Intelligent learning technologies are often applied within the educational industries. While these technologies can be used to create learning experiences tailored to an individual student, they cannot address students' affect accurately and quickly during the learning process. This paper focuses on two core research questions. How do students…

Solving mathematical (math) word problems (MWP) automatically is a challenging research problem in natural language processing, machine learning, and education (learning) technology domains, which has gained momentum in the recent years. Applications of solving varieties of MWPs can increase the efficacy of teaching-learning systems, such as…

Twenty-first century literacy includes a mixture of digital and print literacy skills and strategies. AutoTutor for Adult Reading Comprehension is a web-based intelligent tutoring system that is designed to help adult learners develop effective reading comprehension strategies. Lessons span basic reading skills (vocabulary, word parts),…

Twenty-first century literacy includes a mixture of digital and print literacy skills and strategies. AutoTutor for Adult Reading Comprehension is a web-based intelligent tutoring system that is designed to help adult learners develop effective reading comprehension strategies. Lessons span basic reading skills (vocabulary, word parts),…

Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines item response theory (IRT) with a deep learning method, provides superior performance. It can express the abilities of each student…

Self-regulation helps students develop various cognitive, metacognitive, and affective strategies to regulate their learning process and maximize learning gains. However, self-regulation demands i) an encouraging environment and ii) student motivation. First, adding Open Learner Models (OLM) to learning environments encourages self-regulation by…

Twenty-first-century skills should be integrated into higher education to prepare students for complex working-life challenges. Artificial intelligence (AI)-powered tools have the potential to optimise skill development among higher education students. Therefore, it is important to conceptualise relevant affordances of AI systems for 21st-century…

Randomized A/B tests within online learning platforms enable us to draw unbiased causal estimators. However, precise estimates of treatment effects can be challenging due to minimal participation, resulting in underpowered A/B tests. Recent advancements indicate that leveraging auxiliary information from detailed logs and employing design-based…

Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…

An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…

With the urgent shift to distance learning due to Covid-19 measures, educational institutions around the world have started to adopt e-learning massively. According to many experts, artificial intelligence (AI) may provide both system-wide and pedagogical solutions to the problems which the administrators, educators, and students encounter during…

Due to the advances of artificial intelligence (AI) and natural language processing, new kinds of Internet-based writing tools have emerged. Among other things, these AI-powered writing tools can be used by students for text translation, to improve spelling or for rewriting and summarizing texts. On the one hand, they can provide detailed…

Learners' choices as to whether and how to use visual representations during learning are an important yet understudied aspect of self-regulated learning. To gain insight, we developed a "choice-based" intelligent tutor in which students can choose whether and when to use diagrams to aid their problem solving in algebra. In an…

To provide personalized support on educational platforms, it is crucial to model the evolution of students' knowledge states. Knowledge tracing is one of the most popular technologies for this purpose, and deep learning-based methods have achieved state-of-the-art performance. Compared to classical models, such as Bayesian knowledge tracing, which…

We studied ALEKS PPL placement scores, SAT scores, and entry-course grades for a population of 1659 students who placed into College Algebra or below over a span of 5 years. In addition to representing an understudied range of placement level, the study was conducted at an HBCU with majority Black/African American students, a demographic that is…