DIGITAL DISTRACTION AND CODING EFFICIENCY: DOES MULTITASKING REDUCE PROGRAMMING ACCURACY IN ONLINE LAB ENVIRONMENTS?

DOI: https://doie.org/10.65985/APER.2026419205

Authors:

Ms. Meenu Verma

Keywords:

Digital multitasking; Coding accuracy; Cognitive load theory; Self-regulated learning; Online programming laboratories; Learning analytics; Task switching; Programming performance; Educational technology; Moderated mediation

Abstract:

This study examines whether digital multitasking during online programming labs reduces coding accuracy and investigates the cognitive mechanism through which this effect occurs. It further tests whether self-regulated learning moderates this relationship. Using a dataset of 312 undergraduate computer science students enrolled in online lab-based programming courses, we combine behavioral log data (tab-switching frequency, background app usage, IDE activity) with survey-based measures of perceived cognitive load and self regulated learning. Coding accuracy is operationalized as error density per 100 lines of code. Hierarchical regression and moderated mediation analyses are employed. Digital multitasking is significantly associated with higher error density (β = 0.28, p < 0.001). Cognitive load partially mediates this relationship (indirect effect = 0.09, 95% CI [0.05, 0.15]). Self-regulated learning moderates the direct effect (β = −0.17, p = 0.012), such that the negative impact of multitasking weakens for students with stronger regulatory strategies. Model R² values range from 0.18 to 0.34, indicating moderate explanatory power. Rather than merely documenting performance decline, this study identifies cognitive load as the explanatory mechanism and self-regulated learning as a protective boundary condition. It contributes to educational technology and cognitive computing literature by integrating behavioral analytics with cognitive theory in authentic online lab environments.

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