The term "Artificial Intelligence" was coined in 1956 at a conference at Dartmouth College and since then it has undergone constant development and has evolved radically. Prominent pioneers of the term include John McCarthy, Marvin Minsky, Allen Newell, and Herbert A. Simon. The application of AI in education worldwide has increased…

Emerging Artificial Intelligence-enhanced technology platforms in education warrant attention to exploring new learning strategies and dynamics. Keeping up with the accelerating momentum to bring classic traditional learning activities to Artificial Intelligence-supported platforms may unbalance the interest in developing the participants'…

Teaching history invokes the motif of ancient feud with dispute focused on meanings of learning. Learning meanings deriving from traditional theories such as behaviourism need abandoning post-pandemic. Emerging theories, including Non-Affirmative Theory of Education (NATE) with a strong social justice motif, ought to undergird new learning. This…

The Cross Industry Standard Process for Data Mining (CRISP-DM) framework was developed in the 1990s and has been widely used as the most relevant and comprehensive leading principle for conducting analytics projects. Despite the wide acceptance and adoption of the CRISP-DM framework, the current business analytics discipline often focuses on the…

Teamwork skills are commonly evaluated by human assessors, which can be logistically challenging and resource intensive. Technological advancements provide an opportunity for a new assessment method -- virtual behavioural simulations with self-scoring algorithms. This study explores whether a rule-based algorithm can match human assessors at…

In language assessment, AI technology has been incorporated in task design, assessment delivery, automated scoring of performance-based tasks, score reporting, and provision of feedback. AI technology is also used for collecting and analyzing performance data in language assessment validation. Research has been conducted to investigate the…

Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…

Artificial Intelligence (AI) is developing in a manner that blurs the boundaries between specific areas of application and expands its capability to be used in a wide range of applications. The public release of ChatGPT, a generative AI chatbot powered by a large language model (LLM), represents a significant step forward in this direction.…

Electronic learning (e-learning) is considered the new norm of learning. One of the significant drawbacks of e-learning in comparison to the traditional classroom is that teachers cannot monitor the students' attentiveness. Previous literature used physical facial features or emotional states in detecting attentiveness. Other studies proposed…

Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…

Many Library and Information Science (LIS) training programs are gradually expanding their curricula to include computational data science courses such as supervised and unsupervised machine learning. These programs focus on developing both "classic" information science competencies as well as core data science competencies among their…

Books shape how children learn about society and norms, in part through representation of different characters. We use computational tools to characterize representation in children's books widely read in homes, classrooms, and libraries over the last century, and describe economic forces that may contribute to these patterns. We introduce new…

Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…

Open-ended responses to surveys can be highly beneficial to higher education institutions, providing clarity and context that quantitative data can sometimes lack. However, analyzing open-ended responses typically takes time and manpower most institutional assessment offices do not have to spare. This study focused on finding a potential solution…

While the discussion on generative artificial intelligence, such as ChatGPT, is making waves in academia and the popular press, there is a need for more insight into the use of ChatGPT among students and the potential harmful or beneficial consequences associated with its usage. Using samples from two studies, the current research examined the…