Outcome based education performance assessment: a computational model to measure electrical engineering subjects learning outcomes

Engineering Accreditation Council of Malaysia (EAC) adopts the American Accreditation Board of Engineering and Technology 2000 (ABET) requirements which promote outcome based education (OBE) learning process. OBE calls for the evaluation of the subjects learning outcomes (LO) as specified in the Programme Specification. This good practice is implemented in the Faculty of Electrical Engineering, Universiti Teknologi Malaysia (FKE) teaching and learning processes which was duly certified to ISO 9001:2000. Evaluation method has been largely dependent on students' performance carrying out tasks such as tests, quizzes or submission of assignments. Evaluation on the performance outputs; categorised as technical knowledge and generic skills, gives an indication on the achievement of the subject expected LO. Technical knowledge is largely taken care of by the Final Exam papers. However, evaluation of generic skills remain vague. This paper describes a measurement model which can be used to measure a subject LO of an undergraduate electrical engineering subject. An overview of the measurement model and its key concepts are presented and illustrated using assignments given through SEE 2523 - Electromagnetic Field Theory. The assignments were evaluated on how well it relates to the generic skills dimension being assessed and scrutinised, whether it correspond to the LO that is to be measured. The model has a simple framework where an evaluation form was designed showing each dimension of the generic skills to be assessed. Attributes for each dimension were duly identified and coded dichotomously to clearly define the assessment. Results obtained were assessed against the course LO maps for consistency and used as a guide for future improvement of the teaching method and style. The study shows that this model of measurement can classify grades into learning outcomes accurately with only very few randomly selected dimensions.