Decision Support System to Help Assess Instructor’s Performance in SJIT

Making decisions involving complicated systems such as rational processes often stresses our intellectual abilities. In many circumstances, the quality of decisions is essential. Helping the deficiencies of a person’s intelligence and decision making has been a major focus of science during the course of history. That is why, today, different information systems are being developed to help the
end-users manage and control business processes to provide information that leads to better decision-making. More recently, variety of techniques originating from information science, cognitive psychology, and artificial intelligence have been implemented in the form of computer programs for complex decision making.

Druzdzel and Flynn (2002) introduce “Decision Support System” or referred to as an interactive computer-based system that aid users in judgment and choice activities. Decision Support Systems are gaining an increased popularity in various domains including business, engineering, and medicine. In fact, a talented community of computer scientists and healthcare professionals are researching about a research program for a new discipline called Artificial Intelligence in Medicine (AIM) which can assist clinicians with tasks like diagnosis. Moreover, Druzdzel and Flynn also added that Decision Support Systems can aid human cognitive deficiencies by integrating various sources on information, providing intelligent access to relevant knowledge, and aiding the process of structuring decisions.

In SJIT, performance evaluation is done every semester. The President evaluates the two vice presidents. The Vice-President for Academics and Research evaluates the deans. The Vice-President for Administrative and Students Services evaluates the heads of offices. The deans evaluate the faculty while the heads of offices evaluate the support staff. A conference follows after the evaluation for feedback and clarification purposes.

Faculties are evaluated regularly by the students. The said evaluation reviews the faculty’s quality of teaching, professional contribution, and personality / interpersonal skills. Before the end of the term or semester, the guidance counselors provide students with standardized evaluation form to evaluate their instructors. A faculty is evaluated 3 times by 3 different classes with 30% respondents from the total population per class. Then, the SPS coordinator computes the evaluation and gives the result to the dean from which he / she draw his final recommendation.

However, assessing the instructor’s performance is not a simple job. Firstly, manual computation of the evaluation forms takes time because each item in the appraisal form is computed before getting the general weighted average performance of a single faculty only. Secondly, there are tendencies that assessments are inconsistent and not fairly given because of judgmental biases that affect the optimality in decision making. Thirdly, the manual evaluation is prone to errors especially that it involves computations, under a rapid pace. Hence, accuracy of the result is not secured.

A DSS for instructor’s performance will generate a result of the evaluation with suggestions that will help the dean in decision making. This leads to fast, efficient and reliable assessments. With the system, the deans will be able to assess his subordinates and colleagues fairly and effectively. The said DSS will help the deans construct better decision based on the result and suggestions of the automated teaching performance evaluation system.