i-SUFO as teaching evaluation system for lecturer in UiTM Pasir Gudang / Narita Noh ... [et al.] - Noh, Narita; Abdul Razak, Nurul Azida; Mat Yusof, Doris Asmani; Che Lat, Diana; Jamal, Mohammad Hazizi (Universiti Teknologi MARA, Kedah, 2023)
Student feedback online (SUFO) is a must for all programs offered in UiTM as a tool for ensuring the standard quality of the program and accreditation purposed especially for Diploma in Civil Engineering. Although the SUFO result is available in U-future (online platform for teaching, learning and assessment for UiTM students). However, the result is not shared with the auditor or any third party. Hence, analysis on teaching evaluation based on SUFO should be carried out separately to confirm all lecturers achieve at least 3.0 as minimum key performance indicator as stipulated by college. Previously, SUFO data will be gathered from online survey spreadsheet and data will be transferred to master spread sheet to produce graph for at least 5 consequences semester. Analysis and graph generation normally takes about 2 to 3 days to complete. This process is tedious and tiring for the person in charge (PIC) and sometimes, there is tendency to make mistakes while exporting data to master spreadsheet. Hence, i-SUFO is developed to improve the efficiency of data collection, storage, display, and graph generator. This system uses an online platform via shared point server. The lecturer will sign in, using Microsoft 365 account to fill in the form. The system will record the data and graph for individual performance will be displayed on the home page of the sites. Hence, lecturers would be able to monitor their performance for each semester, which is not being shown based on previous method. Immediately, for accreditation and audit purposes summary data for all lecturers is available in the summary graph immediate after lecturer keys in the data using the system. PIC is no longer required to analyses the data because graph is automatically generated using existing pivot table in the system. Moreover, the authenticity of the data is more valid.