Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in humancentric fields. We implement five state-of-the-art methodologies for explaining black-box machine learning models…

Artificial intelligence technology has become widely used in many industries, including healthcare, agriculture, banking, social security, and home furnishings, due to the rise and development of this discipline. One of the newest areas of technology in the education industry is AI in Education, where extensive research supports instructional…

The ability to think critically is an important and valuable skill that students should develop to successfully solve problems. The process of writing requires critical thinking (CT), and the subsequent piece of text can be viewed as a product of CT. One of the strategies educators may use to develop CT is modelling. Given ChatGPT's ability to…

The motivation, philosophy, and organization of a course on artificial intelligence in chemical engineering is presented. The purpose is to teach undergraduate and graduate students how to build AI-based models that incorporate a first principles-based understanding of our products, processes, and systems. This is achieved by combining…

With recent advances in artificial intelligence (AI), machine learning (ML) has been identified as particularly useful for organizations seeking to create value from data. However, as ML is commonly associated with technical professions, such as computer science and engineering, incorporating training in the use of ML into non-technical…

Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…

Research and development work in artificial intelligence in education (AIED) is wide ranging and rapidly growing to support all areas of science, technology, engineering, and mathematics (STEM) teaching and learning. At the risk of hyperbole, this is potentially the most fundamentally game-changing technology for education to emerge since the…

The use of generative artificial intelligence (GAI) large language models has increased in both professional and classroom technical writing settings. One common response to student use of GAI is to increase surveillance, incorporating plagiarism detection services or banning certain composing activities from the classroom. This paper argues such…

Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…

Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…

The arrival of generative artificial intelligence (AI) is fundamentally different from prior technologies used in educational settings. Educators and researchers of online, blended, and in-person learning are still coming to grips with how to employ current AI technologies in the learning experience, let alone understanding the potential…

Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art approaches use neural language models to create vectorized representations of students responses, followed by classifiers to predict the score. However, these…

The limitations of traditional education models and the advancement of technology have revealed the need to transform the learning experience. The "Flipped Learning" approach, born out of this need, is a model where students study learning materials in advance and participate in more interactive and hands-on activities in the classroom.…

There has been great progress towards Reinforcement Learning (RL) approaches that can achieve expert performance across a wide range of domains. However, researchers have not yet applied these models to learn expert models for educationally relevant tasks, such as those taught within tutoring systems and educational games. In this paper we explore…

Learning is an integral part of being human. How people learn has long been discussed, revealed in many learning theories, investigated in numerous studies, and demonstrated in extensive practices. The goal of this article is to rethink how people learn from four fundamental perspectives, that is, learning by interaction with content (C), learning…