Analysis of structural shifts in students’ behavioral patterns during COVID-19
This study uses survey data on hypothetical situations with the aim of measuring risk aversion in different (economical) situations. It was conducted at two different points in time: April 2020 (early Covid pandemic) and January 2021 (later Covid pandemic). Viscovery SOMine is used to cluster the results and show that certain behavioral shifts can be identified.
Examining the effect of time constraint on the online mastery learning approach towards improving postgraduate students' achievement
The dependence of final-examination performance of postgraduate finance students on the setup of self-assessment tests is analyzed. The explorative Viscovery SOMine model shows that the introduction of time constraints coincides with better performance in the final examination.
A study of children's musical preference: a data mining approach
This article studies the musical activity preferences of 228 young children (aged 4–5 years) from Hong Kong, China, and Adelaide City, Australia. Viscovery SOMine is used to find connections between country of residence and preferences for musical activities, such as singing, playing instruments, dancing and listening to music.
Features, objects, and other things: ontological distinctions in the geographic domain
Response of 263 subjects giving examples for one of five geographic categories (geographic features, geographic objects, geographic concepts, something geographic, and something that could be portrayed on a map) are analyzed. The frequencies of various responses are significantly different, indicating that the basic ontological terms feature, object, etc., are not interchangeable but carry different meanings when combined with adjectives indicating geographic or mappable aspects. Viscovery SOMine is used for training and initial labeling of neurons, and ArcView is used for processing base map configurations and two-dimensional interpolation.