Director of Assessment Position - The College of Saint Rose

  • October 06, 2016 3:49 PM
    Message # 4294222


    Title: Director of Assessment

    Division: President’s Office

    Department: Office of Institutional Effectiveness

    Reports to: Associate Vice President for Institutional Effectiveness

    Hours: Full Time, 12 months

    Class: Exempt


    Job Summary: Provide coordination and assistance with curricular outcomes assessment and the use of assessment of student learning outcomes within the academic programs and liberal education curriculum.  Ensure assessment is in accordance with the accreditation requirements of the Middle States Commission on Higher Education and other organizations that accredit College programs.  Provide assessment support to Deans, Department Chairs, Faculty, Committees and Programs.


    1. Provide coordination to the process, procedures, and tools used to assess curricular outcomes.
    2. Consult with and assist Deans, Department Chairs, Faculty, Programs and Committees regarding the design and implementation of assessment activities, analysis and interpretation of data related to student learning outcomes, and the measures and tools used for assessment purposes.
    3. Interface with the Undergraduate Academic Committee, Graduate Academic Committee, and Liberal Educational Coordinating Committee for assessment activities and reporting.
    4. Provide support for assessment activities needed by specialized accrediting bodies (e.g., Accreditation Council for Business Schools and Programs, Council for the Accreditation of Educator Preparation, Council on Social Work Education, National Association of Schools of Art and Design, National Association of Schools of Music, and National Association of School Psychologists).
    5. Promote best practices for using assessment results to foster continuous improvement of academic quality.
    6. Utilize technologies to facilitate and strengthen assessment activities.
    7. Organize resource materials and professional development opportunities in order to improve the reliability and validity of assessment activities at the College.
    8. Collaborate with various other campus constituencies related to the analysis and use of assessment outcomes data.
    9. Support and facilitate communication with the Middle States Commission on Higher Education and other accrediting organizations.
    10. Work collaboratively with Institutional Research on co-curricular assessments.


    1. Master’s degree in educational assessment, measurement, social sciences or other related discipline required; Doctoral degree preferred.
    2. Minimum of two years of experience in educational research and assessment.
    3. Demonstrated experience with quantitative and qualitative methods in designing and conducting assessments of student learning outcomes in higher education.
    4. Familiarity with the accreditation requirements of the Middle States Commission on Higher Education and other accrediting organizations preferred.
    5. Intermediate level computer skills using a Windows based operating system, specifically MS Word, Excel and PowerPoint are required.
    6. Experience with assessment technologies preferred.
    7. Strong interpersonal skills and the ability to interact effectively with Deans, Department Chairs, Faculty and Administrators.
    8. Strong organizational, communication, and problem-solving skills.
    9. Manage an institutional calendar of assessment-related activities and reporting requirements.
  • May 31, 2017 1:00 PM
    Reply # 4863174 on 4294222

    I am a collaborative engineering professional with substantial experience designing and executing solutions for complex business problems involving large scale data warehousing, real-time analytics based on Natural Language Processing (NLP), and reporting solutions based on intuitive architecture that effectively analyze and process petabytes of structured and unstructured data. I have an extensive background in architecting and developing large-scale data processing systems and serving as a subject matter expert in data warehousing solutions while working with a variety of database, analytical, and statistical based technologies. This experience in architecting highly scalable, distributed systems using different open source and specific vendor tools as well as designing and optimizing large, multi-petabytes of clustered data warehouses were primarily in the clinical/ medical research, academia, computer integrated manufacturing, military battlefield self-awareness systems, aerospace, and financial/investment systems. Based on this experience I was able to integrate state-of-the-art Big Data technologies from IBM and Oracle into the overall architecture and lead a multi-team of Senior Data Scientists, Software Engineers, and Enterprise Architects through the design, development, engineering testing, and implementation phases. I have been working in industry and academia with Analytics and Artificial Intelligence in designing and constructing neural networks to be used as computational models in machine learning based on NLP and linguistics. These models were used as the basis to support the execution of statistical applications developed in R and SAS languages, and algorithms based on discreet and continuous mathematics and inter-operability with rule-based application languages. I have used NLP as a means to examine and analyze patterns of data, statistics, and related content relative to their behaviors predicated on metamorphosis processes as well as to the next level which is providing human intelligence with a secondary self-awareness that is technology generated and in support of the primary self-awareness which is human intelligence. In summary, this means that as data and related content changes due to interactions with applications, human interactions, and streams of research, the use of these NLP applications become self-aware of these new patterns through interpretative learning. Based on this self-awareness information is derived that allows actions and recommendations to be readily added to these patterns and the extension of these patterns across other patterns by predictive and inferential models. The net result is that what we learn on a day-to-day basis by interacting with data, statistics, and content is exponentially and organically increased but the relevancy from this is meaningful information that works for us, for example, the ability to give back to us the missing chemical component or surgical technique for DNA molecular cell structure breakdown in order to address a specific cause to autism, or increase business competitiveness in your specific marketplace by niche. The application of NLP was the missing link to the work completed in Analytics.

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