi.org/10.1111/jcal.12766