In order to get a proper answer, you should provide more information about variables and about the type of data you want to analyze. If you have one dependent variable (readiness to E-learning) with interval data and one independent variable (academic performance) with categorical data you will test the hypothesis by employing One Way Anova test. However, you should provide more information about variables and data.

In order to get a proper answer, you should provide more information about variables and about the type of data you want to analyze. If you have one dependent variable (readiness to E-learning) with interval data and one independent variable (academic performance) with categorical data you will test the hypothesis by employing One Way Anova test. However, you should provide more information about variables and data.

Concerning your hypotheses, you should

a) adjust your H0 so that it does not interpret potential results more than your H1, e.g.," there is no relationship between these variables"

b) your eesearch design and hypotheses should follow your research questions. So ask yourself what you would like to know. By now I think you could go for an investigation of the relationship, and investigate it by means of a correlation, or you could hypothesize that students' readiness affects the grades more than other variables (tentative evidenceight come from regression analysis )

Dear Senad Bećirović

I really appreciate your answer

well, in this study the independent variable is students' readiness for E-learning, while the dependent variable is the students' academic performance

The aim of the study is to examine whether students' academic performance changes depending on their readiness for E-learning

To collect data I intend to use a questionnaire of 5-point Likert-scale questions ((1) Strongly disagree; (2) Disagree; (3) Neither agree nor disagree; (4) Agree; (5) Strongly agree) to measure the indicators of readiness for E-learning (time-management skills, access to technology, and self-direction)

Besides, another question about students' grades in the previous semester.

I hope I made the necessary clarifications.

Sven Greving Thank you very much for your suggestion.

Apply direct (i.e., exams, students grades, academic performance) and indirect (i.e., surveys) evaluation methods.

Good ideas. Let me add a short note: I do think that we are dealing with different personality types. For me, distances studies were a blessing, because I could work and learn. However, I visited often lectures of good teachers, and there is no substitute for this personal learning experience. Before you embark into the construction of any testing battery, it is, in my humble opinion , important to consider the qualitative elements of the learners (e.g. who gains by e-learning, who loses something by e-learning? which subjects do profit vs. suffer from e-learning? ).

A. Wheeler formulated the working principle: never make a calculation, if you do not know the answer (structure of the result).

There are several factors that affect the reception and welcome of e-learning, which is the subject of study, especially if it is mathematical and derivation, as well as if the material is new to students and to forget the power of the internet network and communication and possibilities available