This book on Philosophy of Science includes a comprehensive discussion of ontology, epistemology, and axiology of science in the constellation of various other knowledge, as well as the development of scientific knowledge holistically contained in each module in this course. These three things are branches of philosophy which are very useful for students of Teacher Training and Education in mediating the learning and learning process so that the essence of Philosophy of Science can then be implemented within the scope of (...) professionalism in particular and society in general and the challenges of the industrial era 4.0 in the 20th century 21 The discussion on ontology is focused on elements of empirical reality (empericism) such as facts, data, and information without releasing it from rational reality (rationalism), and its position in scientific activities. The epistemology of science is focused on the scientific method and its operationalization in research methodology. The axiology of science discusses the values ​​associated with scientific activities and their uses, both internally, externally, and socially. (shrink)

Verbal learning and memory summaries of older adults have usually been used to describe neuropsychiatric complaints. Bayesian hierarchical models are modern and appropriate approaches for predicting repeated measures data where information exchangeability is considered and a violation of the independence assumption in classical statistics. Such models are complex models for clustered data that account for distributions of hyper-parameters for fixed-term parameters in Bayesian computations. Repeated measures are inherently clustered and typically occur in clinical trials, education, cognitive psychology, and treatment follow-up. (...) The Hopkins Verbal Learning Test is a general verbal knowledge and memory assessment administered repeatedly as part of a neurophysiological experiment to examine an individual’s performance outcomes at different time points. Multiple trial-based scores of verbal learning and memory tests were considered as an outcome measurement. In this article, we attempted to evaluate the predicting effect of individual characteristics in considering within and between-group variations by fitting various Bayesian hierarchical models via the hybrid Hamiltonian Monte Carlo under the Bayesian Regression Models using ‘Stan’ package of R. Comparisons of the fitted models were done using leave-one-out information criteria, Widely applicable information criterion, and K-fold cross-validation methods. The full hierarchical model with varying intercepts and slopes had the best predictive performance for verbal learning tests [from the Advanced Cognitive Training for Independent and Vital Elderly study dataset] using the hybrid Hamiltonian-Markov Chain Monte Carlo approach. (shrink)