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Regular version of the site
Book
eLearning Stakeholders and Researchers Summit 2018: Материалы международной конференции

Edited by: Е. Ю. Кулик

М.: Национальный исследовательский университет "Высшая школа экономики", 2018.

Article
Measuring student’s proficiency in MOOCs: Multiple attempts extensions for the Rasch model

Abbakumov D., Desmet P., Van den Noortgate W.

Heliyon. 2018. Vol. 4. No. 12. P. 1-15.

Book chapter
Integrating MOOCs in University Curriculum: HSE University Experience

Kulik E., Kidimova K. A.

In bk.: Proceedings of Work in Progress Papers of the Experience and Research Tracks and Position Papers of the Policy Track at EMOOCs 2017. CEUR Workshop Proceedings, 2017. P. 118-127.

Book
eLearning Stakeholders and Researchers Summit 2017. Материалы международной конференции

Edited by: Е. Ю. Кулик, У. Кускин

М.: Национальный исследовательский университет "Высшая школа экономики", 2017.

Modern Digital Educational Environment in the Russian Federation

Contemporary Digital Education in Russia

«Modern Digital Educational Environment in the Russian Federation» (see project factsheet (in Russian) on the website of the Russian Ministry of Education and Science) is a priority project being implemented under the auspices of the Russian ‘Education Development’ programme for 2013–2020. HSE has been charged with implementing one of the project’s main tasks: developing and introducing methodologies and instruments for psychometric analysis of online courses.

An automatic psychometric analysis service has been developed by the staff of the HSE eLearning Office and integrated with the online.edu.ru portal’s subsystem (a ‘one stop shop’ information service), which ensures access to 100s of Russian online courses. The service’s functions are open to all users: online course developers, who are registered on the portal. Analysis of course data allows the authors to improve content, adapt it for the needs of specific groups of students, as well as provide more objective assessments and, as a result, improve the effectiveness of studies.

When taking an online course, learners leave behind their ‘digital footprint’. In other words, this would mean statistical data on such things as views of a lecture video or test performance information (including such metrics as duration, total attempts, the ratio of correct to incorrect answers, etc.), as well as peer reviews of other students. This results in a large quantity of data, which can be stored in online course platforms to be analysed automatically by the service.

Our service analyses online courses with respect to four key criteria: difficulty of content; variations in students’ abilities; students’ comprehension of course content; analysis of evaluation materials. An analytical report, which is sent to course creators, includes recommendations on how to improve a course’s content. Such reports and recommendations help creators to optimise difficulty levels and accessibility of course content for learners, enhance student involvement, make sure a course’s difficulty and student ability coincide, as well as improve the quality of evaluation materials of online courses (tests and peer-review materials).
 
When this service was being developed in 2017, around 270 online courses were analysed and updated. In addition, more than100 course creators, developers and methodological specialists took part in training sessions in data analysis at HSE, while future users of this services will have a chance to use a special electronic handbook (in Russian), which includes methodological materials and recommendations on how to upgrade and improve online courses. Since the 2018 autumn session, many courses have been improved in terms of content quality.

Once adjustments have been made to an online course, it is subject to automatic psychometric analysis and then receives a ‘mark of quality’, which means it has received the service’s approval. The priority project ‘Modern Digital Educational Environment in the Russian Federation’ is particularly focused on assessing the quality of online courses, available through ‘one stop shop’ resources, their multifaceted expert review and boosting the effectiveness of the learning process.

A multifaceted analysis of a course can boost competition between platforms and developers, encourage creators to improve the quality of their work, ensure access to verifiable information about online courses for educational institutions and students with respect to virtual academic mobility, as well as foster trust on the part of users and educational organisations in regards to eLearning in general.

HSE won the competition to develop the project ‘Development and Implementation of Methodologies and Instruments of Psychometrical Analysis of Online Courses’ (as a part of the priority project ‘Modern Digital Educational Environment in the Russian Federation’) in 2017.

This service was launched via the online.edu.ru portal in September 2018.

If you wish to receive consultations on course development by using psychometric data, please send a message to elearn@hse.ru RE: ‘converter for psychometric service’.