Аңдатпа
The article gives an overview of Astana IT University's (AITU) experience in using IT tools in sociological study to determine the social profile of an AITU student based on the data of sociological surveys. The purpose of the study is aimed at summarizing the experience how IT tools can be used in gathering and processing data and survey result analysis. In this article the features of various software and hardware tools, the process of applying information technologies at different stages of sociological research that affect the effectiveness of sociological research are discussed. The aim of the study is to determine the effectiveness of various software (from word processors to statistical packages) and hardware (from cell phones to modern computers) tools at different stages of conducting a sociological survey. The most common problems the sociologist may run into when looking for a survey tool are technical, design, legal, and expertise one as well as problems with length, survey fatigue and interpreting respondents’ mood. It is highly likely in the case of long, confusing, or complicated surveys the questions can be skipped or responded mindlessly by respondents and be resulting in confusing results and inaccurate responses. Long surveys more than 10-15 minutes can course respondents mind fatigue which can lead and result the dishonest responses and survey dropout. The respondents can be tired with especially open-ended questions which require careful and deep thinking. The problem of selecting adaptive tools for conducting sociological research for obtaining the most reliable and high-quality information lies in the lack of a universal IT tool for implementing sociological research at its all stages. The model of the university efficiency promotion for sustainable development is presented to compare the progress of university efficiency in learner recruiting, hiring of local and international staff, the number of staff participated in the program of professional development, the number of laboratories and IT technologies, the range of national and international partners, etc. Stages of a Data-driven decision-making approach in university efficiency promotion are presented in detail.