The study, conducted across five nursing colleges in Jordan, surveyed 537 undergraduate nursing students about their experiences with online and blended learning. The researchers, guided by Cognitive Load Theory, set out to measure two intertwined phenomena: digital fatigue, the physical, cognitive, and psychological exhaustion associated with screens and virtual classrooms that is popularly known as “Zoom fatigue,” and cognitive load, the mental effort required to process, organize, and retain information during learning. What they found was a student population operating near the limits of its mental bandwidth.

The participants, drawn from the University of Jordan, Yarmouk University, Al-Zaytoonah University of Jordan, Zarqa University, and Applied Science Private University, had a mean age of just under 21 years, and slightly more than half were women. All were required to have taken at least one online course within the previous six months, and students taking medications that could affect concentration were excluded. Data were collected between March and April 2025 through an internet-based questionnaire distributed via institutional learning platforms and student email accounts, and the study was reported according to the STROBE guidelines for observational research.

To measure digital fatigue, the team used the 15-item Zoom Exhaustion and Fatigue Scale, which assesses five dimensions of exhaustion: general, social, emotional, visual, and motivational. Cognitive load was assessed with the Cognitive Load Scale developed by Leppink and colleagues, which distinguishes three components identified by Cognitive Load Theory: intrinsic load, the inherent complexity of the material itself; extrinsic load, unnecessary mental effort imposed by the way information is presented; and germane load, the productive cognitive effort devoted to building understanding and long-term knowledge structures. Both instruments were translated into Arabic and validated for the Jordanian context through a rigorous cross-cultural adaptation process involving independent forward and backward translations, expert committee review, and pilot testing with 32 nursing students that confirmed strong reliability.

The results were sobering. Total digital fatigue scores, which can range from 15 to 75, had a median of 61, clustering toward the upper end of the scale and indicating that most students experienced moderate to high levels of exhaustion. Total cognitive load was similarly elevated, with a median of 56 on a scale reaching 100. But the most striking finding concerned the extrinsic load subscale. Although its scores could theoretically range from 7 to 30, the median and the 75th percentile both sat at exactly 30, the maximum possible value. In other words, at least half of the sample scored at the ceiling of the measure, a pattern the researchers interpreted as clear evidence that poorly structured instruction was imposing unnecessary mental effort on a large majority of students.

The statistical relationships between these variables tell a coherent story. Spearman’s correlation analysis revealed a significant positive correlation between total digital fatigue and total cognitive load, with a coefficient of 0.405, indicating a moderate association. Breaking the cognitive load construct into its components revealed that extrinsic load was the dimension most strongly correlated with fatigue, at 0.308, while intrinsic load showed a weaker positive association at 0.224. Germane load, by contrast, was negatively correlated with digital fatigue at −0.118, meaning that students whose mental effort was being channeled into meaningful learning reported less exhaustion. Taken together, the pattern suggests that when instructional design wastes cognitive resources, students burn through their limited mental capacity on navigational and presentational friction rather than on learning, and fatigue follows.

To identify the factors independently associated with extrinsic cognitive load, the researchers built a multiple linear regression model using bootstrap estimation with 5,000 resamples, a robust approach made necessary by the pronounced ceiling effect and non-normal distribution of the extrinsic load scores. The model, which included 15 predictors, was statistically significant and explained 30.7 percent of the variance in extrinsic load. Within it, digital fatigue remained a strong independent predictor after controlling for demographic and academic characteristics, with an unstandardized coefficient of 0.342, meaning that every additional point of fatigue was associated with a measurable increase in unnecessary cognitive burden.

Several demographic and institutional patterns also emerged. Students attending governmental universities reported significantly lower extrinsic cognitive load than those at private universities, a difference that only became apparent after statistical adjustment and which the authors suggest may reflect differences in instructional organization, curriculum delivery, or digital learning implementation across institutions. Third-year students reported lower extrinsic load than fourth-year students, possibly because nursing students in their final year face increasing academic and clinical complexity, frequent transitions between classrooms and clinical placements, and fragmented integration across learning environments. Students who used digital devices for four to six hours per day reported lower extrinsic load than heavy users exceeding six hours daily, consistent with prior evidence that prolonged screen exposure inflates mental effort and attentional demands. Notably, perceived internet quality showed no significant relationship with extrinsic load, a finding the authors interpret as evidence that curriculum design and information organization matter more than technical access alone, a departure from the long-standing assumption that connectivity is the primary barrier to effective digital education.

The theoretical implications are significant. Cognitive Load Theory holds that working memory is a limited resource, and that learning fails when the demands placed on it exceed capacity. Intrinsic load cannot easily be reduced because it reflects the genuine complexity of the material, and in nursing education that complexity is considerable: students must integrate abstract biomedical concepts with clinically oriented reasoning and high-stakes decision-making. Germane load, meanwhile, is the desirable effort that builds expertise. Extrinsic load is different. It originates not from the content but from the design of instruction, which makes it the one component of cognitive burden that educators can actually modify. Complex digital interfaces, fragmented content delivery, excessive information presentation, and inefficient interaction requirements all dump unnecessary processing demands onto students, and the ceiling effect observed in this study suggests such demands are pervasive in Jordanian online nursing education.

The authors argue that their findings point to instructional design, rather than digital engagement itself, as the primary modifiable source of cognitive burden. If students are spending their finite cognitive resources on deciphering poorly organized platforms and switching between fragmented tasks, fewer resources remain for the deep, schema-building engagement that nursing education demands, and the result is both poorer learning and greater exhaustion. The inverse relationship between germane load and fatigue supports this reading: meaningful learning and fatigue appear to compete for the same cognitive budget.

The study carries practical implications for educators and institutions. Rather than focusing solely on how much technology students use, the researchers recommend that faculty redesign teaching materials to reduce unnecessary load, drawing on evidence-based strategies such as breaking learning into smaller segments, minimizing task switching, clarifying navigation, and scheduling time for students to process and recover from learning sessions. At the institutional level, they call for training and capacity-building programs to strengthen instructors’ digital pedagogy and instructional design skills, arguing that cognitively informed, student-centered course design can improve learning efficiency, reduce perceived fatigue, and sustain student engagement.

The authors are careful to acknowledge the limitations of their work. The ceiling effect in extrinsic load reduced response variability even with bootstrapping in place. The regression model left nearly 70 percent of the variance unexplained, pointing to unmeasured factors such as psychological stress, sleep quality, and academic workload. The cross-sectional design means the associations cannot establish causation; it is plausible, for instance, that fatigue drives poorer engagement with poorly designed courses rather than the reverse. Convenience sampling recruited students reachable through institutional platforms, potentially underrepresenting those less engaged with online systems, and the self-administered survey format may have attracted students with particularly strong opinions about digital learning. Self-reported measures of internet quality may also not reflect actual connectivity. The researchers call for future studies using probability-based sampling, longitudinal designs, and objective measures of digital learning conditions.

Even with those caveats, the study offers a rare data point from a developing educational context, where most existing evidence on digital fatigue comes from well-resourced systems in other regions. The message for educators everywhere is uncomfortable but actionable: the problem may not be screens themselves, but what educators put on them. As online and blended learning become permanent fixtures of higher education, the cognitive cost of careless design is no longer hypothetical. It is measurable, it is high, and, unlike the intrinsic difficulty of nursing itself, it is entirely fixable.