**3.2 Participants and procedure**

The testing group comprised 561 university students of two universities and one independent higher education school in Slovenia. Composition of the group by gender, study year, and type of study major is shown in **Table 3**.

All 561 students took the IL test before taking any IL-dedicated classes. At the same time, they also took the SL test and both ICT and psychological questionnaires. *Factors Influencing Information Literacy of University Students DOI: http://dx.doi.org/10.5772/intechopen.109436*


#### **Table 3.**

*Testing group composition by demographic parameters.*

Of the 561 students, 151 later took a credit-bearing IL course, described in the instruments section. This group of students took the IL test again as a post-test, so that the change in their IL skills could be studied in comparison to the test results before the course (pre-test). The 151 students were divided into three groups based on the teaching method used in the course: lecture-based (52 students), project-based (52 students), and problem-based (47 students) learning.

The online survey system 1 ka (1 ka.si) was applied for testing, which took place at university locations, in presence of a professor. Before testing, an introductory protocol was administered, providing explanation of the study goals and assurances of anonymity and voluntary, emphasizing participation. There was no time limit for completing the tests and questionnaires.

#### **3.3 Analyses**

Reliability in terms of Cronbach alpha was calculated for IL and SL tests, 4 ICT, and 7 psychological/learning subscales. IL score means were analyzed, both total scores and partial scores, corresponding to the five IL content categories and three cognitive categories. Differences in IL levels between the pre-test and the post-test were measured with paired t-tests. Differences in IL between teaching methods and differences in IL between demographic parameters (gender, type of study major, study year) were investigated using two-sample t-tests. SL score means were analyzed for total scores and cognitive categories. Means were also calculated for ICT subscales as well as psychological subscales. Pearson's correlation coefficients were calculated between IL and SL, their content/cognitive subscales, and ICT and psychological subscales. Multiple linear regression was applied to predict the IL level from other parameters: SL, demographic parameters, ICT, and psychological/learning parameters. All data collected were analyzed using Microsoft Excel.
