This study is part of a research programme investigating the dynamics and impacts of learning engagement in a challenge-based digital learning environment. Learning engagement is a multidimensional concept which includes an individual's ability to behaviourally, cognitively, emotionally, and motivationally engage in an on-going learning process.…

Accurately modeling individual students' knowledge growth is important in many applications of learning analytics. A key step is to decompose the knowledge targeted in the instruction into detailed knowledge components (KCs). We search for an accurate KC model for basic equation solving skills, using data from an intelligent tutoring system (ITS),…

Many scholars have highlighted the importance of motivation and anxiety in language learning. They have also indicated the advantages of integrating learning content into a mobile-assisted English learning system environment. Meanwhile, a few studies have explored the impacts of a mobile-assisted English learning system on the motivation and…

MOOCs (Massive Open Online Courses) were first introduced to the wider public in 2008, with the first language MOOCs appearing in 2012. Following the initial hype, a number of problems with the way MOOCs had been conceived and implemented have emerged from research and practical experiences. In this article we revisit some of the arguments for and…

One of the major factors affecting student learning is feedback. Although the importance of feedback has been recognized in educational institutions, dramatic changes--such as bigger class sizes and a more diverse student population--challenged the provision of effective feedback. In light of these changes, educators have increasingly been using…

Distance computer-assisted learning is increasingly common, owing largely to the expansion and development of e-technology. Nevertheless, the available tools of the learning platforms have demonstrated their limits during the pandemic context, since many students, who were used to "face-to-face" education, got discouraged and dropped out…

Learning analytic models are built upon traces students leave in technology-enhanced learning platforms as the digital footprints of their learning processes. Learning analytics uses these traces of learning engagement to predict performance and provide learning feedback to students and teachers when these predictions signal the risk of failing a…

The author writes this letter to provide an update on assessment, accountability, and reporting requirements for the 2020-2021 school year. President Biden's first priority is to safely re-open schools and get students back in classrooms, learning face-to-face from teachers with their fellow students. To be successful once schools have re-opened,…

Aim/Purpose: Although many computer science measures have been proposed, visualizing individual students' capabilities is difficult, as those measures often rely on specific tools and methods or are not graded. To solve these problems, we propose a rubric for measuring and visualizing the effects of learning computer programming for elementary…

Many factors play a role in a students' learning experience, but students' course interaction behaviors are particularly important toward fostering success. Instructors build learning tools (such as videos, online quizzes, etc.) that provide students with the opportunity to extend their learning outside the classroom. These tools require students…

There is growing demand for online learning activities that offer flexibility for students to study anywhere, anytime, as online students fit study around work and family commitments. We designed a series of online activities and evaluated how, where, and with what devices students used the activities, as well as their levels of engagement and…

This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…

The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD). Despite the growing potential of LA in higher education (HE), the benefits are not yet convincing to the practitioner, in particular aspects of…

In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…

Purpose: Most educational assessments tend to be constructed in a close-ended format, which is easier to score consistently and more affordable. However, recent work has leveraged computation text methods from the information sciences to make open-ended measurement more effective and reliable for older students. This study asks whether such text…