Purpose – It is a normal practice that students’ overall scores are computed by simple average (SA) method which considers all academic subjects as having the same weights or same degree of importance. This paper highlights the application of simple weighted average (SWA) as an alternative method in aggregating students’ academic achievements. The weights of the academic subjects must be determined prior to the use of SWA.   Methodology – In a case study, a group of five teachers from one primary school was asked to rate five main subjects taught in primary schools according to their importance. These five teachers have taught the five subjects for more than six years. The obtained weights values were used to re-compute 2011 mid-semester final examination scores of 33 year-six pupils at the selected primary school.   Findings – The teachers decided to give different weight to three subjects, but same weights to two subjects. Furthermore, the SWA scores give different ranking to the pupils as compared to the SA scores. Another sentence or two needed here to explain the findings.   Significance – It is argued that the use of the SWA method is more suitable than the simple average method in finding the overall scores of students’ achievements. The SWA method considers the subjects to have different degrees of importance, as they do in the actual educational context.

Abstract. In the context of multi-criteria decision making (MCDM), the average method used in Integrated Students Information System (ISIS) can be classified as an additive measure where the students' academic achievement are aggregated based on the assumption that there is no interaction among the evaluation criteria or the criteria are independent. This method is not suitable to be used if the schools look for equilibrium in their students' achievement. Thus, the non-additive aggregation operator is chosen to analyze students' academic achievements by further taking into accounts the interactions between the subjects. The measures of interaction were represented as λ-fuzzy measures. The effectiveness and success of this non-additive measures can be recognized by comparing the results of the new ranking which was obtained by nonadditive aggregation operator with the current approach of ranking that were based on the global scores using average score method. Throughout this study, it could be postulated that employing the non-additive aggregation operators to obtain an overall evaluation is more suitable because this method able to deal with interactions among subjects whereas the average method only assumes that there is no interaction between subjects or the subjects must be independent.

Abstract. Many average methods are available to aggregate a set of numbers to become single number. However these methods do not consider the interdependencies between the criteria of the related numbers. This paper is highlighting the Choquet Integral method as an alternative aggregation method where the interdependency estimates between the criteria are comprised in the aggregation process. The interdependency values can be estimated by using lambda fuzzy measure method. By considering the interdependencies or interaction between the criteria, the resulted aggregated values are more meaningful as compared to the ones obtained by normal average methods. The application of the Choquet Integral is illustrated in a case study of finding the overall academic achievement of year six pupils in a selected primary school in a northern state of Malaysia.

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