Introduction: This study investigated eye tracking technology for 12 lead electrocardiography interpretation to Healthcare Scientist students.Methods: Participants (n=33) interpreted ten 12 lead ECG recordings and randomised to receive objective individual appraisal on their efforts either by traditional didactic format or by eye tracker software.Results: 100% of participants reported the experience positively at improving their ECG interpretation competency. ECG analysis time ranged between 13.2 – 59.5secs. The rhythm strip was the most common lead studied and fixated on for the longest duration (mean 9.9secs). Lead I was studied for the shortest duration (mean 0.25secs). Feedback using eye tracking data during ECG interpretation did not produce any significant variation between the assessment marks of the study and the control groups (p=0.32). .Conclusions: Although the hypothesis of this study was rejected active teaching and early feedback practices are recommended within this discipline.