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Modelling Subject Domain Causality for Learning Content Renewal
Volume 30, Issue 3 (2019), pp. 455–480
Pub. online: 1 January 2019      Type: Research Article      Open accessOpen Access
Received
1 January 2019
Accepted
1 June 2019
Published
1 January 2019

Abstract

The paper deals with the causality driven modelling method applied for the domain deep knowledge elicitation. This method is suitable for discovering causal relationships in domains that are characterized by internal circular causality, e.g. control and management, regulatory processes, self-regulation and renewal. Such domains are organizational systems (i.e. enterprise) or cyber-social systems, also biological systems, ecological systems, and other complex systems. Subject domain may be of different nature: real-world activities or documented content. A causality driven approach is applied here for the learning content analysis and normalization of the knowledge structures. This method was used in the field of education, and a case study of learning content renewal is provided. The domain here is a real world area – a learning content is about. The paper is on how to align the existing learning content and current (new) knowledge of the domain using the same causality driven viewpoint and the described models (frameworks). Two levels of the domain causal modelling are obtained. The first level is the discovery of the causality of the domain using the Management Transaction (MT) framework. Secondly, a deep knowledge structure of MT is revealed through a more detailed framework called the Elementary Management Cycle (EMC). The algorithms for updating the LO content in two steps are presented. Traceability matrix indicates the mismatch of the LO content (old knowledge) and new domain knowledge. Classification of the content discrepancies and an example of the study program content analysis is presented. The main outcome of the causality driven modelling approach is the effectiveness of discovering the deep knowledge when the relevant domain causality frameworks are applicable.

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Biographies

Gudas Saulius
saulius.gudas@mii.vu.lt

S. Gudas, PhD, is a full professor at the Institute of Data Science and Digital Technologies, Faculty of Mathematics and Informatics, Vilnius University, Lithuania. 2008–2013, Dean of VU KHF. Education: in 1969–1974, studied at Kaunas University of Technology, Lithuania; in 1982 defended the PhD dissertation on the topic “Synthesis of Algorithmic Structure of Information Systems for Manufacturing Objects”; in 2005, passed the doctor habilitation procedure on the topic “Modelling of Knowledge Based Information Systems Engineering Processes”. Research directions are as follows: knowledge-based enterprise modelling, information systems theory, knowledge-based information system engineering. He is the author of the monograph on foundations of the information systems engineering theory and co-author of more than 165 research publications.

Tekutov Jurij
jurij.tekutov@yahoo.com

J. Tekutov received the PhD degree in computer science (informatics) at the Vilnius University in 2013, Lithuania. He is a lecturer at the Department of Informatics and Statistics at Klaipeda University; associate professor at the Department of Information Technologies at Klaipeda State University of Applied Sciences and Lithuania Business University of Applied Sciences. He is a member of council of the Faculty of Marine Technologies and Natural Sciences of KU. In 2008 he took part in project “Modernisation, development and assurance of mobility of Master study programmes in information technology area” implementation. In 2009 he attended 10th extended workshop/summer school of NordForsk network “Methodologies for Interactive Networked Enterprises – MINE”. 2012–2015 – researcher of project “Lithuanian Maritime Sector’s Technologies and Environment Research Development”. His main research interests include study process control knowledge based models. He is the author of more than 15 publications, several e-learning materials in the virtual environment, participated in several international and republican scientific conferences of young scientists and the methodological-training camps.

Butleris Rimantas
rimantas.butleris@ktu.lt

R. Butleris, PhD, is a full professor and director of Center of Information Systems Design Technologies at the Faculty of Informatics of Kaunas University of Technology (Lithuania), and professor at Kaunas Faculty of Humanities, Vilnius University (Lithuania). Prof. Butleris is the co-author and author of over 130 scientific publications. He was a general chairman of international conferences: BIR 2006, I3E’2011, ICIST 2012; chairman of organizing committees of international conferences: IT’2008, IT’2009, IT’2010, IT’2011; a member of program committees of over 30 international conferences. During the past 10 years, Prof. Butleris coordinated or managed over 15 national or International research and development projects.

Denisovas Vitalijus
vitalijus.denisovas@ku.lt

V. Denisovas, PhD in technical sciences, is a professor at the Department of Informatics and Statistics, Faculty of Marine Technologies and Natural Sciences, Klaipeda University, Lithuania. 2013–2014, Dean of the Faculty of Natural Sciences and Mathematics of KU. He is a member of the working group of development of new study cycles and informatics study area regulations, established by the Lithuanian Centre for Quality Assessment in Higher Education; member of the Senate of KU; member council of the Marine Technologies and Natural Sciences of KU; member of the International Council on Systems Engineering, INCOSE; member of the Association of the Lithuanian Informatics Teachers; also member of Academic Council of Lithuania Business University of Applied Sciences. He is the author of about 20 books (textbooks) and more than 70 prestigious scientific publications on mathematical and simulation modelling, software implementation of models, their identification algorithms and modelling systems (simulators), data mining methods as well as on the various e-learning methods.


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© 2019 Vilnius University
Open access article under the CC BY license.

Keywords
enterprise domain causal knowledge circular causality domain causality management transaction learning content

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