Predictors of academic achievement in distance learning for nursing students

Abstract

Background: Distance learning (DL) is no longer simply an alternative method in the new educational environment induced by COVID-19. The ability of learners to control the learning process is becoming an essential prerequisite for DL because learners are physically separated from their instructors. Therefore, it is necessary to understand the factors influencing DL and investigate the appropriate learning strategy.

Objectives: This study aimed to identify the relationships between academic achievement and the factors influencing DL.

Design: This study adopted a cross-sectional design.

Setting: This study was conducted in nursing colleges in Korea.

Participants: Two hundred and one undergraduate nursing students in Korea participated in this study.

Methods: An online survey of academic achievement, self-regulated learning (SRL), learning flow, engagement, academic stress, and grade point average was conducted using Google Surveys on December 22 and 23, 2020 at four nursing colleges. A hierarchical multiple linear regression model was conducted to identify the predictors of academic achievement. Age and sex were included in the regression model in the first step. Then, learning flow and engagement were included in the second step, and SRL was included in the final step.

Results: Learning flow (β = 0.37, p < .001), engagement (β = 0.23, p = .001), and SRL (β = 0.22 p = .003) explained 49.5% of the variance in academic achievement (Adj R² = 0.50, F = 40.21, p < .001). After controlling for sex, age, flow state, and engagement in learning, SRL explained an additional 2% of the variance in academic achievement (R² change = 0.02, p = .003).

Conclusions: The development of learning strategies, including SRL ability, learning flow and engagement in DL, contributes not only to students achieving high academic competency but also to educating students about perceptions of their 'future possible self'.

Keywords: Academic stress; Distance learning; Engagement; Learning flow; Self-regulated learning.