Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given the complexities of studying learning in authentic contexts interwoven with technological affordances, conducting tightly-controlled randomized experiments is not always feasible nor desirable. Today,…

Mathematical modeling describes how events, concepts, and systems of interest behave in the world using mathematical concepts. This research approach can be applied to theory construction and testing by using empirical data to evaluate whether the specific theory can explain the empirical data or whether the theory fits the data available.…

Purpose: The purpose of this study is to determine the competency characteristics required for the employment of master's degree students in educational technology. Design/methodology/approach: A combined qualitative and quantitative method was used to consult multiple experts through a modified Delphi method. Competency characteristics were…

An extraordinary amount of data is becoming available in educational settings, collected from a wide range of Educational Technology tools and services. This creates opportunities for using methods from Artificial Intelligence and Learning Analytics (LA) to improve learning and the environments in which it occurs. And yet, analytics results…

Rural schools face unique challenges providing high-quality professional development opportunities due to barriers such as geographic isolation and limited resources. This article provides information on three coaching models, eCoaching, iCoaching, and teacher dyad coaching. Each model has the potential to leverage technology to ameliorate…

As teacher educators who need to support the next generation of practitioners with technology and practice in the post-COVID teaching landscape, we draw on PICRAT (Kimmons, Graham, and West 2020) to guide our instructional work. This paper primarily addresses the ways that PICRAT has moved beyond TPACK and SAMR, two foundational theories for…

Advances in information technologies present opportunities for novel approaches, methods, and tools for new or improved education and training practices. Furthermore, these technologies are enabling a shift in the education paradigm. Based on an investigation of a wide range of information technologies supporting smart education, we developed a…

Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…

Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…

This study examines the current research on educational data mining, educational learning support services, personalized learning services, and personalized learning paths in education. The authors aim to integrate personalized learning concepts into traditional support services by drawing on the latest theoretical and practical research. Using…

In anatomical research and education, three-dimensional visualization of anatomical structures is crucial for understanding spatial relationships in diagnostics, surgical planning, and teaching. While computed tomography (CT) and magnetic resonance imaging (MRI) offer valuable insights, they are often expensive and require specialized resources.…

With the emergence of the Industrial Revolution 4.0, modern technologies such as cloud computing, artificial intelligence, and big data are profoundly transforming the education ecosystem. The development of education is not only faced with huge challenges but also contains rare opportunities. New concepts such as deep learning, adaptive learning,…

Acid-base chemistry, and in particular the Lewis acid-base model, is foundational to understanding mechanistic ideas. This is due to the similarity in language chemists use to describe Lewis acid-base reactions and nucleophile-electrophile interactions. The development of artificial intelligence and machine learning technologies has led to the…

Paradigmatic pluralism in educational technology is a largely unaddressed reality, and we have heretofore not provided guidance to professionals on how to navigate it. Pushing back against mainstream views of scientific progress (e.g., linear, progressive), we must recognize the processes by which paradigms are born, adopted, and rejected and that…

In this paper we present a collaborative 3D modeling and printing experience within a Project Based Learning (PBL) activity, carried out with two different groups of participants: pre-service teachers at the Universidad Autónoma de Madrid (Spain), and school students of Primary and Secondary level taking part in an extra-curricular activity.…