Purpose: This study investigates user preferences for motivational features aligned with self-determination theory (SDT), emphasizing autonomy, relatedness, and competency. The study seeks to identify the most appealing and effective motivational features in AI-driven mobile apps for fostering autonomy, promoting relatedness, and enhancing…

Multilingual learners (MLs) often struggle with science conceptual learning partly due to the abstractness of the concepts and the complexity of scientific texts. This study presents a case of a Virtual Reality (VR) enhanced science learning unit to support middle-school students' science conceptual learning. Using a transformative mixed methods…

Developing models and using mathematics are two key practices in internationally recognized science education standards, such as the Next Generation Science Standards (NGSS). However, students often struggle with these two intersecting practices, particularly when developing mathematical models about scientific phenomena. Formative…

Providing feedback to students in a sustainable way represents a perennial challenge for secondary teachers of writing. Employing artificial intelligence (AI) tools to give students personalized and immediate feedback holds great promise. Project Topeka offered middle school teachers pre-curated teaching materials, foundational texts and videos,…

Adaptive learning systems personalize instruction to students' individual learning needs and abilities. Such systems have shown positive impacts on learning. Many schools in the United States have adopted adaptive learning systems, and the rate of adoption in China is accelerating, reaching almost 2 million unique users for one product alone in…

Drama learning is helpful for English speaking, however, few studies provided students with opportunities to practice drama conversations individually. This study proposed a Context-Awareness Smart Learning Mechanism (CASLM) and integrated into SmartVpen that consisted of context-aware learning content, context-aware input assistance, oral…

Artificial intelligence (AI) education is still in the exploratory stage for K-12 schools. There is a serious lack of studies that informed schools teachers about AI curriculum design. Accordingly, this paper presented an AI curriculum and examined whether the curriculum improves students' perceived AI knowledge, attitudes, and motivation towards…

There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…

Recent work describes methods for systematic, data-driven improvement to instructional content and calls for diverse teams of learning engineers to implement and evaluate such improvements. Focusing on an approach called "design-loop adaptivity," we consider the problem of how developers might use data to target or prioritize particular…

Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education…

The rapid development of generative artificial intelligence (AI) is expected to have a profound impact on various aspects of human society, including mathematics education. Nevertheless, there is a noticeable lack of research, particularly in Greece, that focuses on the development and assessment of lesson plans and math worksheets tailored for…

Willingness to communicate (WTC) is considered to be an important factor contributing to successful foreign language learning. Many studies aim at finding effective tools for enhancing WTC. With the support of AI and Automatic Speech Recognition technology, intelligent personal assistants (IPAs) seem to have potentials in improving foreign…

This study explores the use of the Adaptive Neuro-Fuzzy Inference System (ANFIS), a neuro-fuzzy approach, to analyze the log data of technology-based assessments to extract relevant features of student problem-solving processes, and develop and refine a set of fuzzy logic rules that could be used to interpret student performance. The log data that…

Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…

Background: We examine the development of youth sociopolitical consciousness and agency in an eighth-grade science classroom as students of color engage in critical speculative design activities, exploring the multi-scalar, racial realities and possibilities of the science and engineering of pervasive digital technologies--specifically involving…