Functional Monitoring and Control in Electronic Information and Educational Environment

Abstract

 Abstract: The paper deals with the monitoring of the functioning and control of the effectiveness of the use of electronic information and educational environment of higher education. Particular attention is paid to the registration of events and their analysis in the Moodle learning management system from the perspective of the organization of educational interaction and analytical activities of the management. It is noted that the learning management system Moodle can not without additional plugins to provide information about site visitors, traffic sources, load indicators on the system. External tools, such as «Yandex.Metrics». By integrating this information system into the electronic information and educational environment of the University, it is possible to analyze additional statistical data (number and age of visitors, devices used to enter the environment). The obtained information allows not only to optimize the educational process from the position of control over the study of educational material, but also to significantly improve the efficiency, convenience and quality of work of students in the electronic information and educational environment of higher education. Index Terms: electronic information and educational environment, e-learning, control, monitoring the functioning of information systems

Monitoring of Student Learning in Learning Management Systems: An Application of Educational Data Mining Techniques

“…This is obviously a problem for the early prevention of the at-risk student. A further step in the analysis of logs has been taken with the incorporation of plugins that are inserted in LMSs [2,[23][24][25][26][27][28][29][30][31] and facilitate the analysis and interpretation of the logs. The use of these tools provides a series of advances in the organisation and interpretation of the data and in the detection of the student at risk in the different learning objects (activities and resources), because it allows the teacher to choose the standard deviation (SD) that they consider to be an indicator of the detection of at-risk students (1, 2, 3, etc., SD) in their subject.…”

Perceived satisfaction of university students with the use of chatbots as a tool for self-regulated learning

“…However, the lack of influence of that knowledge on the use of the chatbot can be explained by the need to improve the feedback provided by the conversational agent [ 45 ] by increasing the types of questions and answers. These question-answer pairs could be tailored to different levels of prior knowledge [ 1 , 50 , 56 ].…”

“…Students’ technology skills is another important variable for the effective use of chatbots. In addition, Tsivitanidou & Ioannou [ 2 ] indicated the importance of monitoring the learning process by offering personalised feedback to each student [ 1 , 49 , 50 ]. This means that the process of building a chatbot becomes a challenge of technological structure and instructional design.…”

Monitoring Students at the University: Design and Application of a Moodle Plugin

“…Similarly, the data analyses with a learning analytics system that includes comparative averaged values and deviation from the average offer additional advantages, as well as the option of storing the results in databases that can be exported in different file formats (.csv, .xlsx, HTML table, .json, .ods, .pdf). This functionality facilitates the use of different statistical packages or libraries in which more complex data-analysis techniques can be applied, such as supervised and unsupervised learning techniques [36,[47][48][49]. The use of these techniques establishes predictive and grouping factors that will facilitate the development of specific and personalized learning for each student at each moment of their learning process.…”

“…For this reason, LMSs must include plugins that offer teachers different functionalities for processing, interpreting, and visualizing the results. Within these plugins, the use of supervised and unsupervised learning techniques will be essential for monitoring students [48]. The plugins will facilitate an analysis of student learning patterns and their past grades, which will allow the teacher to offer a personalized educational response tailored to personal characteristics and needs throughout the learning process of each student on the degree course [48,49].…”