The aim of the article is the architecture of the computer-linguistic processing system of web-communities' educational content, which makes it possible to predict and form qualitative students' contingent of higher education institutions and to make management decisions based on the motivational intentions of potential entrants. The paper proposes the architecture and functional structure of the computer-linguistic processing system of educational communities' content for effective planning to provision of educational services based on procedures selection of potential entrants' motivational intentions and the quality of information content for educational communities. Chart data streams of complex information system automated processing of specialized educational content describes the operation of software agents working out of the content. The proposed software agents select relevant thematic educational discussions, identify motivational intentions of potential entrants, and formulate reaction of higher education institutions to selected postings to provide and create quality content for specialized online education communities. The results of the research are applied and can be used to effectively plan educational services and to create quality content for specialized educational communities, taking into account the motivational intentions of potential entrants.
Today, higher education institutions (HEI) are the focus to the provision of
educational services for higher education applicants. In general, the educational service is
interpreted as the end result of the planning process and providing these services.
That is why the developed information systems are oriented to support the main forms
of introduction of educational services in the educational process. However, the
absence of educational consumers makes it impossible to carry out the process of
providing these services of higher education institutions. HEIs need to undergo major
changes in their management approach [
Therefore, a prerequisite for the existence of HEI in the market of educational services is to predict the consumers’ contingent of these services. For this reason, the main task of this article is creation the architecture of the computer-linguistic processing system of the specialized communities’ educational content for the formation of a qualitative contingent of educational services consumers and for management decision-making by HEI. 2
ticular for the efficient operation of higher education institutions today.
well as instructions and rules for the development, presentation and understanding of
information systems architecture is considered in [
systems, which simplifies the technology of integrated automation and content
management described in [
processing system of the specialized communities’ educational content for the purpose of predicting and create a high-quality contingent of university students and for making management decisions taking into account the motivational intentions of potential entrants.
content for planning the provision of educational services of HEI [
3
Architecture of Information System for ComputerLinguistic Processing of Educational Content for
Predicting Higher Education Students
Prediction and formation of high-quality students’ contingent of higher education
institution is directly connected with consumers of educational services [
educational information content, which takes into account the motivational intentions of educational services consumers, generates appropriate reactions from them by HEI and conducts constant monitoring and analysis of the quality of information content of educational communities is presented in Fig. 1.
At the first level, work is done with information content within the local information system, which provides: formation of the necessary elements of educational information content; identification of indicative features; monitoring the quality of the content and the vocabulary of motivational intentions; specifying selection options relevant to the entry campaign period, thematic discussions and posts.
At the second level, there are software agents of information processing which are intended for: selection of relevant educational discussions; keeping thematic posts; detecting users' motivational intent in posts; matching the keywords of the entry campaign period with the identified motivational intentions; retention of motivated intentions; dictionary of the motivational intentions database formation. selection of HEI reactions to identified motivational intentions At the third level, external information services and resources are used to process the information content: Web-resource search services (search engines); open Web-resources that serve as sources of educational information for content. 4
Functional structure of the automatic content processing system for specialized educational webcommunities Functional structure of the automatic content processing system of specialized educational communities is based on the architecture of a complex information system of automated computer-linguistic information content processing.
The context diagram of a complex information system for automatic processing of specialized educational communities information content is presented in Fig. 2.
keyword formation in relation to the periods of the entry campaign; checking the relevance of the thematic discussion; defining topical thematic discussions regarding the entry campaign periods.
Agent of motivational intention selection based on the motivational intention
selection algorithm [
Considering the algorithm of selection of motivational intentions from thematic posts of specialized web-communities, Processing of Motivational Intentions contains the following functions: setting indicative features; reviewing educational content; assessment of the importance of the identified motivational intentions; export of motivational intentions.
The HEI reactions, which are the result of the algorithm of formation of the dictionary
of motivational intentions concerning a certain period of the entry campaign [
Quality monitoring of educational content is based on the indicators of quality of
educational content, based on the criteria [
Quality monitoring of educational content contains the following features: analysis of plural keywords; analysis of plural motivational intentions; analysis of the relevance content; analysis of the assistance level of HEI reactions; analysis of the deficiencies. 5
Since the architecture of the computer-linguistic processing system of webcommunities’ educational content takes into account motivational intentions consumers of educational services and generates appropriate reactions from the HEI, informative indicators of this system are the speed of HEI reactions in the process of communicative activity and analysis of enrollment of potential entrants.
According to the results of the analysis of educational web-forum for entrants communication activity and relevant thematic groups in social networks of Lviv Polytechnic National University, the reaction time indicator decreased by 20% - 40% depending on the period of the entry campaign (Fig. 4), and, on average, 30% for the 2016/2019 introductory campaigns (Fig. 5). 10 n o i t a 8 c e r f o im6 e T 4 2 0 60 50 ino 40 t c rae 30 f eo 20 m i T 10 0
2016/2017 2017/2018 2018/2019 The analysis of the information system work shows the positive dynamics of change in the number of enrolled students for 2016/2019 to the Lviv Polytechnic National University, by an average of 3%.
Therefore, this article develops the architecture of the computer-linguistic processing system of web-communities’ educational content to plan effectively the provision of educational services and to make management decisions by the HEI during the entry campaign based on the procedures for selecting motivational intentions of potential entrants indicators of the quality of the content of educational web-communities , which in practice allowed to establish a system of maintaining the relevance and correctness of educational information the content of educational web-communities and official web-resources of higher education institutions with the ability to properly support the quality of information content. The analysis of the results of the communication activities of the consumers of educational services in specialized webcommunities showed a decrease in the time for a response by HEI to the identified motivational intentions of potential entrants, as well as the positive dynamics of actually enrolled entrance in relation to the entry campaigns in recent years for the HEI.