Comparison of Mental Structures of Eighth-graders in Different Countries on the Basis of Fennema-Sherman Test

Abstract

The intended factor structure of attitude scales in TIMSS 2007 dataset (N > 240, 000) is totally unstructured in several countries. There are two inseparable phenomena which explain the differences between countries. First, the ability level of the students is strictly connected with the level of maturation in thinking. Second, there are differences between countries which cannot be explained by the differences in achievement level. Four distinguishmental structures are identified: "Western" structure, "African-Asian" structure, "Middle Eastern-Asian" structure, and "high-performing East Asian" structure.

Changes in Achievement in and Attitude toward Mathematics of the Finnish Children from Grade 0 to 9—A Longitudinal Study

“…Though the dimensions are the same, the item-wise changes are so radical that the Finnish test is no more Fennema-Sherman test but rather "loosely based on Fennema-Sherman test" as described by Metsämuuronen (2009, p. 20). Further, Metsämuuronen (2012a;2012b) argues, on the basis of extensive study with TIMSS dataset, that the Finnish version would be more suitable in the international settings because it is evident that the original test is not optimal with the lowest achieving students (Metsämuuronen 2012a) and in many Asian countries (Metsämuuronen, 2012b).…”

From beliefs to dynamic affect systems in mathematics education

“…For example, Metsämuuronen ( 2012a ), and Rutkowski and Rutkowski ( 2010 ) reported that some scales (e.g., math self-concept) that had been used in PISA and TIMMS studies showed less reliable scores in East Asia, the Middle East, and Europe, when compared to data from North America, where the scales were originally constructed. Metsämuuronen ( 2012b ) found that in the TIMSS2007, the math attitudes scale were not invariant and manifested " fragmentation " in most of the participating countries (in most low achieving countries) due to different cultural values. With empirical examples, Rutkowski and Rutkowski ( 2010 ) found that the possible cause to this was too much missing data: a possible sign of respondent misinterpretation.…”