scholarly journals Usage of Machine Learning for Strategic Decision Making at Higher Educational Institutions

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 75007-75017 ◽  
Author(s):  
Yuri Nieto ◽  
Vicente Gacia-Diaz ◽  
Carlos Montenegro ◽  
Claudio Camilo Gonzalez ◽  
Ruben Gonzalez Crespo
2018 ◽  
Vol 23 (12) ◽  
pp. 4145-4153 ◽  
Author(s):  
Yuri Nieto ◽  
Vicente García-Díaz ◽  
Carlos Montenegro ◽  
Rubén González Crespo

2020 ◽  
pp. 227853372094203
Author(s):  
Shefali Srivastava ◽  
Gyan Prakash ◽  
Ritika Gauba

This article aims to identify teachers’ accountability in the context of higher educational institutions (HEIs). Most of the literature has used student-oriented outcomes as basic building blocks of accountability. This article contributes to the literature by gauging teachers’ perceptions in conceptualising accountability in the HEIs. Indicators of accountability have been identified from the literature. Decision-making trial and evaluation laboratory (DEMATEL) method has been used to explore the nature of interrelationships among these indicators. Results reveal that accountability indicators have varying impact and some of these indicators have cause and effect type of relationship among them. The article underscores the role of performance-based accountability system (PBAS) which will help in assessing and evaluating teachers in the HEIs. It is argued that accountability strengthens the autopoietic nature of the HEIs and enables underlying knowledge generation and dissemination processes. Using accountability indicators, teachers can self-assess their performance and adapt to evolving needs of students, businesses, and societal stakeholders. The relationships among accountability indicators can be used by policymakers to steer the HEIs.


2018 ◽  
Vol 7 (4.7) ◽  
pp. 283
Author(s):  
Batyrkhan Kuzenbaev ◽  
Rosamgul Niyazova ◽  
Ayzhan Kuzenbaevа

The present paper considers the development of learning process management expert system in higher educational institutions, based on the ontological approach. The purpose of research is an improve the effectiveness of decision making during the management of learning processes by using intelligent management methods and modern approaches to knowledge modelling. The methodology of solving the set task is based on models and methods of knowledge representation usage, the artificial intelligence theory, expert methods of decision-making and general theoretical principles of the control theory, and the theory of decision-making. Authors conducted a qualitative analysis of the domain knowledge, which allowed distinguishing and formalizing main concepts and relations between them. Authors suggested a methodological approach to the construction of the learning process management system, which allows implementing knowledge-based approaches to the development of information systems in the domain knowledge of learning process management. Authors also developed the structure and formal description of the ontology of the learning process in higher educational institutions, which allows reusing the suggested solutions. Research results were implemented in the expert information system; they can be used in practice in learning process management in higher educational institutions. 


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