Employment of Business Intelligence Methods for Competences Evaluation in Business Games
This research involves justification of Business Intelligence methods usage in order to analyze the outcome of computer-based business games. In such games, it is necessary to evaluate efficiency of player’s actions that is associated with the development of professional competences acquired by participants as well as the game effectiveness in regard to the qualitative development of the specified competences. Computer-based business games development and conduction is performed within the source environment of “Competence-based Business Games Studio”. The challenge of player’s competences evaluation and the game effectiveness is tackled by Business Intelligence methods implementation into analysis subsystem of “Competence-based Business Games Studio”. The analysis of participants’ actions allows getting player’s behavior characterization based on the information about the results of all games that the player participated. In order to guide the course of the business game, analysis is conducted on the basis of all players’ actions during all games and the reference models of the games. The paper defines data source subsystems and the main measurements; it also considers the process of data warehouse development and the requirements to the output of analysis subsystem
The article considers the conceptual approach of creating a set of development tools for active learning methods in a form of competency-based business-game studio. Competence-based business game is an information system, which aims to give a certain level of professional competence while implementing scenarios that are determined by business-process models of the domain. The structure of the gaming studio, suggests a set-theoretic representation of business-game design process. Business game can be represented as a cybernetic system with feedback, which contains both the object of management and the management system. The game is implemented as control and operating machines accordingly. For the construction of the operational machine it is proposed to use a knowledge model in the form of ontology. To represent the automate model it is proposed to use a model of managing business processes of an enterprise. A block diagram of the business-game design process is provided.
This paper describes the experience of the application of the design approach which is used in the HSE - Nizhny Novgorod in the teaching of accounting (financial) accounting, auditing, economic analysis. The stages of a complex project, as benefits of this approach and the problems that arise.
This book constitutes a collection of selected contributions from the 11th International Conference on Perspectives in Business Informatics Research, BIR 2012, held in Nizhny Novgorod, Russia, in September 2012.
The 15 papers presented in this volume were carefully reviewed and selected from 36 submissions. They have been organized in topical sections on: knowledge management and the Semantic Web; business and information systems development; business, people, and systems interoperability; and business intelligence.
To large organizations, business intelligence (BI) promises the capability of collecting and analyzing internal and external data to generate knowledge and value, thus providing decision support at the strategic, tactical, and operational levels. BI is now impacted by the “Big Data” phenomena and the evolution of society and users. In particular, BI applications must cope with additional heterogeneous (often Web-based) sources, e.g., from social networks, blogs, competitors’, suppliers’, or distributors’ data, governmental or NGO-based analysis and papers, or from research publications. In addition, they must be able to provide their results also on mobile devices, taking into account location-based or time-based environmental data. The lectures held at the Third European Business Intelligence Summer School (eBISS), which are presented here in an extended and refined format, cover not only established BI and BPM technologies, but extend into innovative aspects that are important in this new environment and for novel applications, e.g., pattern and process mining, business semantics, Linked Open Data, and large-scale data management and analysis. Combining papers by leading researchers in the field, this volume equips the reader with the state-of-the-art background necessary for creating the future of BI. It also provides the reader with an excellent basis and many pointers for further research in this growing field.
Successful online learning if we look outside the didactics but in the field of personal development, from the anthropological bases, is in learner’s identification as an active subject of the learning process. Activities that online learners perform correlate with the characteristics of the subjectness that researchers revealed: spotting one’s own gaps in the educational environment and one’s educational needs, satisfying them and enhancing one’s competence by means of online learning (ability to change the environment and oneself inside that, reflexive way of life, realizing the principle of development), searching, selecting and studying online courses on one’s own, supported first and foremost by the intrinsic motivation (initiative), ability to plan and analyze one’s activity or inaction in the course, managing the requirements and the deadlines of the assignments, as well as readiness to accept the consequences of one’s choice (responsibility). Therefore, successful online learners (those who study on their own, cope with the tasks in time and in a proper way, achieve expected results) are characterized with such a subjectness that is based on a set of general-cultural and general-professional competencies that should be formed. To define the set of competencies, which an online learner needs to become successful and to study learners’ attitude to them, we have done a competency-based test (self-assessment questionnaire) in September - November 2017. The respondents were 2060 learners from TSU online courses offered on three e-learning platforms (population is 80938). Learners responded that the following general-cultural competencies are of much help for them in online learning: readiness to self-development, self-realization and using one’s own creativity (69,7%), ability to organize and educate oneself (53,3%), ability to acquire new scientific and professional knowledge using modern educational and informational technologies (62,3%), as well as ability to imply means and methods of learning and self-control over one’s intellectual development, increasing one’s cultural level and professional competence (50,2%). Among general-professional competencies the learners replied that the most useful competencies for online learning are computer skills for receiving, processing and managing information (79,5%), ability to work with the main retrieval query systems (60,2%), ability to search for scientific information, perform its critical analysis, to set research objectives and choosing appropriate methods and technologies to achieve them (59,3%), ability to critically analyze the learning process and training materials from the point of view of their effectiveness (54%) and ability to use polite manners in oral and written speech (21,9%). At the same time, the respondents define general-cultural competencies as more significant. Therefore, the survey results proved our idea that successful online learning requires firstly, a set of general-cultural competences (those which are connected to the learner’s personal development and his/ her subjectness in the learning process) and secondly, a set of general-professional competencies to be formed. This led us to the idea that assessing learner’s level of the general-cultural competences we can predict his/ her future success in taking online courses.
This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables