With the goal of moving toward an alternative rate model for child care subsidies, the North Carolina Division of Child Development and Early Education (DCDEE) partnered with the American Institutes for Research® (AIR®) to conduct a study to estimate the true cost of high-quality child care and to recommend three new rate models for the state to…

This paper proposes a conceptual framework enabling the development and adoption of descriptive, diagnostic, predictive and recommendatory data analytics in teacher professional learning by harnessing some of the affordances of digital technologies to convert data into actionable insights. The paper argues for a technology-enhanced approach that…

Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…

A multigenerational caregiving crisis is emerging at the interface of family and work, and human resource development (HRD) should pay attention. This perspective considers the impact of multigenerational caregiving-induced responsibilities on human capital frameworks, and their implications for HRD. We believe traditional models often neglect the…

Background: The 2018 Declaration of Astana acknowledges the need to include traditional, complementary and integrative health care (TCIH) knowledge and technologies within primary health care. The World Health Assembly has also called member states to integrate TCIH into national healthcare systems. However, little attention has been given to…

This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…

Background: Training the memorization of declarative knowledge requires the repetitive presentation of various forms of factual questions to learners. Educational games designed for this purpose should offer activities that are both tailored to individual learners and varied to prevent boredom. Whilst the Technology-Enhanced Learning (TEL)…

In educational systems, predictive models face significant challenges during initial deployment and when new students begin to use them or when new exercises are added to the system due to a lack of data for making initial inferences, often called the cold start problem. This paper tests logitdec and logitdecevol, "evolutionary" features…

Across Europe, university governance models are diverse and changing, but how they approach inclusiveness, collaboration and competences increasingly informs institutional transformation and societal impact. This report explores the evolving landscape of university governance in Europe, drawing on data from the latest edition of EUA's Autonomy…

Research suggests that generative AI (GAI) responds to divergent thinking (DT) prompts with multiple ideas, some of which seem to be original. The present investigation administered 55 DT tasks to three GAI services (Bard, GPT 3.5, and GPT 4.0). Instead of examining individual responses, an Idea Density algorithm was used to assess the output.…

Cognitive diagnosis models (CDMs) are widely used to assess individuals' latent characteristics, offering detailed diagnostic insights for tailored instructional development. Maximum likelihood estimation using the expectation-maximization algorithm (MLE-EM) or its variants, such as the EM algorithm with monotonic constraints and Bayes modal…

This report shows that districts can use data they already routinely collect to predict which students will become chronically absent. Existing work to predict absenteeism in advance either is academic and too challenging for districts to use themselves or uses proprietary systems that are not publicly accessible. Accordingly, in this report, the…

"Internet plus Music Education" has the characteristics of full-scene learning ecology, data-driven model innovation, and immersion experience upgrade, and the exploration of educational metauniverse and the breakthrough of educational big model have become an important development trend, and the industrial ecology is also undergoing…

Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…

Environmental, social, and governance (ESG) considerations are garnering increasing interest from various stakeholders. Nevertheless, the impact of ESG evaluation policies--whether voluntary or mandatory--are complex, particularly in competitive markets. Consequently, this study develops a game-theoretic model to investigate the propensity of…