About this paper

Appears in:
Pages: 4038-4045
Publication year: 2017
ISBN: 978-84-697-3777-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2017.1869

Conference name: 9th International Conference on Education and New Learning Technologies
Dates: 3-5 July, 2017
Location: Barcelona, Spain

ANALYSIS OF INDICATORS OF UNIVERSITY’S SCIENTIFIC ACTIVITY

O. Zyateva, E. Pitukhin, I. Peshkova, M. Bezborodov

Petrozavodsk State University (RUSSIAN FEDERATION)
At present, one of the important criteria for assessing the overall effectiveness of a university refers to indicators of its scientific activity. The indicators do not only include the amount of funds received by a university for research and development or the number of its grants or patents. They also comprise a number of scientific metrics which enable evaluating the organization's performance in scientific areas. The indicators are different in nature, but they all depend in one way or another on the faculty and scientific workers (academic staff) of the organization, since it is the academic staff that exerts a direct impact on the indicators’ values.
This article focuses on the theoretical approach and practical solutions to the problem of assessing and forecasting the main indicators of scientific activity related to the publication activity of a university as a whole, using the example of Petrozavodsk State University. Data on the main indicators characterizing the scientific activity of the university staff were collected and processed: namely, the indicators of the staff publication activity and the distribution of their publications by years for the period 2000-2015, available in the bibliographic database of the Russian Scientific Citation Index (RSCI).
To determine the existence of relationships between different indicators, Data Mining tools were used. These technologies allow you to find in large volumes of data hidden and nontrivial patterns that are not detectable at first sight. The research used several methods of analysis, such as the analysis of key influence factors, forecast, scenario analysis, category search (clustering), and so on. The proposed tools will allow higher education institutions to carry out self-analysis.
Such knowledge can be useful for university managers when making managerial decisions related to improving the position of their organization in a number of indicators of scientific activity. Using the opportunity to predict and control the values of these indicators will improve the image and international recognition not only of publication authors, but also of the organization as a whole.
@InProceedings{ZYATEVA2017ANA,
author = {Zyateva, O. and Pitukhin, E. and Peshkova, I. and Bezborodov, M.},
title = {ANALYSIS OF INDICATORS OF UNIVERSITY’S SCIENTIFIC ACTIVITY},
series = {9th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN17 Proceedings},
isbn = {978-84-697-3777-4},
issn = {2340-1117},
doi = {10.21125/edulearn.2017.1869},
url = {http://dx.doi.org/10.21125/edulearn.2017.1869},
publisher = {IATED},
location = {Barcelona, Spain},
month = {3-5 July, 2017},
year = {2017},
pages = {4038-4045}}
TY - CONF
AU - O. Zyateva AU - E. Pitukhin AU - I. Peshkova AU - M. Bezborodov
TI - ANALYSIS OF INDICATORS OF UNIVERSITY’S SCIENTIFIC ACTIVITY
SN - 978-84-697-3777-4/2340-1117
DO - 10.21125/edulearn.2017.1869
PY - 2017
Y1 - 3-5 July, 2017
CI - Barcelona, Spain
JO - 9th International Conference on Education and New Learning Technologies
JA - EDULEARN17 Proceedings
SP - 4038
EP - 4045
ER -
O. Zyateva, E. Pitukhin, I. Peshkova, M. Bezborodov (2017) ANALYSIS OF INDICATORS OF UNIVERSITY’S SCIENTIFIC ACTIVITY, EDULEARN17 Proceedings, pp. 4038-4045.
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