Purpose
Rapid Automatized Naming (RAN) tasks are widely used to assess processing speed and automaticity, both of which are crucial for fluent reading and academic achievement. However, university students with learning disabilities (LD) often experience difficulties in these tasks, particularly under increased cognitive demands. To better understand the underlying visual and cognitive processes, this study investigated the RAN performance of 15 university students with and without LD using eye-tracking technology as a fine-grained method of analysis.
Materials and Methods
Participants completed one RAN task involving numbers, and one Alternating Stimuli RAN task involving letters and numbers. Eye movement data were assessed using multiple metrics, including total gaze duration, fixation count, first fixation duration, and average fixation duration.
Results
The analyses revealed that students with LD showed significantly longer gaze times and more frequent fixations across all task conditions, reflecting lower automaticity and higher cognitive load. These differences were especially marked in the alternating condition, which requires greater attentional control and cognitive flexibility.
Conclusions
Our findings contribute to a deeper understanding of the attentional and processing challenges faced by students with LD and highlight the value of eye-tracking for identifying subtle processing differences that traditional assessments may overlook. Implications for early identification, intervention design, and future research are discussed.
IMPLICATIONS FOR REHABILITATION
The present study’s findings carry significant implications for the rehabilitation of individuals with Learning Disabilities (LD), particularly those with dyslexia and dyscalculia. The consistent observation of prolonged Time Spent Gaze (TSG), First Fixation Duration (FFD), and Average Fixation Duration (AveFD) among LD participants indicates persistent inefficiencies in automatic symbol recognition, attentional allocation, and cognitive flexibility. These insights, derived from fine-grained eye-tracking metrics, suggest that rehabilitation approaches must address both domain-specific and domain-general cognitive processes.
First, the observed deficits in automaticity and visual-verbal integration support the implementation of rehabilitation programs that emphasise automatisation of symbol retrieval. For individuals with dyslexia, this may include repeated exposure to grapheme-phoneme correspondences, guided oral reading, and structured naming drills using high-frequency letter sequences. For individuals with dyscalculia, targeted interventions should focus on rapid number naming and symbol-magnitude mapping, employing methods such as flashcard-based retrieval practice, visual quantity-symbol association tasks, and structured numerical fluency exercises.
Second, the pronounced challenges observed in alternating RAN tasks highlight the need to address cognitive flexibility and attentional control. Rehabilitation efforts should incorporate components that train executive functions, particularly in areas such as task switching, inhibition, and working memory. Activities such as rapid alternating categorisation, card-sorting tasks, or computerised set-shifting games may be beneficial in enhancing these skills and reducing cognitive load during complex symbol processing.
Third, the gaze behaviour of LD participants suggests impaired visual scanning and parafoveal processing efficiency. To address this, rehabilitation protocols could integrate visual attention training, such as controlled eye movement exercises, visual search tasks, and gaze-contingent digital tools. These approaches aim to optimise fixation patterns and reduce regressions, thereby improving the fluency of visual-symbol recognition.
Finally, the persistent nature of these deficits in a high-functioning university population underscores the importance of sustained, long-term rehabilitation, even beyond primary or secondary education. Rehabilitation should be individualised and adaptive, incorporating real-time feedback (e.g. through eye-tracking or digital monitoring tools) to refine intervention strategies. Additionally, embedding these techniques within academic contexts can promote generalisation to real-world reading and mathematical tasks, enhancing academic independence and self-efficacy.
In summary, the integration of eye-tracking data into the rehabilitation framework provides a promising avenue for tailoring interventions to the specific visual-cognitive profiles of individuals with LD. Interventions that combine automatisation training, executive function enhancement, and visual attention development are likely to yield the most meaningful improvements in functional literacy and numeracy.
