The aims of this study were to evaluate reliability and validity of the Students' Perception of Assessment Questionnaire (SPAQ), to evaluate students' perception on assessment, and to evaluate gender-based, grade-based, and ethnicity-based differences in students' perceptions. The validity and reliability coefficients revealed that the SPAQ was suitable for assessing students' perceptions on five assessment dimensions. The average scale-item mean values for all the scales were less than 3.0, which indicates a need to address these dimensions of assessment at classroom level. The mean value for Student Consultation scale was 1.96 out of 4, indicating a need for special attention in this area. The perceptions of students grouped on the basis of gender and of grade level groups were comparable, but on the basis of ethnic groups were statistically significantly different. Assuming these differences to be real, does it mean that teaching approaches will need to be addressed? Future research in this area is warranted.

No abstract

No abstract

No abstract

Multivariate statistical techniques such as factor analysis (FA) and Discriminant analysis (DA), were applied for the evaluation of spatial variations and the interpretation of a large complex water quality data set of two rivers (Juru and Jejawi) in Malaysia, monitoring 10 parameters at 10 different sites each. Factor analysis resulted in two factors explaining more than 82% of the total variance in water quality data set. The factors indicate that the possible variances in water quality may be due to either sources of anthropogenic origin or due to different biochemical processes that are taking place in the system. The first factor called pseudo anthropogenic factor explained 59.29% of the total variance. The second factor called anthropogenic explained 23.03%. DA gave the best result to identify the relative contribution for all parameters in discriminating (distinguishing) the two rivers affording 100 % correct assignations. This study illustrates the benefit of multivariate statistical techniques for analyzing and interpretation of complex data sets, and to plan for future studies