The integration of artificial intelligence (AI) into mathematical problem-solving has shown significant potential to enhance student learning and performance. However, while AI tools offer numerous benefits, they are prone to occasional conceptual and arithmetic errors that can mislead users and obscure understanding. This research examines such…

This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML outputs. In each of the experiments, participants were given the T and L task with T-shaped targets and…

Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…

As technology continues to evolve, the process of English translation has become easier. A technology called widget, which is used in modern research, provides an efficient graphical user interface for the interaction between the user and the application. This paper compares the newly proposed wireless widget system with existing models of English…

This paper explores the efficacy of ChatGPT, a generative artificial intelligence in educational contexts, particularly concerning its potential to assist students in overcoming academic challenges while highlighting its limitations. ChatGPT is suitable for solving general problems. When a student comes across academic challenges, ChatGPT may…

Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…

Complex sequences are ubiquitous in human mental life, structuring representations within many different cognitive domains--natural language, music, mathematics, and logic, to name a few. However, the representational and computational machinery used to learn abstract grammars and process complex sequences is unknown. Here, we used an artificial…

One-on-one tutoring is widely acknowledged as an effective instructional method, conditioned on qualified tutors. However, the high demand for qualified tutors remains a challenge, often necessitating the training of novice tutors (i.e., trainees) to ensure effective tutoring. Research suggests that providing timely explanatory feedback can…

The aim of the research is to investigate the academic achievement of ChatGPT, an artificial intelligence based chatbot, in a national mathematics exam. For this purpose, 3.5 and 4 versions of ChatGPT were asked mathematics questions in a national exam. The method of the research is a case study. In the research, 3.5 and 4 versions of ChatGPT were…

We present a case study of a conversation between ourselves and an artificial intelligence-based chatbot ChatGPT. We asked the chatbot to respond to a basic physics question that will be familiar to most physics teachers: 'A teddy bear is thrown into the air. What is its acceleration in the highest point?' The chatbot's responses, while…

Cognitive load occurs when the demands of a task surpass the available processing capacity, straining mental resources and potentially impairing performance efficiency, such as increasing the number of errors in a task. Owing to its ubiquity in real-world scenarios, the existence of offloading strategies to reduce cognitive load is not new to…

This study examined a few narrative texts accessed online from kompas.com and translated from Indonesian into French with the help of "Bing Translator," which is a multilingual machine translation cloud service of Microsoft Corporation. This study used a qualitative approach to analyze the translated texts, with the view to identify the…

Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error-driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of…

This study investigated the use of virtual chatbots in a 3D multi-user virtual environment (3D MUVE) to enhance the communication skills of Chinese as a foreign language (CFL) learners. Several virtual chat agents, developed using pattern matching techniques and embedded in Second Life, created a blended learning environment in which CFL learners…

This study investigates the performance of GPT-4, an advanced AI model developed by OpenAI, on the force concept inventory (FCI) to evaluate its accuracy, reasoning patterns, and the occurrence of false positives and false negatives. GPT-4 was tasked with answering the FCI questions across multiple sessions. Key findings include GPT-4's…