Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…

In recent years, the integration of big data and learning analytics has emerged as a significant trend across educational systems worldwide. The implementation of such technologies within universities -- particularly in China -- holds considerable potential for transforming teaching and learning practices. By enabling personalised, data-driven…

Background: It is vital to understand students' Self-Regulatory Learning (SRL) processes, especially in Blended Learning (BL), when students need to be more autonomous in their learning process. In studying SRL, most researchers have followed a variable-oriented approach. Moreover, little has been known about the unfolding process of students' SRL…

An essential part of making dashboards more effective in motivating students and leading to desirable behavioural change is knowing what information to communicate to the student and how to frame and present it. Most of the research studying dashboards' impact on learning analyzes learning indicators of students as a group. Understanding how a…

With the current shift in educational settings to blended and flipped classroom and the introduction of learning management systems (LMS) such as Moodle, it is no surprise big data has found its place in education and is predicted to be extensively implemented in institutions of higher education (Johnson et al., 2013). In a flipped classroom…

The attribution of learning success or failure is crucial for students' learning and motivation. Effective attribution of their learning success or failure in the context of a small private online course (SPOC) could generate students' motivation toward learning success while an incorrect attribution would lead to a sense of helplessness. Based on…

In this study, we analyzed student participation and success in a college-level Calculus I course that utilized standards-based grading. By measuring the level to which students participate in this class structure, we were able to use a clustering algorithm that revealed multiple groupings of students that were distinct based on activity…

The National College English Test Band 4 (CET-4) is a key test to assess the English language ability of Chinese university students, and the success rate of the test is important to improve the quality of their English learning. Artificial intelligence technology can be used to predict and explore the factors influencing the success rate. This…

Within digitally-supported learning environments, learners need to observe themselves so that they can reflect on their strengths and weaknesses and take a step toward autonomous learning. Within the scope of this research, a technology and analytics enhanced assessment environment in which students can assess themselves was implemented and…

Research and development in learning analytics has established viable solutions for scaling personalised feedback to all students. However, questions remain regarding how such feedback is perceived, interpreted and acted upon by stakeholders. The present study reports on the analysis of focus group data from four courses to understand students'…

Purpose: The aims of this study are to examine affective responses of university students when viewing their own predictive learning analytics (PLA) dashboards, and to analyse how those responses are perceived to affect their self-regulated learning behaviour. Design/methodology/approach: A total of 42 Northern Irish students were shown their own…

Based on the achievement goal theory, this experimental study explored the influence of predictive and descriptive learning analytics dashboards on graduate students' motivation and statistics anxiety in an online graduate-level statistics course. Participants were randomly assigned into one of three groups: (1) predictive dashboard; (2)…

How can we best facilitate students most in need of learning support, entering a challenging quantitative methods module at the start of their bachelor programme? In this empirical study into blended learning and the role of assessment for and as learning, we investigate learning processes of students with different learning profiles.…

Extensive studies have been conducted to diagnose and predict students' academic performance by analyzing a large amount of data related to their learning behaviors in a blended learning environment. But there is a lack of research examining how individualized learning interventions could improve students' academic performance in such a learning…

Purpose: Short-term motivation encompasses specific, challenging and attainable goals that develop in the limited timespan. On the other hand, long-term motivation indicates a sort of continuing commitment that is required to complete assigned task. As short-term motivational problems span for a limited period of time, such as a session,…