In this descriptive study I wanted to see how including an assignment which required students to use generative artificial intelligence (AI) would affect students' perceptions of generative AI, including their own assessment and grading of generative AI-created content. I theorized that more than half the students would assess the generative AI's…

Purpose: The study explores the acceptance of AI-driven virtual teaching assistants (VTAs) in Vietnam's online learning. It aims to identify factors influencing students' intention and actual use of these emerging technologies. Design/methodology/approach: Using an extended Unified Theory of Acceptance and Use of Technology (UTAUT2), the research…

The widespread adoption of generative AI is transforming academic writing in higher education, rendering traditional, product-focused assessment models obsolete. These methods fail to capture the iterative and tool-mediated nature of modern writing processes, creating an urgent need for new evaluation approaches. This paper addresses this gap by…

In recent years, the rapid technological development and widespread adoption of chatbots equipped with generative artificial intelligence (GenAI) based on Large Language Models (LLMs) have brought dramatic changes in the field of education. In e-learning, flexible progression and real-time feedback enabled by human-like interaction with artificial…

Advances in machine learning (ML) offer new possibilities for science education research. We report on early progress in the design of an ML-based tool to analyze students' mechanistic sensemaking, working from a coding scheme that is aligned with previous work in physics education research (PER) and that is amenable to recently developed ML…

Low birthweight children are at risk for motor, language and cognitive delay in early childhood. The aim of the present study is the examination of cognitive skill development among 4-year-old preterm and low birthweight children in relation to demographical and perinatal variables. We utilized the Wechsler Preschool Primary Scales of…

Children's ways of learning are as different as the colors of the rainbow. All children have different personalities, preferences and tastes; they all have a certain way they prefer to learn. Teachers and parents need to be aware of and value these differences. Children's brains develop faster from birth to age three than any other time, and more…

Recently, with the advancement in 2D imaging techniques and 3D visual sensors such as LiDAR, RGB-D cameras, etc. The use of 2D and 3D data is ubiquitous in various fields like autonomous driving, AR, and VR. Therefore, we are faced with an ever-increasing demand for approaches toward the automatic processing and analysis of data from multiple…

We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…

Massive Open Online Courses (MOOCs) make high-quality learning accessible to students from all over the world. On the other hand, they are known to exhibit low student performance and high dropout rates. Early prediction of student performance in MOOCs can help teachers intervene in time in order to improve learners' future performance. This is…

Multimodal imaging studies targeting preschoolers and low-functioning autism spectrum disorder (ASD) patients are scarce. We applied machine learning classifiers to parameters from T1-weighted MRI and DTI data of 58 children with ASD (age 3-6 years) and 48 typically developing controls (TDC). Classification performance reached an accuracy,…

Social sciences expose many cognitively complex, highly qualified, or fuzzy problems, whose resolution relies primarily on expert judgement rather than automated systems. One of such instances that we study in this work is a reflection analysis in the writings of student teachers. We share a hands-on experience on how these challenges can be…

In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…

Programming online judges (POJs) have been increasingly used in CS1 classes, as they allow students to practice and get quick feedback. For instructors, it is a useful tool for creating assignments and exams. However, selecting problems in POJs is time consuming. First, problems are generally not organized based on topics covered in the CS1…

Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework…