This paper seeks to explain the migration decisions of minority language speakers by investigating motivating factors. Viewed through a language planning lens, the study pushes the parameters of some of the discipline's more recent agency concepts within the context of migration. Semi-structured interviews were conducted with 60 Welsh speakers…

How scholars name different racial groups has powerful salience for understanding what researchers study. We explored how education researchers used racial terminology in recently published high-profile peer-reviewed studies. Our sample included 1,427 original empirical studies published in the nonreview AERA journals from 2009 to 2019. We found…

The purpose of this study was to examine the perceptions of college students regarding their knowledge of professional development competencies by classification and area of academic study. The study sought to answer the following questions: 1) was there a difference in the perception of college students towards professional development…

Even though working with data is as important as coding for understanding and dealing with complex problems across multiple fields, it has received very little attention in the context of Computational Thinking. This paper discusses an approach for bridging the gap between Computational Thinking with Data Science by employing and studying…

Purpose: This study investigates how the practice of dividing students and coursework into leveled categories persists in science education despite decades of efforts aimed at reducing inequities. This study makes underlying logics visible through an empirical analysis of how science educators attempt to reconcile an egalitarian vision of science…

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…

In recent years, numerous computational methods have been developed that have been widely used in humanities and literary studies. In spite of the potential of such methods in providing workable solutions to various inherent problems in research within these domains, including selectivity, objectivity, and replicability, very little empirical work…

The paper considers digital tutoring platforms as commercial products in the shadow education sector. In particular, it focuses on relatively new platforms which purportedly act as tutors themselves: web-based learning software providing "intelligent tutoring systems.' The question is not how effective and beneficial these platforms are for…

This study addresses the interpretations of the human in the discourse of civil industrial engineers in Chile and analyses their relationship with ethics and training. We argue that engineering is a heterogeneous activity that requires the alignment of multiple elements. Among these, assumptions about the human influence both the design of…

Do we structure object-related conceptual information according to real-world sensorimotor experience, or can it also be shaped by linguistic information? This study investigates whether a feature of language coded in grammar--numeral classifiers--affects the conceptual representation of objects. We compared speakers of Mandarin (a classifier…

Purpose: While the importance of interorganizational learning (IOL) as a resource for strategic renewal has been acknowledged in research, limited attention has been placed on exploring IOL in complex networks or ecosystems. This paper aims to bridge this gap in literature through conceptualizing IOL in the tourism industry at the micro, meso and…

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),…

Classification measures and entropy variants can be used as indicators of model fit for logistic regression. These measures rely on a cut-point, "c," to determine predicted group membership. While recommendations exist for determining the location of the cut-point, these methods are primarily anecdotal. The current study used Monte Carlo…

Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…

This paper investigates whether typical stress patterns in English nouns and verbs are available as a prosodic cue for categorisation and accelerated word learning during first language acquisition. The stress typicality hypothesis states that left-stressed nouns and right-stressed verbs should be acquired earlier than the reverse configurations…