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Background:
In the 1960’s, a significant number of health care institutions began using automated information systems to manage administrative data. Some common examples include billing, admission, transfer and discharge of patients. As these systems became established, health care administrators discovered new and valuable uses for these data. After a significant delay, automated systems moved into the clinical arena, and once again clinicians recognized the value of that health care data. Evidence based practice and data based decision making would not be possible without these systems.
Higher education is following this same evolutionary pattern. Today many institutions of higher education are purchasing and/or designing sophisticated education information systems to manage operations. Examples include automated systems to manage the application, admission, and registration process; grants management; student records; and classroom scheduling. Faculty also manage large amounts of data related to individual students, the curriculum, educational programs, program evaluation, and the teaching learning process. However, few automated systems have been created to assist them in the management of their data. Just as evidence based practice required automated clinical systems, data-based decision making in education will be enhanced by an automated approach to management of data related to the teaching-leaning process. Just as effective systems in the clinical setting required input from health care providers, effective systems that support the teaching learning process in nursing will require input from nurse educators. But first, faculty will need to visualize these types of systems and the advantages they offer. They then can take the lead in the design and development of these new systems.
Purpose of the Task Group:
The purposes of this task group are to help faculty and administrators in nursing education appreciate the value of automated systems to support their work, and to work with companies to design and develop those applications.
Specific Tasks to be Completed:
- Conduct an extensive review of published and fugitive literature, and seek information via mailing lists and other informal venues to identify institutions and vendors who are creating and using automated systems to manage data related to the teaching-learning process. Add this information to the NLN data repository.
- Survey higher education information system vendors to determine if any of the vendors are developing, or considering the development of applications that support the management of data related to the teaching learning process (e.g., assess the learning needs of a population of students, track concepts in the curriculum).
- Using data from tasks 1 and 2 prepare a manuscript for publication describing the current state of automation in education and future directions.
- Using data from task 1 and 2 to identify vendors who could be approached to fund a multi-site study to identify the data management needs related to the teaching/learning process and test applications that address those needs.
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