Reviewing Academic Motivation Levels of Students Study in Different Faculties in Terms of Certain Variables (Sakarya University Case)

Abstract

Entirely 1325 students participated in this research that was conducted to specify the differences between motivation levels of students in terms of age, gender, class and department variables. 'Academic Motivation Scale' that is seven points Likert scale was developed by Karaguven (2012) was used as the data collection tool in this research that was performed by screening model. Descriptive analyses were applied in data T-test was applied in independent groups to determine whether there were differences based on gender and age ranges. One Way ANOVA Test was conducted to specify the differences based on classes and departments. There was found statistically significant differences (p<0,01) between academic motivation sub-dimensions were evaluated based on age range, gender, classes and departments. It is thought that associating these differences with different variables will be beneficial to determine the sources of the differences. Because there are several internal and external factors that positively and negatively affect the motivation level. Eliminating problems by founding the factors can contribute to increasing the motivation level of students and accordingly, the success rate increases as well.

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Factors Affecting Students' Financial Literation: A Study on Widyatama University, Indonesia

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Examining Demographic Differences in Online Learning Self-Efficacy and Online Self-Regulated Learning

“…Students of ages below 20 years old also showed significantly high scores in all online self-regulated learning dimensions compared to older age students. This finding indicated that younger age students had higher extrinsic motivation levels which may be because they just entered and experienced studying in university and they have high motivation to work hard and self-regulate learning for success, but as the age increases, they may steer away from this motivational level because of several different reasons such as experiences and expectations that had fall behind (Keskin & Korkutata, 2018). Third, students in lower semesters; 1 or 2, showed to have higher scores in the five online learning selfefficacy dimensions; self-efficacy in computer/internet, self-efficacy in time management, self-efficacy to interact with lecturers for online courses, self-efficacy to interact socially with classmates, and self-efficacy to interact academically with classmates.…”

“…Overall, students in lower semesters; 1 or 2, were likely to exhibit higher online learning self-efficacy which was inconsistent with studies by (Limiansi & Hadi, 2022), (Yavuzalp & Bahcivan, n.d.), and online selfregulated learning. The possible reason is, that students in lower semesters; 1 or 2, were those students who just entered the university with high levels of excitement and motivation to learn for success (Keskin & Korkutata, 2018).…”