Engineering students performance evaluation of generic skills measurement: ESPEGS Model

• Main Authors: A. Rashid, Rozeha, Abdullah, Razimah, Zaharim, Azami, Ahmad Ghulman, Hamzah
• Format: Book Section
• Published: World Scientific And Engineering Acad And Soc 2008
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/12834/
• Institution: Universiti Teknologi Malaysia

The Faculty of Electrical Engineering, Universiti Teknologi Malaysia (FKE) teaching and learning processes was certified to ISO 9001:2000 and now seeks the Engineering Accreditation Council of Malaysia (EAC) approval. It is one of FKE top management commitment is to assure the program accreditation requiremets is met. EAC adopts American Accreditation Board of Engineering and Technology 2000 (ABET) principles which promote outcome based education (OBE) learning process. OBE calls for the evaluation of the course learning outcomes (CLO) as specified in each Course Outline. Performance Measurement has been largely dependent on students' performance in 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 oil the achievement of the subject's expected CLO. This paper describes a computational model which can be used to measure a subject CLO in an undergraduate electrical engineering program. An overview of the measurement model and it's key concepts are presented. ESPEGS Model is the acronym for Engineering Student Performance Evaluation on Generic Skills. This model of measurement is jointly developed based on Rasch Measurement can be used to improve the students' assessment method on the CLO of each subject. Results obtained were assessed against the CLO maps for consistency and used as a guide for future improvement of the teaching method. The study shows that this model of measurement, which adopts Rasch Model based on Logistic Regression Model, can classify students learning ability more accurately with only very few randomly selected students and dimensions as compared to the traditional CGPA method.