This paper provides an experience report on a co-design approach with teachers to co-create learning analytics-based technology to support problem-based learning in middle school science classrooms. We have mapped out a workflow for such applications and developed design narratives to investigate the implementation, modifications and temporal…

This article queries how learning analytics systems can support content-specific group formation to develop students' thinking about a specific mathematical concept. Automated group formation requires identifying personal characteristics, designing tasks to probe students' perceptions, and grouping them to increase individual learning chances.…

Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…

This study explores how the use of learning analytics (LA) visualizations to eliciting examples tasks (EET) on the topic of functions can shape middle school mathematics teachers' formative assessment (FA) practices. Teachers' practices were examined when provided with LA visualizations, offering them an interactive analysis of their students'…

This study explores the application of the task-based teaching method in English education, particularly from the perspective of big data. Traditional English teaching models often fail to meet the diverse needs of students, with the task-based approach, despite being student-centered, encountering challenges such as task difficulty control and…

Many U.S. districts are investing in education technologies to improve student learning. Yet, when technologies with established promise of evidence are deployed at scale, they frequently encounter challenges that compromise their efficacy. MathSpring is a technology-based math learning platform that offers personalized content, remedial tutoring,…

This study analyses the potential of a learning analytics (LA) based formative assessment to construct personalised teaching sequences in Mathematics for 5th-grade primary school students. A total of 127 students from Spanish public schools participated in the study. The quasi-experimental study was conducted over the course of six sessions, in…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…

Self-regulated learning (SRL) is a critical component of mathematics problem solving. Students skilled in SRL are more likely to effectively set goals, search for information, and direct their attention and cognitive process so that they align their efforts with their objectives. An influential framework for SRL, the SMART model, proposes that…

This paper explores how learning analytics data provided by a math problem-solving educational technology platform informed 5th and 6th grade teachers' instructional decisions around socioemotional learning (SEL). MathSpring is an educational technology tool that provides teachers with data on students' effort, progress, and emotions while…

This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried…

Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods (k-means clustering, data visualization) to…

Online educational games have been widely used to support students' mathematics learning. However, their effects largely depend on student-related factors, the most prominent being their behavioral characteristics as they play the games. In this study, we applied a set of learning analytics methods ("k"-means clustering, data…

Providing high-level support to students on NGSS inquiry practices can be challenging; however, teacher dashboards can help teachers provide just-in-time instruction to students, both in-person and online. Prior work has shown some success with a dashboard that alerts teachers in real time on students' science inquiry difficulties, but teachers…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…