Third language (L3) lexical acquisition is still underexplored. In this article I overview theoretical and empirical evidence on L3 lexical acquisition and the role of cross-linguistic influence (CLI) in learning L3 words. I explain the mechanism of CLI as resulting from language co-activation in the multilingual learner's/user's mind.…

Automated image analysis has received increasing attention in social scientific research, yet existing scholarship has mostly covered the application of supervised learning to classify images into predefined categories. This study focuses on the task of unsupervised image clustering, which aims to automatically discover categories from unlabelled…

We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category…

Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…

Despite much research, the role of the medial temporal lobes (MTL) in category learning is unclear. Two unstructured categorization experiments explored conditions that might recruit MTL category learning and memory systems--namely, whether the stimulus display includes one or two stimuli, and whether category membership depends on configural…

We are currently in a century of data where massive amount of data are collected and processed every day, and machine learning plays a critical role in automatically processing the data and mining useful information from it for making decisions. Despite the wide and successful applications of machine learning in different fields, the robustness of…

In a novel version of the classic dot-pattern prototype-distortion paradigm of category learning, Homa et al. (2019) tested a condition in which individual training instances never repeated, and observed results that they claimed severely challenged exemplar models of classification and recognition. Among the results was a dissociation in which…

The curse of dimensionality, which has been widely studied in statistics and machine learning, occurs when additional features cause the size of the feature space to grow so quickly that learning classification rules becomes increasingly difficult. How do people overcome the curse of dimensionality when acquiring real-world categories that have…

Student modeling is one of the most important processes in adaptive systems. Although learning is individual, a model can be created based on patterns in student behavior. Since a student model can be created for more than one student, the use of machine learning techniques in student modeling is increasing. Artificial neural networks (ANNs),…

To meet the national and international call for creative and innovative engineers, many engineering departments and classrooms are striving to create more authentic learning spaces where students are actively engaging with design and innovation activities. For example, one model for teaching innovation is Innovation-Based Learning (IBL) where…

Text provides a compelling example of unstructured data that can be used to motivate and explore classification problems. Challenges arise regarding the representation of features of text and student linkage between text representations as character strings and identification of features that embed connections with underlying phenomena. In order…

Educators have long questioned why some students can experience achievement more easily in some school subjects/curriculum, but not in others. We argue that learners cannot ignore navigating two key features inherent within every curriculum--its cognitive demands as well as its opportunities for access to knowledge that are the twin foci of this…

ICAP is a framework that classifies learning processes based on students' explicit behaviors. The framework is developed for testing the hypothesis that interactive exercises are better than constructive exercises, and active exercises are better than the passive exercises for higher cognitive engagement and better learning outcomes. The ICAP…

This article takes a conceptual approach to an issue of pedagogical relevance--the presence of "teaching and learning moments" within educational environments. We suggest sources of philosophical confusions that design patterns for the classification and creation of typologies of classroom events. We identify three foundational…

Learning objectives, especially those well defined by applying Bloom's taxonomy for Cognitive Objectives, have been widely recognized as important in various teaching and learning practices. However, many educators have difficulties developing learning objectives appropriate to the levels in Bloom's taxonomy, as they need to consider the…