Universiti Teknologi Malaysia Institutional Repository

Engineering students performance evaluation of generic skills measurement: ESPEGS Model

A. Rashid, Rozeha and Abdullah, Razimah and Zaharim, Azami and Ahmad Ghulman, Hamzah (2008) Engineering students performance evaluation of generic skills measurement: ESPEGS Model. In: New Aspects Of Engineering Education. World Scientific And Engineering Acad And Soc, Athens, Grece, pp. 377-383. ISBN 978-960-6766-86-2

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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.

Item Type:Book Section
Additional Information:ISBN: 978-960-6766-86-2; 5th IASME/WSEAS International Conference on Engineering Education, Heraklion, Greece, Jul 22-24, 2008
Uncontrolled Keywords:learning outcomes, performance measurement, quality, engineering education, rasch measurement
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:12834
Deposited By: Liza Porijo
Deposited On:30 Jun 2011 10:11
Last Modified:30 Jun 2011 10:11

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