Knowledge tracing aims to model and predict students' knowledge states during learning activities. Traditional methods like Bayesian Knowledge Tracing (BKT) and logistic regression have limitations in granularity and performance, while deep knowledge tracing (DKT) models often suffer from lacking transparency. This paper proposes a…

The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…

With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

Technology and data analysis have evolved into a resource-rich tool for collecting, researching and comparing student achievement levels in the classroom. There are sufficient resources to discover student success through data analysis by routinely collecting extensive data on student behaviour and curriculum structure. Educational Data Mining…

Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…

Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…

Online education is an important component of education reform and one of the important learning modes in today's society, which can achieve the goal of learning anytime, anywhere and for everyone. Therefore, this paper constructs an analysis model of online education course emotional perception and course resource integration based on new media…

Implementation of a culturally responsive positive behavioral interventions and supports (PBIS) framework is associated with positive outcomes for secondary students when implemented schoolwide. Yet, educators often report more implementation challenges in secondary school as compared to elementary school settings. Difficulties obtaining student…

Hands-on cybersecurity training allows students and professionals to practice various tools and improve their technical skills. The training occurs in an interactive learning environment that enables completing sophisticated tasks in full-fledged operating systems, networks, and applications. During the training, the learning environment allows…

Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…

In classrooms, some transitions between activities impose (quasi-)synchronicity, meaning there is a need for learners to move between activities at the same time. To make real-time decisions about when to move to the next activity, teachers need to be able to balance the progress of their students as they work at different paces. In this paper, we…

This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…

We introduce DeepPerfEmb, or DPE, a new deep-learning model that captures dense representations of students' online behaviour and meta-data about students and educational content. The model uses these representations to predict student performance. We evaluate DPE on standard datasets from the literature, showing superior performance to the…

Purpose: This report highlights ways in which race-based data can be used to combat systemic racism in matters relating to academic and non-academic and student misconduct. Methods: Information synthesis of available information relating to race-based data and student conduct. Results: A summary and synthesis of how and why race-based data can be…

Arguably one of the most valuable tools for investigating pupil behaviour in an educational environment is systematic classroom observation. Classroom observation is often cited as having the potential to enable research of the learning process in action. Low inference classroom observation instruments are designed to record a sequence of data…