Judy Sheard, Martin Dick, Selby Markham

March 2001

This is Part 2 of a report on a study that aims to determine attitudes towards questionable work practices of postgraduate and graduate diploma students within the School of Computer Science and Software Engineering (CSSE).

More details of the study and the research method used may be found in Part 1 of this report at ???

The students’ ratings of the acceptability of the scenarios were analysed using a factor analysis. This is a method used to determine a latent variable structure that can account for intercorrelations of an observed set of variables. The factor analysis method performed used a Principal Axis Factoring extraction and a Varimax rotation with Kaiser normalization.

Examination of the variable loadings within the rotated factor matrix, using a minimum variable loading of |0.4|, indicate interpretable results for each factor. The variable loadings are shown in Table 1 and the scenarios within each factor structure are shown in Table 2.

Table 1 Rotated Factor Matrix (rotation converged in 6 iterations)

The students’ ratings of the likelihood of each reason causing cheating were analysed using a factor analysis. The factor analysis method performed used a Principal Axis Factoring extraction and a Varimax rotation with Kaiser normalization.

The factor analysis yielded four factors with eigenvalues greater than 1.0. Examination of the variable loadings within the rotated factor matrix indicate interpretable results for each factor. One variable (Q22H) is salient within two factors. The variable loadings are shown in Table 3 and the reasons for cheating within each factor structure are shown in Table 4.

Table 3 Rotated Factor Matrix (rotation converged in 11 iterations)

The students’ ratings of the likelihood of each reason preventing cheating were analysed using a factor analysis. The factor analysis method performed used a Principal Axis Factoring extraction and a Varimax rotation with Kaiser normalization.

The factor analysis yielded three factors with eigenvalues greater than 1.0. Examination of the variable loadings within the rotated factor matrix produced indicate interpretable results for each factor. The variable loadings are shown in Table 5 and the reasons within each factor structure are shown in Table 6.

Table 5 Rotated Factor Matrix (rotation converged in 5 iterations)