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  • Assistant Director for Academic Program Development and SCHEV Liaison
    INSTITUTIONAL ASSESSMENT
    Old Dominion University

    Job Summary


    The Assistant Director for Academic Program Development and SCHEV Liaison manages activities related to new program development and organizational changes by monitoring academic-related proposals from beginning to end in collaboration with SCHEV and ODU representatives. Assists the Vice Provost for Academic Affairs by crafting, reviewing, and submitting new program and organizational changes proposals, monitoring ODU compliance with state policies and procedures; overseeing data collection related to SCHEV proposals to include surveys and focus groups with students; and supporting faculty and staff with new program and organizational changes proposals activities.

     

    Master’s degree in social science, technical writing, education, business or related area.


    • Effective communication, leadership and collaboration skills; working experience with faculty members.

    • Attention to detail; professionalism while working with others.

    • Considerable skills with word processing, spreadsheets, and presentation software applications.

    • Considerable technical writing skills.

    • Some experience providing data support to a variety of audiences.

    • Some experience managing data and generating reports.

    • Considerable experience managing Microsoft desktop applications (e.g. Excel, MS Access, Word, PowerPoint).

    • Some ability to collaborate and work as a member of a team to reach common goals.

    • Considerable ability to write reports for external agencies.


    Preferred Qualifications



    • Some teaching or training skills preferred.

    • Working knowledge SCHEV policies and procedures preferred.

    • Working knowledge of applied research design and statistics preferred.

    • Working in an academic context with faculty and administrators preferred.

    • Some experience managing data with statistical packages/programming languages (e.g., SAS, SPSS) preferred.


 


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