Can sentiment analysis be used in an educational context to help teachers and researchers evaluate students' learning experiences? Are sentiment analyzing algorithms accurate enough to replace multiple human raters in educational research? A dataset of 333 students evaluating a learning experience was acquired with positive, negative, and neutral…

Various theories and models have implicitly discussed the role of interaction when using learning technologies. Indeed, interaction is described as being important as it relates to technology adoption, cognitive load, and usability. While each of these perspectives describe elements of interaction, they fail to comprehensively detail how educators…

The application of the metaverse provides a new perspective for educational innovation and talent training in the new century. By creating multi-channel perceptions such as sight, hearing, and touch through the VR/AR/MR immersive environment, the study found that learners' emotional engagement and cognitive level can be effectively improved in the…

How do scientists generate and weight candidate queries for hypothesis testing, and how does learning from observations or experimental data impact query selection? Field sciences offer a compelling context to ask these questions because query selection and adaptation involves consideration of the spatiotemporal arrangement of data, and therefore…

Assessing students' participation in science practices presents several challenges, especially when aiming to differentiate meaningful (vs. rote) forms of participation. In this study, we sought to use machine learning (ML) for a novel purpose in science assessment: developing a construct map for students' "consideration of generality,"…

Extending previous research on the Computers Are Social Actors paradigm and the human-to-human interaction script, this study examines the interpersonal impressions of a social robot evaluator versus a human evaluator in a performance evaluation context. A between-subjects experiment was conducted to measure participants' impressions of the…

This paper investigates the role of English in voice assistant (Siri, Alexa, Google Assistant) use from the perspective of language ideology. Major commercial companies in the voice assistant market use English as a training language for their speech technologies and offer the most optimised support for standardised varieties of English. This…

Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been…

EFL learners generally have the problem of logical fallacies in EFL argumentative writings. Logical fallacies are errors in reasoning that can undermine EFL argumentative writing quality. Explicit training on logical fallacies may help learners deal with the problem and enhance their self-efficacy and proficiency in EFL argumentative writing,…

Purpose: The prediction of student attrition is critical to facilitate retention mechanisms. This study aims to focus on implementing a method to predict student attrition in the upper years of a physiotherapy program. Design/methodology/approach: Machine learning is a computer tool that can recognize patterns and generate predictive models. Using…

This research intended to identify key contextual factors that synergistically influence high- and low-performing students' science outcomes by drawing upon a dynamic model of educational effectiveness. The dataset, the Programme for International Student Assessment (PISA) 2015, consisted of 79,963 science scores for secondary students (49,924…

Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver and have low ecological validity and accuracy. To support an SIB monitoring system for autism spectrum disorder (ASD), we evaluated machine learning methods for detecting and distinguishing diverse SIB types. SIB episodes were captured with body-worn…

Coprocessor architectures in High Performance Computing are prevalent in today's scientific computing clusters and require specialized knowledge for proper utilization. Various alternative paradigms for parallel and offload computation exist, but little is known about the human factors impacts of using the different paradigms. With computer…

Identifying critical decisions is one of the most challenging decision-making problems in real-world applications. In this work, we propose a novel Reinforcement Learning (RL) based Long-Short Term Rewards (LSTR) framework for critical decisions identification. RL is a machine learning area concerning with inducing effective decision-making…

This research describes a case study of an integrated human-computer interaction (HCI) course for construction engineering students using project-based learning and experiential learning cycle methods. To help engineering students keep pace with the increasing use of information technology (IT) in the construction industry, educational…