The radical exemplar model resonates with work on perceptual classification and categorization highlighting the role of exemplars in memory representations. Further development of the model requires acknowledgment of both the fleeting and fragile nature of perceptual representations and the gist-based, good-enough quality of long-term memory…

Modeling projects in differential equations and engineering courses create an authentic activity and an opportunity to attain the holy grail of "deeper" learning. However, what do we mean by "deeper" learning and how do we create an environment that encourages that? This article describes a proposal and case study in using…

Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Learners style is grouped into four types mainly; Visual, auditory, kinesthetic and Read/Write. Each type of learners learns primarily through one of the main receiving senses, visual, listening, or by doing. Learner style has an effect on the learning process and learner's achievement. It is better to select suitable learning tool for the learner…

Nondichotomous response models have been of greater interest in recent years due to the increasing use of different scoring methods and various performance measures. As an important alternative to dichotomous scoring, the use of continuous response formats has been found in the literature. To assess finer-grained skills or attributes and to…

Information integration is great for military operations because the range of pertinent information sources is significantly distinct and dynamic. This article develops an intelligent knowledge treasure comprised of military resource ontology and procedures, as a learning model for better interoperability of heterogeneous resources of the Indian…

Algorithms for approximate Bayesian inference, such as those based on sampling (i.e., Monte Carlo methods), provide a natural source of models of how people may deal with uncertainty with limited cognitive resources. Here, we consider the idea that individual differences in working memory capacity (WMC) may be usefully modeled in terms of the…

The purpose of this study was to apply Fautley's model-- [Faultley, Martin. 2005. "A New Model of the Group Composing Process of Lower Secondary School Students." "Music Education Research" 7 (1): 39-57. doi:10.1080/14613800500042109]of the group composing process to the analysis of a collaborative composing project in a lower…

In this study, it was aimed to investigate the impact of different missing data handling methods on DINA model parameter estimation and classification accuracy. In the study, simulated data were used and the data were generated by manipulating the number of items and sample size. In the generated data, two different missing data mechanisms…

This text comments on the Keynote article 'Microvariation in multilingual situations: The importance of property-by-property acquisition' by Marit Westergaard, who argues for Full Transfer Potential within the Linguistic Proximity Model in third language (L3) acquisition. The commentary points at some theoretical and methodological issues related…

The objectives of this paper were to 1) study the learning model of the smart crematorium system, 2) create a learning manual on smart cremation management, and 3) promote the development of learning for undertakers to use the smart crematorium. This was mixed method research with qualitative research and action research as parts of the conduct of…

The study examines language dimensions of mathematical word problems and the classification of mathematical word problems according to these dimensions with unsupervised machine learning (ML) techniques. Previous research suggests that the language dimensions are important for mathematical word problems because it has an influence on the…

Researchers commonly estimate the prevalence of nativelikeness among second-language learners by assessing how many of them perform similarly to a sample of native speakers on one or several linguistic tasks. Even when the native (L1) samples and second-language (L2) samples are comparable in terms of age, socio-economic status, educational…

Many studies have demonstrated that we can identify a familiar face on an image much better than an unfamiliar one, especially when various degradations or changes (e.g., image distortions or blurring, new illuminations) have been applied, but few have asked how different types of facial information from familiar faces are stored in memory. Here…