Random forests are a nonparametric machine learning method, which is currently gaining popularity in the behavioral sciences. Despite random forests' potential advantages over more conventional statistical methods, a remaining question is how reliably informative predictor variables can be identified by means of random forests. The present study…

In the field of educational robotics, it is important to understand the processes trough which child-robot interactions are established during play activities. In terms of socio-material characteristics, robots can vary widely, from more mechanical robots to more anthropomorphic ones. Research has shown that the degree of anthropomorphization of…

This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three…

With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of supports from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatGPT. In particular, there has been a surge of academic interest in human-AI collaboration and…

Background: In computing education, educators are constantly faced with the challenge of developing new curricula, including learning objectives (LOs), while ensuring that existing courses remain relevant. Large language models (LLMs) were shown to successfully generate a wide spectrum of natural language artefacts in computing education.…

Background Study: Assessing learners' inquiry-based skills is challenging as social, political, and technological dimensions must be considered. The advanced development of artificial intelligence (AI) makes it possible to address these challenges and shape the next generation of science education. Objectives: The present study evaluated the SSI…

This article examines the risk of crossover contamination in individual-level randomization, a common concern in experimental research, in the context of a large-enrollment college course. While individual-level randomization is more efficient for assessing program effectiveness, it also increases the potential for control group students to cross…

Despite the increasing interest in using AI tools as assistant agents in instructional settings, the effectiveness of ChatGPT, the generative pretrained AI, for evaluating the accuracy of second language (L2) writing has been largely unexplored in formative assessment. Therefore, the current study aims to examine how ChatGPT, as an evaluator,…

This study aimed to compare the effectiveness of the experiential learning cycle (ELC) and self-regulated learning (SRL), both implemented through a game-based approach (AI 2 Robot City board game), in fostering computational thinking (CT) and understanding of artificial intelligence (AI) applications in university level. The sample consisted of…

Purpose: Automatic speech analysis (ASA) and automatic speech recognition systems are increasingly being used in the treatment of speech sound disorders (SSDs). When utilized as a home practice tool or in the absence of the clinician, the ASA system has the potential to facilitate treatment gains. However, the feedback accuracy of such systems…

Chemistry education research demonstrates the value of open-ended writing tasks, such as writing-to-learn (WTL) assignments, for supporting students' learning with topics including reasoning about reaction mechanisms. The emergence of generative artificial intelligence (AI)technology, such as chatbots ChatGPT and Bard, raises concerns regarding…

Role-play activities are considered a useful instructional design in enhancing the speaking performance of foreign language learners. However, in the traditional classroom context, learners may not readily have access to interlocutors for role-play activities. In this study, we proposed a designed method that integrated the GenAI agent into…

Objective: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of intrinsic patterns of brain connectivity revealed during resting state using machine learning…

This report summarizes the work conducted for the Artificial Intelligence Measurement System (AIMS) Project which was undertaken as an exploration of methodology to consider how the effects of artificial intelligence systems could be compared to human performance. The research covered four areas of inquiry: (1) natural language processing and…