A new process has been brought about due to the COVID-19 pandemic that has affected the world. Due to the COVID-19 pandemic, since the spring semester of the 2019–2020 academic year, all education and courses are provided through distance education. Therefore, since distance education is a new process for many, faculty members may encounter various problems. For this reason, deter-mining the views of lecturers about the distance education process is important for the improvement and development of the distance education system. The aim of this study is to examine the views of the lecturers who teach through the dis-tance education system and to make suggestions for the improvement of the sys-tem. The situation was determined using the qualitative research method. The re-search questions were prepared by the researchers. Their validity was ensured by taking experts’ opinions. For this purpose, interviews with semi-structured ques-tions were conducted with 28 instructors at Cyprus and Russian universities and the data obtained were evaluated by content analysis. The findings obtained as a result of the research are given in detail in the findings and results section.

The paper aim is to come up with methodology for performing video learning data history of learner’s video watching logs, video segments or time series data in accordance with learning processes via mobile technologies. To reach this goal, it is introduced a theoretical method of sequential pattern mining specialized for learning histories in identifying the most important or difficult learning. Based on this method, it is designed a model for understanding and learning the most difficult topics of students topics. The user will be able to use and access the model through mobile technologies when and where he/she wants. The performed video learning history data of learner’s video watching logs consists of functions that are responsible for collection of stop/replay/backward data activities, generation of sequence from the collected learning histories, extraction of important patterns from a set of sequences, and findings of learner’s most difficult/important topic from the extracted patterns. The paper mainly describes the model for understanding and learning the most difficult topics through the sequential pattern mining method. Implementing the method to use in mobile phones is considered as future aim.

In this study, which was created with distance education and augmented reality technology, it was aimed to determine the effect on the performance of university students. When the research is examined, it is seen that the quantitative research method is used. The study was carried out in the fall semester of 2021–2022. A total of 422 volunteer university students who continue their achievements in the study participated in the research. In the research, augmented reality, virtual technology and distance education were taught to university students for 5 weeks via online application training. The data collection tool, which was developed by the researchers and organised by experts in the field, was used in the study, simply called ‘Augmented Reality’. The data collection tool was used to collect data of the people who participated in the research and created the research by solving it with the help of virtual programmes. In the analysis of the collected and compiled data, frequency analysis and t-test were used by using the SPSS programme, which is preferred in many studies, and the results were added to the research in the presence of tables. According to the results obtained from the research, it was concluded that university students’ views on distance education and augmented reality were high and there was a difference. Keywords— Distance Education, Augmented Reality, University Students