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

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.

Assessing Computational Thinking, Motivation, and Grit of Undergraduate Students Using Educational Robots

“…Consequently, there were notable differences in students’ socio-cognitive backgrounds, making it challenging to personalize any similar task. Nonetheless, previous research (Adanir et al, 2023; Gao et al, 2022; Gonzalez, 2023) has emphasized the substantial impact of interactive platforms on students’ performance, despite the relatively small sample size. Therefore, researchers must adapt and optimize instructional conditions to achieve more favorable outcomes.…”

“…In recent years, there has been significant attention given to the use of educational robotics in learning programming, as it has the potential to support students with diverse backgrounds. By conducting a review and synthesis of relevant literature, this study experimented to provide a comprehensive understanding of how educational robotics influences students' emotional experiences, as well as identify any relation of CT skills with motivation and grit (Gao et al, 2022; Kerimbayev et al, 2023; Mahatanankoon & Wolf, 2021). Nonetheless, recent literature shows that is often facilitated through tangible devices, and there is a lack of empirical research on educational robotics usage in contrast to digital effectiveness, as noted by previous studies (Coşkun & Filiz, 2023; Pellas & Vosinakis, 2018).…”

“…For example, Mahatanankoon and Wolf (2021) have admitted that programming grit and self-efficacy have low to moderate correlations with shallow and deep learning. More recently, Gao et al (2022) advocated that students with different levels of grit engaged in explorative tasks in a short period 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 tasks.…”