Artificial intelligence companies and researchers are currently working to create Artificial Superintelligence (ASI): AI systems that significantly exceed human problem-solving speed, power, and precision across the full range of human solvable problems. Some have claimed that achieving ASI -- for better or worse -- would be the most significant…

This study explores the novice programmers' intention to use chat generative pretrained transformer (ChatGPT) for programming tasks with emphasis on performance expectancy (PE), risk-reward appraisal (RRA), and decision-making (DM). Utilizing partial least squares structural equation modeling (PLS-SEM) and a sample of 413 novice programmers, the…

The rapid advancement of artificial intelligence (AI) has given rise to sophisticated language models that excel in understanding and generating human-like text. With the capacity to process vast amounts of information, these models effectively tackle problems across diverse domains. In this paper, we present a comparative analysis of prominent AI…

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…

Recent research suggests that working with generative artificial intelligence (AI), such as ChatGPT, can produce more creative outcomes than humans alone. However, does AI retain its creative edge when humans have access to alternative information sources, such as another human or the internet. We explored this question in a between-group…

This research aimed to develop and validate a rubric to assess Artificial Intelligence (AI) chatbots' effectiveness in accomplishing tasks, particularly within educational contexts. Given the rapidly growing integration of AI in various sectors, including education, a systematic and robust tool for evaluating AI chatbot performance is essential.…

Human-computer collaboration is an effective way to learn programming courses. However, most existing human-computer collaborative programming learning is supported by traditional computers with a relatively low level of personalized interaction, which greatly limits the efficiency of students' efficiency of programming learning and development of…

This study compared the problem-solving abilities of ChatGPT and 58 pre-service teachers (PSTs) in solving a mathematical word problem using various strategies. PSTs were asked to solve a problem individually. Data was collected from PSTs' submitted assignments, and their problem-solving strategies were analyzed. ChatGPT was also given the same…

Background: Collaborative problem solving (CPS) is important for success in the 21st century, especially for teamwork and communication in technology-enhanced environments. Measurement of CPS skills has emerged as an essential aspect in educational assessment. Modern research in CPS relies on theory-driven measurements that are usually carried out…

The aim of this paper is to survey recent research publications that use Soft Computing methods to answer education-related problems based on the analysis of educational data 'mined' mainly from interactive/e-learning systems. Such systems are known to generate and store large volumes of data that can be exploited to assess the learner, the system…

Detecting the student internal state during learning is a key construct in educational environment and particularly in Intelligent Tutoring Systems (ITS). Students' uncertainty is of primary interest as it is deeply rooted in the process of knowledge construction. In this paper we propose a new sensor-based multimodal approach to model…

A basic and classical assumption in the machine learning research area is "randomness assumption" (also known as i.i.d assumption), which states that data are assumed to be independent and identically generated by some known or unknown distribution. This assumption, which is the foundation of most existing approaches in the literature, simplifies…

This paper argues that an important design principle for building expert systems is to represent all control knowledge abstractly and separately from the domain knowledge upon which it operates. Abstract control knowledge is defined as the specifications of when and how a program is to carry out its operations, such as pursuing a goal, focusing,…

Overview of expert systems (intelligent computer applications that use data, a knowledge base, and a control mechanism to solve problems) highlights history of expert systems; construction (human element, knowledge acquisition and learning, system architecture); limitations; issues and trends; and implications for information science. Thirty-three…

A group of American and Japanese psychologists, anthropologists, linguists, and computer scientists gathered at the University of California, San Diego, to exchange ideas on models of joint problem solving and their special relevance to the design and implementation of computer-based systems of instruction. Much of the discussion focused on…