This article examines sociotechnical imaginaries of generative artificial intelligence (GenAI) through the cultural lens of the film "Barbie." The hyperreal setting of Barbieland serves as a prescient metaphor for education in an increasingly synthetic world where the real and artificial converge. By analysing representations of…

Most previous studies on creativity and motivation looked into the effects of intrinsic and extrinsic motivations on creativity. However, there have been newer motivation approaches related to work orientation and needs that may offer a chance to gain new insight into how people think about creativity. The present study used a hypothetical hiring…

Creativity is often characterized by the capacity to generate novel ideas, explore unconventional approaches, and solve problems through intuition, curiosity, and innovative thinking. Assessing this multifaceted skill is both essential and challenging, especially in educational and game-based environments where creativity drives engagement and…

The increasing use of complex machine learning models in education has led to concerns about their interpretability, which in turn has spurred interest in developing explainability techniques that are both faithful to the model's inner workings and intelligible to human end-users. In this paper, we describe a novel approach to creating a…

Background/purpose: In the first quarter of the twenty-first century, unprecedented developments in technology began to revolutionize 'modern' society and started the era of Industry 4.0, which is characterized by the rapid integration of the newest technologies such as the Internet of Things (IoT), smart technologies, and artificial intelligence…

This study investigates ChatGPT's perspectives on coding education for preschool children to provide a comprehensive understanding that is valuable for educators in early childhood education. An instrumental case study approach was employed, utilizing qualitative research design and case study methods. Data were gathered using a structured…

Explanatory processes are at the core of scientific investigation, legal reasoning, and education. However, effectively explaining complex or large amounts of information, such as that contained in a textbook or library, in an intuitive, user-centered way is still an open challenge. Indeed, different people may search for and request different…

In recent years, the pre-training of Large Language Models (LLMs) in the educational domain has garnered significant attention. However, a discernible gap exists in the application of these models to mathematics education. This study aims to bridge this gap by pre-training LLMs on authentic K-12 mathematical dialogue datasets. Our research is…

This study compared Stepwise Logistic Regression (Stepwise-LR) and three machine learning (ML) methods--Classification and Regression Trees (CART), Random Forest (RF), and Generalized Boosted Modeling (GBM) for estimating propensity scores (PS) applied in causal inference. A simulation study was conducted considering factors of the sample size,…

The rapid advancement of Artificial Intelligence (AI) offers new perspectives for addressing global environmental challenges like climate change. However, its effective application relies on cultivating interdisciplinary talent with expertise in AI and environmental science. Therefore, motivating adolescents to apply AI in environmental protection…

In-service teacher professional learning (PL) has become essential for enhancing teaching competence to meet the ever-changing demands of teaching English to speakers of other languages (TESOL). Existing literature reviews have identified and focused on specific factors influencing TESOL teachers' PL and probed into PL for preservice teachers but…

Human and animal behaviors are influenced by goal-directed planning or automatic habitual choices. Reinforcement learning (RL) models propose two distinct learning strategies: a model-based strategy, which is more flexible but computationally demanding, and a model-free strategy is less flexible yet computationally efficient. In the current RL…

Purpose: This study aims to explore the relationship between emotional intelligence (EI) and performance. Based on the job demands and resources (JD-R) and conservation of resources (COR) theories, a conceptual model is developed showing organizational citizenship behavior (OCB) as a mediator and emotional exhaustion as a moderator in influencing…

Large language models (LLMs) hold significant potential to enhance online learning by automating responses to learner queries and offering personalized, scalable support. However, concerns about bias in LLM-generated responses present challenges to their ethical and equitable use in educational settings. This study explores fairness and…

Designed for educators, researchers, and policymakers, this insightful book equips readers with practical strategies, critical perspectives, and ethical insights into integrating AI in education. First published in Swedish in 2023, and here translated, updated, and adapted for an English-speaking international audience, it provides a user-friendly…