Graduate Assistant, Program Evaluation (IU CEWiT)

Graduate Assistant, Program Evaluation

IU Center of Excellence for Women in Technology


The IU Center of Excellence for Women in Technology (CEWIT) addresses the global need to increase participation of women at all stages of their involvement in technology-related fields through research collaborations, education, mentoring, and community building. The interdisciplinary, unified approach to this center serves as a national model to encourage, empower, and promote women in technology and computing-related fields at IU and across the region.

Essential Job Duties

  • Design and conduct needs assessments, literature reviews, and program evaluation reports to assist CEWIT staff in achieving desired program outcomes, identifying opportunities for improvement, and making informed decisions for effective management of CEWIT programs.
  • Monitor program effectiveness and integrity.
  • Provide technical assistance to CEWIT staff on planning and evaluation methods and the use and interpretation of data including affiliate demographics, program attendance, website and social media metrics, and survey responses.
  • Support the development of CEWIT’s annual and long-term strategic planning reports.
  • Participate in staff meetings, staff leadership trainings, and major events.

Required Skills

  • Comprehensive knowledge of program planning, logic modeling, and evaluation methodology.
  • Skilled in research and evaluation design, implementation, and management.
  • Comprehensive knowledge of quantitative methods, including sampling design, questionnaire construction and knowledge of appropriate application of descriptive and inferential statistical techniques; as well as qualitative methods, such as unstructured interviews, focus groups, and content analysis.
  • Excellent oral and written communication skills and experience developing written materials for various audiences.
  • Experience working with survey software such as SurveyMonkey or Qualtrics.

Desired Skills

  • Experience collecting and managing large datasets.
  • Experience using findings to develop recommendations in the decision-making process for programs, policies, and special projects.
  • Ability to present information, research findings, and data that range in difficulty from simple and concrete to highly complex and abstract.
  • Experience working with programming languages or statistical tools such as Python, SQL, R, SPSS, or SAS.

Position Type: Part-Time (18-20 hours/week)

Pay Rate: $20/hour (student health insurance coverage possible)

How to Apply: To apply for this position please send your interest letter, CV, and the names and contact information for three references to Maureen Biggers at

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