This edited volume presents the latest research focussing on current challenges on the deployment of smart technologies and pedagogies for supporting teaching and learning in the post-covid19 era. This is at the core of studying the evolution of the learning process, the role of technology-supported pedagogical approaches, and the progress of…

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)…

Videos created with the hands of teachers filmed have been perceived as useful educational resource for students of Physics in undergraduate courses. In previous works, we analyzed the students' perception about educational videos by asking them about their experiences. In this work, we analyze the same facts, but from a learning analytics…

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…

Instruction in many STEM domains heavily relies on visual representations, such as graphs, figures, and diagrams. However, students who lack representational competencies do not benefit from these visual representations. Therefore, students must learn not only content knowledge but also representational competencies. Further, as learning…

The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…

A major problem faced by instructors post-implementation of unsupervised online assessments is that they may lack real-time access to the students' actual learning behaviors. Limitations in student-feedback, limited know-how of accessing and analyzing log data, and large class sizes could restrict instructors' access to learners' behaviors. This…

Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…

In this paper, six interviews with course coordinators from two mathematics departments are analysed to better understand the relationship between course coordination and local data in the Precalculus to Calculus 2 sequence with respect to online grading platforms. We highlight several potential coordinator decisions and present illustrative…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

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…

Background: Data-driven educational technology solutions have the potential to support teachers in different tasks, such as the designing and orchestration of collaborative learning activities. When designing, such solutions can improve teacher understanding of how learning designs impact student learning and behaviour; and guide them to refine…

This study explored the impact of integrating ChatGPT into asynchronous online discussions. The analysis encompassed students' log data from Canvas and their perspectives on using ChatGPT. Results revealed a significant enhancement in overall discussion participation when ChatGPT is encouraged, emphasizing its potential as a catalyst for…

This book explores and further expands on the rich history of theoretical and empirical research in open and distributed learning, and addresses the impact of the "data revolution" and the emergence of learning analytics on this increasingly diverse form of educational delivery. Following an introductory chapter that maps the book's…

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…