Abstract:

Aims:
The aims of this paper are to discuss the importance of student's Internet open data for his/her components of competence automatically assessment and how the innovative implementation of open data mining based on well-known technology affect student profile. This paper is based on the experience of funded research project conducted beyond the context of Russian Federation Ministry of Education and Science by academics in engineering higher education (#14.577.21.0135 dated 24.11.2014).

Background:
The challenges confronting students in higher education in today’s competitive environments have highlighted the importance for graduating students to be estimated independently. In ICT disciplines such as networking, programming and engineering etc., the significance of student activity in Internet experience together with other elements of real world practice built into the structured approach for the student's competences assessment in terms of new parameters developing such as their metacognitive and met creative features.

Design:
Qualitative indicators of competences based on open data mined from social networks and students’ activity behavior discussion.

Method:
The open data was collected in the period between February 2015 and May 2015 when one of the authors undertook an enrolled course for 3rd year of study students from the Bauman Moscow State Technical University to explore challenges and innovative pedagogic practices in the field of assessment.

Result:
The indicators of students Internet activity were compared with the results of well-known Belbin test and correlation observed.

Conclusion:
Quantitate parameters based on open data from social networks which could be used for students competence estimation are important for developing new structured approach to the students’ competence estimation. Hence, the new methods of estimation has an important role in preparing students for employment.

Keywords:

Competences, assessment, rubrics.