Project Director
- Vitaly Viktorovich Kashpur. Project executor from the Institute of Distance Education—Artyom Viktorovich Feshchenko.
Pursuance of state education policy in the area of identification and support of talents, vocational guidance, and education customization forms a request for analysis of factors affecting educational achievements of students. However, the available analytics is limited to assessment of dependence of performance on personal (related to the student) and institutional (related to the university) factors. The data source for such analytics is the data generated within LMS systems of universities, data of psychological testing, as well as educational and social and economic statistics. In this case, a huge amount of data enabling recording and assessment of student performance — the data generated on the Internet and its key locus for contemporary youth — social media, is disregarded. Current attempts to use this data for educational process customization are limited to application of data from LMS systems of universities, information on the education progress to build a trajectory within the course. Meanwhile, social media penetration in daily and professional life of modern society makes the studies of methods and tools of retrieval and analysis of social media user data — digital footprints — highly topical. Studying the digital footprint of a person enables analysis and modeling of their physiological, psychological and cognitive features and allows for the use of such a model for forecasting, programming and management of the educational trajectory. In our case, it is important that the digital footprint of a person on social media opens a fundamentally new opportunity for assessment and analysis of educational achievements of students — it enables assessment of their non-formal and informal educational trajectories and achievement previously invisible for the state and education establishments. Besides, the structure and content of human activity on the Internet is an important component of the person’s digital footprint, which forms the necessity of separate study of its impact on educational trajectories and achievements.
Thus, the research relevance is determined by the demand for its results for development of complex assessment methodology and forecasting of educational achievements under conditions of development of customized education in the digital era.
The purpose of the proposed project
Analysis of impact of structural and content characteristics of Internet activities of high school seniors and university students on their educational achievements.
Academic novelty of the proposed approach consists of using of big open user data and machine learning algorithms for assessment of impact of Internet activity on educational achievements. Deep analysis of structural and content features of such activities will enable to clearly understand the nature and genesis of personal educational environments of young people.
As a key result, it is planned to create a complex model of assessment of impact of structural and content features of Internet activities on educational achievements of a student based on the data on formal and non-formal education and the digital footprint on social media. Apart from gaining new knowledge of impact of Internet activities on educational achievements, creation of such a model will enable using it as the basis for development of advanced technologies in education.
Another important result will be the development of a model of forecasting potential educational achievements of students based on the analysis of the digital footprint data, using machine learning technologies. This model can be used as a talent search tool, as well as a tool for tutor work at universities.
The following is planned as applied project results
- Based on a complex model of assessment of impact of Internet activity and educational achievements, typology of forms of such impact in respect to various behavior patterns of students will be developed, which will enable updating characteristics of personal educational environments of young people and using them in the future design of educational programs and events.
- Analysis of structural and content features of Internet activities based on a large empirical material (more than 30,000 people) will enable mapping out of the educational segment of the Internet space, updating perception of specifics of informal education, distinguishing most influencing communities and content sources. An interactive map as a product.
- A recommendation engine for teachers, mentors and tutors for assessment of probability of achieving high results in educational programs on the basis of analysis of student’s open user data in VKontakte. This service will be created on the base of the opendata.university platform.