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Fuzzy Rules In Assessing Student Learning Outcomes

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2006 Annual Conference & Exposition


Chicago, Illinois

Publication Date

June 18, 2006

Start Date

June 18, 2006

End Date

June 21, 2006



Conference Session


Tagged Division

Educational Research and Methods

Page Count


Page Numbers

11.659.1 - 11.659.9



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Paper Authors


Faouzi Bouslama Zayed University

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Faouzi received a PhD in Electronics Engineering from Shizuoka University, Japan, in 1992. From 1992-1994, he was a researcher at Toshiba Co., Tokyo. From 1994-2000, he was Associate Professor of Information Systems, Hiroshima City University, Japan. He joined Zayed University, UAE, in August 2000. Currently, he is a Professor of Information Systems, Zayed University, UAE. His research interests include Neuro-fuzzy modeling and control, Signal processing, and IS curriculum design and development.

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Azzedine Lansari Zayed University

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Azzedine received a PhD in Biomedical Engineering from North Carolina State University in 1992. From 1992-1998, he was a senior researcher at MANTECH, NC. He joined Zayed University in August 1998. Currently he is an assistant professor of Information systems. His research interests include systems modeling, educational technology and curriculum design in Information Systems. His teaching interests include instructional technology and statistical modeling.

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Akram Al-Rawi Zayed University

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Akram is a Professor of CIS at Zayed University, UAE. He has worked at several academic institutions of which the last two were the University of Missouri-Columbia and Columbia College, MO. His teaching interests in-clude programming languages, logic design, and computer architecture. His research interests include computer simulation, web-caching architecture, and curriculum design. He holds certifications in A+, Network+, Sun Certi-fied Java Programmer, ICDL, i-Net+ and CCNA Intro.

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Fuzzy Rules in Assessing Student Learning Outcomes


In this paper, it is shown how fuzzy rules can be used as a modeling and evaluation tool for the achievement of the learning outcomes in information systems (IS) courses. In an outcome-based educational model (OBE), all courses in an IS college are required to clearly demonstrate the experiences that students can gain upon achieving a learning outcome. Consequently, master course syllabi describing the integration of the desired learning outcomes into IS courses are developed. The IS college provides a map between passing a given course and achieving a particular learning outcome at a certain level. Four different levels of achievements are identified: Beginning, Developmental, Achieved and Exemplary. Though, the map shows a clear relationship between courses and learning outcomes, it is not easy to define the boundaries between these four achievement levels or to combine all of the achievement results into one final assessment. In this case, the use of fuzzy logic is suitable to represent the complexities and vagueness in modeling the students learning outcomes achievements. Fuzzy membership functions are developed to model the achievement levels and define their overlaps and Fuzzy rules are generated to model the relationship between course grade (input) and the expected achievement level of learning outcomes (output). The aggregation of all learning outcome achievement levels for a sequence of courses that a student has to take provides an approximate indication of the experiences learned. Moreover, an overall analysis of all students’ performances can identify the inherent strengths and weaknesses in the outcome-based educational model. Furthermore, theses results can be used by faculty members to assess the effectiveness of the integration of the learning outcomes into their courses.

1. Introduction

Academic institutions, when moving to an outcome-based education, try to ensure that all students acquire appropriate skills to be effective and productive in the workplace. At Zayed University (ZU), an all female laptop university in the United Arab Emirates (UAE), the education model is based on Learning Outcomes (LOs). The Outcomes-Based Education (OBE) model at ZU is framed by two different sets of LOs1. One set is course embedded, the MAjor Learning Outcomes (MALOs), and another one is a set of higher intellectual outcomes called the ZU Learning Outcomes (ZULOs). To fulfill their ZULO and MALOS requirements, students compile evidence of their achievement in electronic portfolios (ePortfolios), which are then later assessed by faculty members. The LOs are observable demonstrations of student learning that occur after a significant set of learning experiences. Typically, these demonstrations or performances reflect what students know, what they can actually do with what they know, and their confidence and motivation in demonstrating what they know.

Although the OBE2,3 is a very promising approach which answers the needs for students to have skills that can make them competitive once they join the workforce, there are a number of issues that need to be carefully addressed for the OBE to be successful and to have efficient implementation. Issues such as the evaluation and the assessment of the student’s work, the efficient selection of activities that lead to achieving a given LO, and the courses design are

Bouslama, F., & Lansari, A., & Al-Rawi, A. (2006, June), Fuzzy Rules In Assessing Student Learning Outcomes Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--1101

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