The COVID-19 crisis was a global upheaval that significantly impacted the education systems--in the face of this, district and school leadership demonstrated remarkable resilience, overcoming the challenge of educating students through these uncertain times. They drew upon their existing leadership skills while also acquiring new ones they never…

This study addresses the opportunities presented by AI applications in education and the ethical issues brought about by this technology. AI in education holds excellent potential in personalized learning, automated assessment and feedback, and monitoring and analyzing student performance. However, using these technologies also raises ethical…

The growing implementation of Generative AI (GenAI) in education has implications on the representation of knowledge and identity across languages. In a context where content biases have been reported in AI-generated content, it becomes relevant to interrogate the ways in which AI technologies represent different linguistic identities. This…

Early in 2020, the United States was faced with the global impact of the COVID-19 pandemic resulting in several school districts across the country shutting down. What began as a temporary school closure morphed into one of the most creative and labor-intensive restructurings of schools. Leading the dramatic changes were elementary school…

Researchers increasingly identify virtual reality (VR) simulations as a potentially effective professional development tool. However, simulations used in education and behavior analysis typically require active oversight from technicians and instructors. "Smart" VR integrated with artificial intelligence could independently administer…

This article intends to empower and equip art educators to artistically address the functioning of facial detection algorithms through critical race theory (CRT). By highlighting how biometric data, a specific form of data that measures the physical qualities of individuals, is used in common social media facial detection algorithms like Snapchat,…

The extant literature aimed at characterizing attentional capability in autistics has presented inconsistent findings. This inconsistency and uncertainty may be the product of different theoretical and methodological approaches used to define attention in autism. In the current study, we investigate whether the allocation of attentional resources…

The article reviews some of the relationships between AI and education, emphasizing the metaphors used, the difficulties in finding points of agreement, as well as aspects of the social criticism that is made of AI (e.g. considering that it can be a form of unwanted deviation). AI appears as one more case of technology that comes to improve…

This position paper explores the current state of artificial intelligence (AI) tools, educator support of and opposition to AI tools in teaching and learning, and the ethical and social implications of AI tools in higher education. As technology continuously develops in the educational community, educators must have a voice in how AI exists in the…

Artificial intelligence (AI) and data science (DS) are receiving a lot of attention in various fields. In the educational field, the need for education utilizing AI and DS is also being emerged. In this context, we have created an AI/DS integrating program that generates a compound classification/regression model using characteristics of compounds…

Research into student affect detection has historically relied on ground truth measures of emotion that utilize one of three sources of data: (1) self-report data, (2) classroom observations, or (3) sensor data that is retrospectively labeled. Although a few studies have compared sensor- and observation-based approaches to student affective…

What does it mean for a model to be a better model? One conceptualization, indeed a common one in Educational Data Mining, is that a better model is the one that fits the data better, that is, higher prediction accuracy. However, oftentimes, models that maximize prediction accuracy do not provide meaningful parameter estimates, making them less…

Feedback on student assignments plays a crucial role in steering students toward academic success. To provide feedback more promptly and efficiently, researchers are actively exploring the use of large language models (LLMs) to automatically generate feedback on student artifacts. Although the generated feedback is highly fluent, coherent, and…

Combining formative practice with the primary expository content in a learning by doing method is a proven approach to increase student learning. Artificial intelligence has led the way for automatic question generation (AQG) systems that can generate volumes of formative practice otherwise prohibitive with human effort. One such AQG system was…

Predictive models play a pivotal role in education by aiding learning, teaching, and assessment processes. However, they have the potential to perpetuate educational inequalities through algorithmic biases. This paper investigates how behavioral differences across demographic groups of different sizes propagate through the student success modeling…