This article provides a process to carefully evaluate the suitability of a content domain for which diagnostic classification models (DCMs) could be applicable and then optimized steps for constructing a test blueprint for applying DCMs and a real-life example illustrating this process. The content domains were carefully evaluated using a set of…

It's critical to foster artificial intelligence (AI) literacy for high school students, the first generation to grow up surrounded by AI, to understand working mechanism of data-driven AI technologies and critically evaluate automated decisions from predictive models. While efforts have been made to engage youth in understanding AI through…

Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…

Statistics teaching at the high school level needs modernizing to include digital sources of data that students interact with every day. Algorithmic modeling approaches are recommended, as they can support the teaching of data science and computational thinking. Research is needed about the design of tasks that support high school statistics…

This convergent, parallel, mixed-methods study with qualitative and quantitative content analysis methods was conducted to identify what type of thinking is required by the College and Career Readiness Assessment (CCRA+) by (a) determining the frequency and percentage of questions categorized as higher-level thinking within each cell of Hess'…

Prompting students to generate constructed responses as they read provides a window into the processes and strategies that they use to make sense of complex text. In this study, Markov models examined the extent to which: (1) patterns of strategies; and (2) strategy combinations could be used to inform computational models of students' text…

This brief report presents a secondary analysis of responses to the Student Subjective Wellbeing Questionnaire (SSWQ) with a sample of urban middle-schoolers. Relative classification validity evidence was evaluated for two screening models derived from responses to the SSWQ: one based on the Overall Wellbeing Scale (OWS) and the other based solely…

Historically, responsibility for career education and guidance in English schools was shared between the school and an external careers service. The Education Act 2011 transferred responsibility for career guidance to schools and has created a need for the new role of a 'careers leader'. In this article, we report on research in 27 English state…

A number of machine learning methods can be employed in the prediction of suicide attempts. However, many models do not predict new cases well in cases with unbalanced data. The present study improved prediction of suicide attempts via the use of a generative adversarial network.

In this theoretical paper, I examine the role and potential alterations to uses of social categories in qualitative research. Categories are socially constructed, imbued with power, and include race, class, gender, sexuality, and ability. These categories, although constructs and subject to change, hold durability and are leveraged in much of…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

The new normal imposed on us by the COVID-19 pandemic restricted the traditional ways we would teach high school students who are eager to participate in introductory astronomy projects on our university campus. This turned out to be a blessing in disguise as we were forced to come up with creative ways to get around this obstacle. The outcome is…

MoLam is a cultural performance art in northeast Thailand. MoLam is a profession that requires the high art of singing and relies on literary aesthetics and elaborate melodies to attract listeners. The objectives of this study were to: 1) research and collect information about Isan MoLam's performing arts, 2) explore the current conditions and…

As the world faces increasingly complex issues, there is a recognition in many disciplines that the existing paradigm of reductionist and linear thinking is not enough to address these issues. The agriculture, food, and natural resources fields are facing a host of issues that defy solutions in part because of the level of complexity. Systems…

Feature engineering, the construction of contextual and relevant features from system log data, is a crucial component of developing robust and interpretable models in educational data mining contexts. The practice of feature engineering depends on domain experts and system developers working in tandem in order to creatively identify actions and…