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Research and Development of Examination Methods for Distance Learning Systems

Student: Kachalova Maria

Supervisor: Sergey G. Efremov

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Bachelor)

Final Grade: 10

Year of Graduation: 2017

In this paper, various approaches to knowledge verification in distance learning are explored, and a method for monitoring knowledge on distance learning platforms using Eye Tracking technology is developed. Stated tasks: • Identify the theoretical foundations of the problem: O Characteristics of distance learning O Analysis of the problem of knowledge control in online learning. • Studying the basics of using Eye Tracking technology in various fields. • Development of a method for controlling knowledge in the process of testing on the distance learning platform. • Comparison of existing methods of knowledge control with the developed one. In the work the set goal was achieved and the formulated tasks were solved. The following important theses were obtained during the work: In a series of interviews with distance learning specialists and an expert of proctoring, model limitations were formulated, and an important conclusion was reached: Eye Tracking does not provide the minimum permissible level of reliability in the control of knowledge when using conventional equipment, so it can only be used in conjunction with other methods of control. In addition, Eye Tracking can optimize proctoring process, reducing the cost by 10 times by ranking students in the exam using optimizing algorithms (such as ranking students and video compression). However, Eye Tracking does not cover all problem situations, so it should be used in conjunction with other methods. Therefore, during the research, the method "Anticheating " was developed, which, monitoring 7 key parameters, is capable of exercising quality control over the student during testing. The developed method covers major problematic situations in the process of passing online testing and can bring distance learning to a new level by increasing the level of confidence in the results obtained.

Full text (added May 19, 2017)

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