## 3 Materials and Research Design  
### Participants  
The study involved 24 postgraduate students enrolled in translation studies programs at various UK universities. All participants were native speakers of Chinese (L1) and used English as their second language (L2), with IELTS scores of 7.0 or above, ensuring a consistent level of English proficiency. They reported prior experience with computer-assisted translation tools and had previously taken part in experiments utilizing eye-tracking, keystroke logging, and cue-based Retrospective Think-Aloud Protocols (RTA), which contributed to the smooth implementation of the current research.  
The decision to recruit only native Chinese speakers was based on our research focus: examining cognitive effort allocation in different translation directions (L1 \(\rightarrow\) L2 and L2 \(\rightarrow\) L1) among novice translators with a shared linguistic background. This design helps reduce variability stemming from differences in language proficiency, translation training, or linguistic typology. Including a mixed population of native English and native Chinese translators could introduce confounding factors, potentially obscuring the results. While we acknowledge that a cross-linguistic comparison between native English and native Chinese translators would provide additional insights, such an approach falls beyond the scope of this study and is highlighted as a future research direction.  
Although the sample size of 24 participants may appear limited, our study adopts a within-subject design, where each participant performed multiple translation tasks. This approach resulted in a substantial dataset of eye-tracking and keystroke-logging records and enhanced statistical power by allowing for direct comparison across conditions within the same individuals, thereby reducing the variability that can arise in a between-subject design.  
To ensure the adequacy of our sample size, we conducted a post hoc power analysis using G*Power 3.1.9.7 (statistical power analysis to compute effect sizes), based on effect sizes observed in previous eye-tracking studies on cognitive translation processing (e.g., [1,12]). The analysis focused on detecting differences in Total Attentional Duration (TA duration), AU count, AU duration, and pupil dilation across translation directions. The power analysis yielded the following results:  
Effect size ([PERSON]'s \(\hat{F}\)) = 0.35 (large effect, based on prior research estimates);  
Alpha level = 0.05;  
Power (1\(-\beta\)) = 0.85;  
Required minimum sample = 19 participants (for within-subject comparisons).  
Since our sample size (N = 24) exceeds the minimum required for detecting statistically significant effects at a power level of 0.85, we are confident that our dataset is sufficient for drawing meaningful conclusions.  
Prior to participation, all individuals provided informed consent, in accordance with established ethical research guidelines. Data from twenty-one participants met the inclusion criteria for analysis. These criteria were based on established benchmarks and included (1) the total gaze duration on the screen, (2) the proportion of gaze samples successfully classified as fixations, and (3) the average fixation duration. We followed the standards proposed by [PERSON] [43] and [PERSON] [12].