Capturing Admission Judgment Policy from the Lens Model Perspective to Understand the Gender Difference in Science and Engineering

Despite the government promoting women's participation in the engineering field, some statistics show that it has yet to be achieved. Potential reasons for this phenomenon include lower level of applications by women, or inherent gender gap in the professional field. Therefore, this study attempted to find impact of gender on college admission from the Lens Model perspective and Signal Detection Theory. This study consisted of three phases: identifying the necessary cues used in the admission process, analyzing existing data, and conducting two experiments to identify the effect of gender on admission decisions. Although the college application consisted of many cues, only five cues, school ranking, GPA, SAT score, resident status, and gender, were used to capture the officers' judgment policies for engineering admissions. Two experiments were conducted to investigate the impact of the gender factor in college admission. The enrollment officers first were presented with the existing data without the gender and asked to make dichotomous judgments. Secondly, the officers were asked to perform the judgment task with the gender cue present. Results showed that the gender did not play an important role in the judgments as expected. However, ideographical analyses on judgment strategies revealed that there were significant differences between the admission officers. Possible training implications are discussed.