Sudoku is a puzzle that has a unique solution. No matter how many methods are used, the result will always be the same. The player thought that the number of givens or clues, the initial value on the Sudoku puzzles, would significantly determine the difficulty level, which is not necessarily correct. This research uses two search algorithms,…

Generative Artificial Intelligence (GenAI) is an emerging technology that creates relevant text, images and other content from prompts. Large Language models (LLMs) are the most widely used of these GenAI forms. This technology already has applications in business and education. This paper tests GenAI's ability to apply physics to global problems…

Large language models (LLMs) are now widely accessible, reaching learners across all educational levels. This development has raised concerns that their use may circumvent essential learning processes and compromise the integrity of established assessment formats. In physics education, where problem solving plays a central role in both instruction…

We present the results of a study investigating the potential role of the generative AI GPT-4 in scaffolding students' metacognitive activities during problem-solving. The theoretical framework according to which students' interactions with GPT-4 are analysed is based on three main components: the notion of utilisation scheme within the frame of…

As is rapidly becoming clear, data science increasingly permeates many aspects of life. Educational research recognizes the importance and complexity of learning data science. In line with this imperative, there is a growing need to investigate the factors that influence student performance in data science tasks. In this paper, we aimed to apply…

Creativity is often characterized by the capacity to generate novel ideas, explore unconventional approaches, and solve problems through intuition, curiosity, and innovative thinking. Assessing this multifaceted skill is both essential and challenging, especially in educational and game-based environments where creativity drives engagement and…

The increasing use of complex machine learning models in education has led to concerns about their interpretability, which in turn has spurred interest in developing explainability techniques that are both faithful to the model's inner workings and intelligible to human end-users. In this paper, we describe a novel approach to creating a…

The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…

In this paper, we initially investigate the capabilities of GPT-3 5 and GPT-4 in solving college-level calculus problems, an essential segment of mathematics that remains under-explored so far. Although improving upon earlier versions, GPT-4 attains approximately 65% accuracy for standard problems and decreases to 20% for competition-like…

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…

As artificial intelligence (AI) becomes increasingly integrated into higher education, particularly in creative disciplines, the role of AI turns into a co-creative partner. This study investigates the impact of AI-relevant training on media and communication students in Taiwan, focusing on the development of AI literacy, self-efficacy,…

Creative thinking stems from the cognitive process that fosters the creation of new ideas and problem-solving solutions. Artificial intelligence systems and neural network models can reduce the intricacy of understanding creative cognition. For instance, the generation of ideas could be symbolized as patterns of binary code in which clusters of…

The architecture of the computational thinking with gamified using artificial intelligence prompt engineering, or architecture of the CT platform with gamified, is a learning tool intended to promote activity-based learning that focuses on problem-solving by doing. This platform is fabricated with the combination of computational thinking process…

Increased use of computer-based assessments has facilitated data collection processes that capture both response product data (i.e., correct and incorrect) and response process data (e.g., time-stamped action sequences). Evidence suggests a strong relationship between respondents' correct/incorrect responses and their problem-solving proficiency…

Contribution: We present a framework for teachers to investigate the relationships between attributes of students' solutions in the process of problem solving or computational thinking. We provide visualization and evaluation techniques to find hidden patterns in the students' solutions which allow teachers to predict the specific behavior of…