An Algorithm for Curriculum Decisions in Medical Laboratory Science Education

Abstract

Advances in medical science occur at a dramatic rate, leading to new knowledge and technology that changes clinical laboratory practice. To prepare students for entry level practice and careers in the clinical laboratory profession, MLT and MLS educators need to continually review their curricula to decide what should be added or deleted. Decisions about deleting content are difficult but important in order to avoid curriculum saturation and to facilitate learning. This article presents a rationale for deleting some content and an algorithm that can guide decisions about what to teach and what not to teach. Curriculum Decisions in Medical Laboratory Science Education Faculty members in medical laboratory educational programs are uniquely qualified to make decisions about what to include in a Medical Laboratory Science (MLS) or Medical Laboratory Technician (MLT) curriculum because of their professional education, credentials, and clinical experience. Most faculty members would agree that the decisions about what to include in the curriculum are not as difficult as the decisions about what not to teach. New information, new laboratory tests, and new protocols are constantly added to the laboratory profession. Adding new content to the curriculum is inevitable, but without simultaneously removing some of the older content, the MLS or MLT curriculum becomes unmanageable. This article presents an argument for deleting content from the MLS or MLT curriculum and an algorithm for making decisions about what to teach and what not to teach. The rationale for the algorithm, the algorithm, and the examples provided in this article are based on the experience and views of the authors. The authors welcome suggestions for improvement and additional examples. The need to delete content from the curriculum. Before discussing curriculum decisions in medical laboratory educational programs, it is helpful to first consider how students learn. No one theory of learning is adequate to explain the complexity of the human brain; however, the information processing theory or cognitive theory of learning provides a useful tool for discussing how we receive information and retain it for future use. A simplified version of the theory is shown in Figure 1. The information processing theory postulates that we have three types of memory; sensory memory, working memory, and long term memory. Sensory memory pro