The potential of multivariate analysis in assessing students' attitude to curriculum subjects

Abstract

Background: Understanding student attitudes to curriculum subjects is central to providing evidence-based options to policy makers in education. Purpose: We illustrate how quantitative approaches used in the social sciences and based on multivariate analysis (categorical Principal Components Analysis, Clustering Analysis and General Linear Modelling), can complement qualitative analysis to support this need. Sample: Our example involved an attitude survey of 128 students from five high schools across Botswana to Design and Technology (DT), this subject having declined in uptake over 10 years by up to 6% per year, despite positive encouragement by the government. Design and methods: Qualitative interviews, carried out concomitantly, indicated consistently that age, gender and school performance all affected attitudes. Multivariate analysis provided additional information in ranking how different attitudes contribute to the overall perception of a subject (PCA-Factor analysis), in assessing the relative and interacting effects of external determinands like age or gender and classifying students into attitude groups. Results: Our findings show that DT enrolment could be improved by targeting children who deemed DT too difficult or unimportant as a subject, and by reinforcing perceptions of DT as an enjoyable life-skill. Conclusions: We suggest that combined quantitative and qualitative analysis can act as an effective, evidence-based means to inform educational policies.

Insights into Flood‐Coping Appraisals of Protection Motivation Theory: Empirical Evidence from Germany and France

“…Third, an unconstrained principal component analysis (PCA) was conducted with the coping appraisal variables in order to present the Euclidean distance between the combinations in an ordination plot. PCA is a method often used in ecology, but increasingly also in the social sciences, to reduce the dimensionality of the data, extracting its most important information and revealing patterns of similarity . To display the groups in the most representative way, a group overlay was passed to the plot (Fig.…”

A Comparative Analysis of Patterns of Girls’ Attitudes towards Design and Technology: Botswana and Swaziland.

“…By performing the PCA, data from the questionnaires was arranged and parameterized along the principal factors that describe attitudes of girls towards Design and Technology. In the PCA, objects or variables that are similar to each other have similar scores on each factor (or axis), while dissimilar ones are far apart (Gaotlhobogwe et al, 2011). This visual understanding from the PCA provided inference on the patterns of attitudes of girls towards Design and Technology in Botswana and Swaziland.…”

“…The short history of Design and Technology in Southern Africa and its association with notions of craft have made it an unpopular subject in schools because neither teachers nor students are familiar with it. Gaotlhobogwe, Laugharne, and Durance (2011) noted that in Europe and the USA 20 years ago, as in Africa today, technology education was new in the curriculum and had evolved from craft-based subjects aimed at less academically oriented students and this appeared to be the main reason why students did not perceive the subject as an important one to choose. Becker and Maunasaiyat (2002) observed that through PATT studies around the world, it became evident that students had incomplete and vague concepts of technology.…”

“…Volk and Ming (1999, p.57) observed that "the attitudes students have about technology, whether received through parents, peers, schooling, or one's daily life experience, play an important role in their ability to participate actively in their current and future technological world". More than just personal choice, the aggregate uptake of curriculum subjects can also have large effects on national economies and social development (Gaotlhobogwe et al, 2011).…”

SPESS: A New Instrument for Measuring Student Perceptions in Earth and Ocean Science

“…Factor analysis is a method commonly used in educational research that categorizes sets of statements by correlations apparent between responses to individual statements, and has been particularly utilized with attitudinal surveys (e.g., Gaothlobogwe et al, 2011). In both steps of the analysis, a principle components analysis with a direct oblimin rotation is used.…”