Causal maps in the analysis and unsupervised assessment of the development of expert knowledge: Quantification of the learning effects for knowledge management purposes

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作   者：

Mahinda Mailagaha Kumbure;  Anssi Tarkiainen;  Jan Stoklasa;  Pasi Luukka;  Ari Jantunen; 

作者机构：

Czech Republic;  77900 Olomouc;  Business School;  53850 Lappeenranta;  Faculty of Arts;  LUT University;  Palacky University Olomouc;  Krizkovskeho 12;  Department of Economic and Managerial Studies;  Yliopistonkatu 34;  Finland; 

关键词：

Unsupervised assessment;  fsQCA;  Expert system;  Cognitive maps;  Expert knowledge;  Knowledge enhancement; 

期刊名称：

Expert Systems with Application

i s s n：

0957-4174

年卷期：

2024 年 236 卷 Feb. 期

页   码：

121232.1-121232.22

页   码：

摘   要：

This study proposes an application of cognitive maps in the representation of cognitive structures of the experts and assessment of their development/modification as a result of a (computer or expert system-assisted) learning process. It strives to identify information needed for the guidance of the process of creation and management of expert knowledge by formal modeling tools. Changes in experts' cognitive structures are assumed to stem from individual and collaborative (group-level) learning. The novel approach to assessing the outcomes of learning reflected as changes in the cognitive structures of experts or groups of experts, modeled by cognitive maps, does not assume any correct or desired outcome of the learning process to be known in advance. Instead, it identifies and analyzes the changes in (or robustness of) the constituents of the cognitive maps from different points of view and allows for quantifying and visualizing the actual effect of the learning. The proposed methodology can identify changes in cognitive diversity, causal structures in terms of causal relations and concepts, and the perceived importance of strategic issues over the learning period. It can also detect which cause-effect relationships have appeared/disappeared considering the pre-/post-mapping design. Thus, it provides an exploratory account on the changes in the cognitive structures of the expert(s) as a result of learning. The applicability of the proposed methods is illustrated in the assessment of the learning outcomes of a group of 71 graduate students who participated in an eight-week business simulation task. The results of the empirical analysis confirm the viability of the proposed methodology and indicate that the students' understanding of the utilized concepts and associated relationships in the decision-making process improved throughout the learning activity, ultimately showing that the course learning has considerably improved students' perception and knowledge. Based on the results, it can be concluded that the proposed approach has the potential to be effective in assessing learning outcomes in teaching-learning activities.