Outcome based education performance measurement: A Rasch-based longitudinal assessment model to measure information management courses LO's - Mohamed, Azlinah; Abd. Aziz, Azrilah; Ahlan, Abdul Rahman; Zakaria, Sohaimi; Masodi, Mohdsaidfudin (World Scientific and Engineering Academy and Society, 2008)
Malaysia Qualification Framework, 2005 (MQF) promotes outcome based education (OBE) learning process. OBE calls for the evaluation of the course’s Learning Outcomes (CLO) as specified in the Program Specification. This good practice is implemented in the Faculty of Information Technology and Quantitative Science, Universiti Teknologi MARA (FTMSK) teaching and learning processes which was duly certified to ISO 9001:2000. Assessment methods include giving students’ tasks such as tests, quizzes or assignments at intervals during the 14 weeks study period per semester. CLO’s were evaluated based on the students’ performance which gives an indication of their learning achievements. Despite the marks obtained is orderly in manner, it is on a continuum scale. Hence, further evaluation using the raw score is rather complex to be carried out. This paper describes a Rasch-based measurement model as performance assessment tool to measure the CLO. Rasch Model uses ‘logit’ as the measurement unit thus transforms the assessment results into a linear correlation. An overview of the measurement model and its key concepts were presented and illustrated. An assessment form using Bloom’s Taxonomy as parameter was designed showing each dimension of the ability to be measured. The results there from were evaluated on how well it relates to the attributes being assessed and scrutinized. It is further checked against the CLO Maps for consistency and used as a guide for future improvement of the teaching method and style. This provides the lecturers a more accurate insight of the student level of competency achieved. The study shows that this model of measurement can classify students’ grades into linear competency scale accurately using only very few primary data sets to enable corrective action to be taken effectively at the early stage of learning.