Intelligent personal assistants (IPAs) carry massive potential in enhancing students' performance through individualized dynamic scaffolding strategy. Despite IPAs being increasingly recognized among educationists, little is known about their application in the development of students' scientific inquiry skills, particularly in physics. This study…

Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…

This systematic review provides unique findings with an up-to-date examination of artificial intelligence (AI) in higher education (HE) from 2016 to 2022. Using PRISMA principles and protocol, 138 articles were identified for a full examination. Using a priori, and grounded coding, the data from the 138 articles were extracted, analyzed, and…

In this study, the factors affecting the transactional distance levels of university students who continue their courses with distance education in the 2020-2021 academic years due to the COVID pandemic process were examined. Factors that affect transactional distance are modeled with Artificial Neural Networks, one of the data mining methods.…

As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…

As a prominent aspect of modeling learners in the education domain, knowledge tracing attempts to model learner's cognitive process, and it has been studied for nearly 30 years. Driven by the rapid advancements in deep learning techniques, deep neural networks have been recently adopted for knowledge tracing and have exhibited unique advantages…

Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…

One of the ultimate problems of moral philosophy is to determine who or what is worth moral consideration or not. "Morality" is a relative concept, which changes significantly with the environment and time. This means that morality is incredibly inclusive. The emergence of AI technology has a significant impact on the understanding and…

Background: The recent discussion of introducing artificial intelligence (AI) knowledge to K-12 students, like many engineering and technology education topics, has attracted a wide range of stakeholders and resources for school curriculum development. While teachers often have to directly interact with external stakeholders out of the public…

With the increased popularity of electronic textbooks, there is a growing interest in developing a new generation of "intelligent textbooks," which have the ability to guide readers according to their learning goals and current knowledge. Intelligent textbooks extend regular textbooks by integrating machine-manipulable knowledge, and the…

Researchers have become increasingly interested in response times to survey items as a measure of cognitive effort. We used machine learning to develop a prediction model of response times based on 41 attributes of survey items (e.g., question length, response format, linguistic features) collected in a large, general population sample. The…

This review is aimed at synthesizing current findings concerning technology-based cognitive offloading and the associated effects on learning and memory. While cognitive externalization (i.e., using the environment to outsource mental computation) is a highly useful technique in various problem-solving tasks, a growing body of research suggests…

Design science research (DSR) is taught in university courses and used by students for their final theses. For successfully learning DSR, it is important to learn to apply it to real-world problems. However, students not only need to learn the new DSR paradigm (meta-level) but also need to develop an understanding of the problem domain…

The aim of this article is to use decolonial thinking, as applied in the field of AI, to explore the ethical and pedagogical implications for higher education teaching and learning. The questions driving this article are: What does a decolonial approach to AI imply for higher education teaching and learning? How can educators, researchers and…

Data mining approaches have been widely used to estimate student performance in online education. Various Machine Learning (ML) based data mining techniques have been developed to evaluate student performance accurately. However, they face specific issues in implementation. Hence, a novel hybrid Elman Neural with Apriori Mining (ENAM) approach was…