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This chapter presents application of multi-criteria mathematical programming models by integer and mixed-integer programming for optimal allocation of workers among supporting services in a hospital. The services include logistics, inventory management, financial management, operations management, medical analysis, etc. The optimality criteria of the problem are minimization of operational costs of supporting services subject to some specific constraints. The constraints represent specific conditions for resource allocation in a hospital. The overall problems are formulated as assignment models, where the decision variables represent the assignment of people to various jobs. Numerical examples are presented. Some computational results modeled on a real data from a hospital in Poland are reported.

Degree programs in Information Systems typically include a course on Systems Analysis and Design which is challenging to teach for instructors and challenging to grasp for learners. The central issue is that conditional knowledge, or when to use concepts and techniques in this domain, is seldom, if ever, taught. This chapter explains the ongoing evolution of a course on Systems Analysis and Design with the goal of developing conditional knowledge in students. It follows the process of changing course objectives, developing expert models of problem solving, experiencing challenges in delivering this kind of content, and reflecting on new insights that will improve course design in the future.

Our chapter addresses the balance assessment professionals must strike in supporting academic freedom, shared governance practices, and learning improvement efforts within colleges and universities in the United States. Specifically, we address how assessment professionals (faculty or staff whose primary job involves accreditation or the assessment of student learning) can encourage increased educational equity while supporting academic freedom. The authors offer a unique perspective. As former faculty members, current assessment practitioners, and a current academic administrator, we work to ensure that our institutions are using assessments of student learning to improve learning for all students. This work gives us insight into the ways in which assessment information shapes institutional efforts, balancing the rights of faculty to control the curriculum with the rights of historically underserved students (including students from underserved ethnic or racial groups, first generation college students, students from low-income households, and students with special needs or disabilities) to receive a quality education. We propose that one solution to this apparent conflict is to provide faculty with data that allow them to analyze the ways in which their assessment choices influence educational equity. To contextualize our work in this area we summarize institutional and faculty freedoms and discuss areas of conflict. We then describe ways to reduce areas of conflict by creating a culture of inquiry that centers around consideration of data and opportunities to modify assessments to increase educational equity.