Browsing by Subject "konfirmatorinen faktorianalyysi"

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  • Vartiainen, Liisa (Helsingin yliopisto, 2018)
    Aims. The aim of this Master’s Thesis (Special Education) is to evaluate reliability and validity of the CodyTest in Finland with grade 2–4 children. The CodyTest is designed to identify children who are at risk for mathematical learning difficulties. The test’s reliability and validity has been evaluated in German sample, but not before with Finnish sample. Methods. Fivehundredthirteen children participate the study. Data was collected during years 2016–2017 and that was part of teacher’s training program of Niilo Mäki Instituutti. The teachers used the test with children in their own classes. The data is owned by Niilo Mäki Instituutti, which granted it to be used in this study. The construction of CodyTest was evaluated by confirmatory factor analysis (CFA) and the reliability was evaluated by Cronbach’s alfa. Configural freqvency analysis and Pearson’s correlation was used to assess if the results of CodyTest were stable over seven months. The concurrent validity of CodyTest was evaluated with correlations between CodyTest and other mathematical skills tests. Results. The structural equation model which was found by CFA has a good fit (X^2 (33)=99.427, p<0.001, CFI=0.96, TLI=0.93, RMSEA=0.06). The analysis showed that CodyTest has two latent factors, namely “subitizing and comparing” (α=0.75) and “number sequence and basic arithmetic skills” (α=0.74). The composite test’s reliability was 0.77. The stability of CodyTest’s scores were reliable between seven months, the test-retest correlations were high, and it was possible to identify low performing children both times. The two factor and composite scores were correlating with mathematics skills test total scores. The results in this thesis show that the reliability and validity of CodyTest are good in Finnish sample.
  • Viljakainen, Reeta (Helsingin yliopisto, 2020)
    The aim of this study was to find out how much enjoyment, boredom and anxiety students experience in mathematics-related situations: during lessons, homework and tests. The study investigates the relations of these emotions with achievement in mathematics. Moreover, gender, school and classroom differences in these relationships are examined. In spring 2017, 215 third-graders from four Helsinki schools responded to the AEQ-ES (Achievement Emotions Questionnaire-Elementary School) survey and participated in three tests measuring mathematics achievement as part of the MathMot study. The fit of the data for the AEQ-ES structural model was analysed using confirmatory factor analysis. The connections between emotions and achievement as well as differences in these connections were studied by non-parametric methods: the Mann-Whitney U and Kruskal-Wallis H tests, as well as Spearman’s rank correlation coefficient. The study revealed that students experienced much more mathematics-related enjoyment than boredom or anxiety, which were experienced very little. Consistent with findings from previous research, it was found that emotions are related to achievement, positively to enjoyment and negatively to boredom and anxiety. This connection was strongest in emotions associated with lessons. Few statistically significant differences were observed between genders. In terms of achievement, there was a statistically significant difference between schools in all mathematics tests. Differences were also found between classrooms, albeit not in all tests. Furthermore, between a school receiving positive discrimination funding and a school providing weighted-curriculum education, there was a statistically significant difference in achievement and some emotions.
  • Pousi, Iina (Helsingin yliopisto, 2020)
    Reflection is often stated as a learning outcome of teacher education. However no consistent method exists to assess the extent to which students engage in reflective thinking. The purpose of this study is to explore the utility of Reflection Questionnaire developed by Kember et al. (2000) for measuring the reflection levels of Finnish pre-service teachers. In addition, the Reflection Questionnaire is placed as a part of a broader theoretical framework by examining associations between students’ approaches to learning and stages of reflective thinking. The data (n= 220) was collected in the spring of 2018 and it consisted of pre-service teachers at the beginning of their studies at the University of Helsinki. The reliability and validity of the instrument was examined in terms of internal consistency, structural validity, convergence validity, discriminant validity and nomological validity. The internal consistency was estimated by calculating Cronbach’s alpha. Confirmatory factor analysis (CFA) was used to examine the structural, convergent and discriminant validity of the Reflection Questionnaire. Nomological validity was examined using ALSI questionnaire which measures deep and surface approaches to learning. The Cronbach's alpha values signified that the dimensions of the Finnish version of Reflection Questionnaire were internally consistent. The confirmatory factor analysis indicated acceptable model fit and confirmed the original four-factor model, indicating structural validity of the instrument. In addition, the relationships between the dimensions of reflection supported convergence and discriminant validity. Relationships between deep and surface approaches to learning and the dimensions of reflection provided evidence of nomological validity. These findings reveal the utility of Reflection Questionnaire in measuring reflection levels of pre-service teachers. The Finnish version of Reflection Questionnaire is a valid instrument to be used for learning the extent to which students are engaging in the reflective thinking.
  • Mattsson, Markus (Helsingin yliopisto, 2015)
    In this Master's thesis I examine the measurement invariance of the Driver Behavior Questionnaire (DBQ), the perhaps most widely used questionnaire instrument in traffic psychology, across samples of Finnish and Irish young drivers (18 - 25 years of age). The DBQ was developed in the beginning of the 1990s based on principal component analyses. The questionnaire was originally based on a well-tested theory in cognitive ergonomics (the Generic Error Modeling System, GEMS), but in the research that has ensued, the item pool and the factor structure has been determined in an exploratory fashion. This has resulted in an abundance of DBQ versions, which comprise anything from nine to over one hundred items and from one to seven factors. Further, in research articles based on the DBQ, it is a common practice to calculate sum or average scores and compare them across subgroups of respondents. The 28-item version of questionnaire, which is currently perhaps most widely used, is thought to measure two, three or four latent variables. In this thesis I use confirmatory factor analysis and, specifically, analysis of measurement invariance to examine which of the three alternative factor structures functions as the most fitting description of the responses of Finnish and Irish young drivers. The analysis of measurement invariance is based on fitting a series of increasingly restrictive models to data. At each stage of the analysis, an increasing set of parameters are constrained to equality across the samples under comparison. In case the constrained model does not fit the data worse than the unconstrained model, the constrained model can be applied in all (in this thesis both) data sets. The models that are fit to data are, in order: 1) The configural model in which only the number of factors is constrained, 2) the weak invariance model, in which factor loadings are constrained to equality, 3) the strong invariance model, in which also the intercept terms of each item are constrained to equality and 4) the strict invariance model, in which also the error terms of each item are constrained to equality. In addition, models of partial invariance are applied. In these models, only some of the constraints related to each stage of the analysis are preserved. In addition to comparing the models statistically, their fit to data is examined using various descriptive statistics and graphical representations. As a central result I propose that the four-factor model offers the best fit to both data sets, even though the model needs to be modified in an exploratory mode of analysis to ensure sufficient fit to data. Further analyses show that two of the four factors are different in nature in the two samples and that only in the Irish data set do all of the items load on the factors they are expected to. On the other hand, the analysis of the other two factors shows that the items that load on them are interpreted essentially similarly in the two samples and that weak invariance can be assumed on their part. In addition, partial strong invariance can be assumed in the case of one factor, even though even then the values of most of the intercept terms need to be freely estimated in the two data sets. As a conclusion I suggest that, in contrast to the prevailing practice, comparing sum scores based on DBQ factors is dubious and that comparing latent variables scores may be justified only in the case of one factor out of four. As a practical recommendation, I suggest that the factor structure of the DBQ be further developed based on theories of cognitive ergonomics and cognitive psychology and that invariance analyses be performed as a matter of routine before carrying out comparisons of groups based on results of factor analyses.