Conference Session

Gender Track - Technical Session III

Collection

2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference

Authors

Tim John Weston, University of Colorado, Boulder; Wendy DuBow, National Center for Women & IT; Alexis Kaminsky, Kaminsky Consulting, LLC

Tagged Topics

Diversity, Gender

Paper ID #242252018 CoNECD - The Collaborative Network for Engineering and ComputingDiversity Conference: Crystal City, Virginia Apr 29Women in Computing & Engineering: Differences between Persisters andNon-persistersTim John Weston, University of Colorado, Boulder Tim Weston is a research associate for the University of Colorado’s Alliance for Technology, Learning and Society (ATLAS) where he has conducted evaluation and research on NSF, Department of Educa- tion, NASA and private foundation funded projects for 19 years. Weston specializes in the evaluation of programs with educational technology interventions, assessing new

Conference Session

Gender Track - Technical Session I

Collection

2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference

Authors

Maya Rucks, Clemson University; Marisa K. Orr, Clemson University

Tagged Topics

Diversity, Gender

determines the levelof performance in the occupation.For this study, we view interest as the desire to learn more about engineering. At ClemsonUniversity, all students begin in the same general engineering class before they can declare theirmajors. We will call this the interest stage. Keep in mind, all the students in WISER aresophomores so many, if not all of them, will have already been through the interest stage. Afterthis stage, we have the intentions stage. At this point, students declare their majors with theintention of becoming engineers. The Activity, Selection, and Practice stage involves purposefulactions taken to become an engineer. This might include passing upper level engineering classes,joining professional engineering organizations

Conference Session

Gender Track - Technical Session I

Collection

2018 CoNECD - The Collaborative Network for Engineering and Computing Diversity Conference

Authors

Nicole Nieto, Ohio State University

Tagged Topics

Diversity, Gender

Computer and 16.3% in Computer Science(Outside Engineering). These numbers are some of the lowest in representation of womenamong all engineering disciplines. These low numbers negativity affect gender diversity in thetechnology sector. III. Examining InterventionsImplicit Bias In recent years, implicit bias has garnered more attention as a bias that negatively affectshiring processes and workplace climate. Characteristics of implicit bias include: one is unawareof bias, it is difficult to control, it is unintentional, there is no introspection, it is not endorsed andit is a habit of the mind. We all have implicit biases that are learned from culture andstereotypes. Implicit biases often conflict with our consciously endorsed beliefs. We