Student Evaluation of Online Teaching Quality, Their Own Engagement and Success Expectancy in the Future Profession

Abstract

The aim of this research was to examine students’ perceptions of online teaching, their own engagement and abilities, and their success expectancy in the future profession. 713 students attending the University of Zagreb, Croa-tia, took part in the research. The results indicate that students spend an aver-age of 6 hours studying per day. Statistically significant differences were identified in students’ perceptions of the way in which the teaching process was conducted, support provided by professors and the engagement of stu-dents in terms of the time they spend in organized and independent studying. Students who study less than 5 hours per day tend to give lower rating to the quality of the teaching process and their own engagement. Students who study more than 6 hours per day tend to give lower rating to the support pro-vided by professors. Regression analysis revealed that the perceptions of the way in which the online teaching process was organized and conducted, of the abilities, engagement and hope significantly contribute to the interpreta-tion of success expectancy in the future profession. Students’ age was not found to be a significant predictor.

Improving the Quality of Education in the Development of Algorithmic and Critical Thinking of Students of “Applied Informatics” – Case Study

“…The facts only confirm that systematic management and regular monitoring of students' activities are more or less necessary for achieving satisfactory educational goals, which is in accordance with [21]. Indirectly, this proves the validity of using a complex heterogeneous evaluation system, which is laborious from the point of view of the teacher's work but clearly leads to results, as well as the validity of publishing as many materials as possible.…”

Exploration on Classroom Teaching Quality of Intelligent Digital Information and Cloud Model

“…These resources not only attract students' attention and enhance their interest in learning, but also help them better understand and master knowledge. In addition, intelligent digital information can also collect and analyze students' learning data in real-time, and provide personalized teaching plans and feedback to teachers, thereby improving teaching quality [6].…”

“…Among the indicators that reduce conditional attributes, this article used six indicators, namely language teaching, answering questions, organizing discussions, expanding materials, in class quizzes, video playback function, etc. (represented by [1][2][3][4][5][6]. In order to verify the accuracy of new sample evaluation in the rough set neural network quality evaluation model of online learning platforms, this article selected three online learning platforms distinguished by style (content, interaction, and compatibility) for testing.…”

Readiness of Higher Education Institutions for E-learning Case of Jordanian Universities

“…In their study in three private universities in Jordan Al-Adwan et al, (2021) argued that the quality factors associated with the performance of a faculty member, the technical support system and services, the quality of educational systems and educational content provided to students have a direct positive impact on students' attitudes towards elearning, and the perceived benefit and use of the system, in the same context Vidić et al, 2022;Klasnić (2022) mentioned that e-learning requires the availability of education and training skills and skills, communication skills, and educational sciences. This study is mainly concerned with investigating the Readiness of Jordanian Universities from the perspective of their g faculty members.…”