Advantages of Using Self-Organizing Maps to Analyse Student Evaluations of Teaching

Self‐organizing maps and Bayesian networks in organizational modelling: A case study in innovation projects management

“…f. According to Forradellas et al (2012), the advantage of SOM application in process analysis is the grouping of individuals in terms of the uniformity of their typical characteristics (clustering), reducing the size of the problem to a two-dimensional map while maintaining all the information about the behaviour of the variables. g. SOM application are found, for example, in meteorology (Hewitson & Crane, 2002), education and teaching (Forradellas et al, 2012), financial operations (Deboeck, 1998), ecology (Postolache et al, 2005), medicine (Fernandez & Balzarini, 2007) and geography (Jiang & Harrie, 2004.) h. Yin (2008) mentions that SOM is a fundamental pattern recognition process, in which intrinsic inter-and intra-pattern relationships among the stimuli and responses are learnt without the presence of a potentially biased or subjective external influence.…”

“…e. BN are used in many different areas, like for example, sentiment analysis (Ruz et al, 2020), interpretation of evidences in forensic science (trials) (Smit et al, 2016), medicine (Zhou et al, 2020), environmental modelling (Krueger et al, 2012), marketing and financial operations (Cooper, 2000), psychopathology diagnosis (McNally, 2016) and human reliability analysis, what is an aspect of risk assessment concerned with systematically identifying and analysing the causes and consequences of human decisions and actions (Groth & Mosleh, 2012). f. According to Forradellas et al (2012), the advantage of SOM application in process analysis is the grouping of individuals in terms of the uniformity of their typical characteristics (clustering), reducing the size of the problem to a two-dimensional map while maintaining all the information about the behaviour of the variables. g. SOM application are found, for example, in meteorology (Hewitson & Crane, 2002), education and teaching (Forradellas et al, 2012), financial operations (Deboeck, 1998), ecology (Postolache et al, 2005), medicine (Fernandez & Balzarini, 2007) and geography (Jiang & Harrie, 2004.)…”

“…At the same time, sensitivity analyses can demonstrate that a strongly held belief does or does not impact on a particular decision, why decision alternatives vary, helping to find out which sources of uncertainty (variables) really impact on the decision and the importance of reducing uncertainty in particular parameters. BN are used in many different areas, like for example, sentiment analysis (Ruz et al, 2020), interpretation of evidences in forensic science (trials) (Smit et al, 2016), medicine (Zhou et al, 2020), environmental modelling (Krueger et al, 2012), marketing and financial operations (Cooper, 2000), psychopathology diagnosis (McNally, 2016) and human reliability analysis, what is an aspect of risk assessment concerned with systematically identifying and analysing the causes and consequences of human decisions and actions (Groth & Mosleh, 2012). According to Forradellas et al (2012), the advantage of SOM application in process analysis is the grouping of individuals in terms of the uniformity of their typical characteristics (clustering), reducing the size of the problem to a two‐dimensional map while maintaining all the information about the behaviour of the variables. SOM application are found, for example, in meteorology (Hewitson & Crane, 2002), education and teaching (Forradellas et al, 2012), financial operations (Deboeck, 1998), ecology (Postolache et al, 2005), medicine (Fernandez & Balzarini, 2007) and geography (Jiang & Harrie, 2004. ) Yin (2008) mentions that SOM is a fundamental pattern recognition process, in which intrinsic inter‐ and intra‐pattern relationships among the stimuli and responses are learnt without the presence of a potentially biased or subjective external influence.…”

A Two-stage Intelligent Model for Personal Credit Loans Default Prediction by Using SOM and PHM

“…For example, it was used to find out the relationship between users and agents in telecommunications (Chien, 2006); to segment travelers (li et al, 2010); to analyze students' evaluations of teaching (Sorrosal Forradellas et al, 2012); to know purchase intention in e-commerce (Hong & Kim, 2012); to improve the stock trading system (Pham et al, 2014), and in the transportation field (Yang et al, 2014) etc. However, it seems to rarely be applied in segmenting the borrowers of personal credit loans.…”