Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…

Intelligent tutoring systems (ITS) have been shown to be highly effective at promoting learning as compared to other computer-based instructional approaches. However, many ITS rely heavily on expert design and hand-crafted rules. This makes them difficult to build and transfer across domains and limits their potential efficacy. In this paper, we…

Many previous studies have highlighted the influence of learners' affective states on learning with tutoring systems. However, the associations between learning and learners' meta-affective capability are still unclear. The goal of this paper is to analyse meta-affective capability and its influence on learning outcomes as well as the dynamics of…

Several studies have investigated the need for learning difficulties identification specifically Dyslexia, Dysgraphia and Dyscalculia. The identification of these difficulties among children is a multiple screening process under psychologist's supervision. Learning difficulties identification is a difficult task; it affects the learning process…

To inform pedagogical decisions about using technology, it is important to understand from the ground up how technology is utilised during language learning activities. This paper takes an ethnomethodological conversation analytic approach to examine a learner's participation in epistemic management actions and its consequences for second language…

We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance modeling problem is a critical step for building adaptive online teaching systems. Specifically, we conduct a study of how to utilize various types and large amounts of log data from earlier…

Understanding a student's problem-solving strategy can have a significant impact on effective math learning using Intelligent Tutoring Systems (ITSs) and Adaptive Instructional Systems (AISs). For instance, the ITS/AIS can better personalize itself to correct specific misconceptions that are indicated by incorrect strategies, specific problems can…

Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at designing systems that recommend sequences of educational activities to maximize students' learning…

Intelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning…

Adaptive educational software is likely to better support broader and more diverse sets of learners by considering more comprehensive views (or models) of such learners. For example, recent work proposed making inferences about "non-math" factors like reading comprehension while students used adaptive software for mathematics to better…

Understanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' preferences between AI and human tutors to support their learning. While AI demonstrates growing…

In designing an intelligent tutoring system, a core area of the application of AI in education, tips from the system or virtual tutors are crucial in helping students solve difficult questions in disciplines like mathematics. Traditionally, the manual design of general tips by teachers is time-consuming and error-prone. Generative AI, like…

Students are termed "multitaskers," and it is likely that they easily fall prey to other subjects or topics that most interest them. They occasionally took heed or gave close and thoughtful attention to the lectures they were on. In the current educational system, our young generations receive materials from their leftovers, and their…

In many science, technology, engineering, and mathematics (STEM) domains, instruction on foundational concepts heavily relies on visuals. Instructors often assume that students can mentally visualize concepts but students often struggle with internal visualization skills--the ability to mentally visualize information. In order to address this…

The present paper evaluates the processes of reading acquisition in Latin from the component-skills approach and discusses how advances in reading in modern foreign languages could be adapted to the specific needs of Latin as a historical language. Compared to the holistic and socially embedded approaches to modern foreign language acquisition,…