Oldal 103 [103]
STUDY Two
reduction; however, the positive aspect of it is that it creates a manageable
number of factors.
First the activities were divided into two sections: those involving reading
and the rest of the activities made up the “miscellaneous” category. Once ac¬
tivities were categorized, factor analysis (maximum likelihood with varimax
rotation) was used to identify the different dimensions within the categories.
Furthermore, varimax rotation was used in the analysis, and the rotated factor
matrix was used in the analysis of the results without the small values (<.3)
omitted from Tables 13 and 14, in which the factor structures are visually
represented. In the second step of the analysis, scales were created from the
factors in order to perform further analyses of the database and to explore
possible relationships between the factors by correlation and regression anal¬
ysis.
Half of the EE activities in the questionnaire (nine activities) were found to
be related to reading, so as a first step, these nine statements were investi¬
gated (see Table 17); factor analysis revealed that these EE activities load onto
two dimensions. Consequently, Factor 1 was named “online reading” as all of
the activities loading onto this dimension may be pursued online, and Factor
2 was named “paper-based reading” as activities 15, 17, and 11 are tradition¬
ally accessible in a printed format.
Table 17. Results of factor analysis examining EE activities related to reading
EE activities Factors
1 2
6. EE reading websites 741
18. EE reading news .677
8. EE reading blogs .659
5. EE reading Twitter posts .629
10. EE read posts on Instagram .612
13. EE reading posts on Facebook .542
15. EE reading magazines 846
17. EE reading newspapers 841
11. EE reading books .650
The rest of the EE activities (9 activities) were also subjected to factor
analysis (maximum likelihood with varimax rotation), which revealed that
these activities loaded onto a total of six different dimensions (see Table 18).
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