In natural science education, experiments often lead to the collection of raw data that need to be processed into results by doing calculations. Teaching students how to approach such calculations can be done using digital learning materials that provide guidance. The goal of this study was to investigate students' behaviour regarding the use of…

This paper analyzes how learners interact with the pedagogical sequences of educational videos, and its effect on their performance. In this study, the suggested video courses are segmented on several pedagogical sequences. In fact, we're not focusing on the type of clicks made by learners, but we're concentrating on the pedagogical sequences in…

Non-compliance is a challenge for practitioners serving children with and without disabilities. Many interventions have been developed to increase compliance. High-probability request sequences (HPRS), an antecedent-based intervention that is based on behavioral momentum theory, is one way to increase compliant behavior. HPRS includes the…

The current study investigated students' gameplay behavioral patterns as a function of in-game learning supports delivery timing when played a computer-based physics game. Our sample included 134 secondary students (M = 14.40, SD = .90) from all over the United States, who were randomly assigned into three conditions: receiving instructional…

Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at…

High probability request (high-"p") sequences, based on the momentum of behavior principle, have been an effective intervention for improving compliance and work completion for students who display challenging behaviors. They have been portrayed as a low-intensity intervention because of being perceived as simple, clear, and easy for any…

Consistency of learning behaviors is known to play an important role in learners' engagement in a course and impact their learning outcomes. Despite significant advances in the area of learning analytics (LA) in measuring various self-regulated learning behaviors, using LA to measure consistency of online course engagement patterns remains largely…

Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…

Design is a key element of both the teaching and learning of engineering and technology. However, the process of engineering design has yielded limited research results. This study explored the iterative design process by searching for sequential design thinking patterns. The researchers collected nine concurrent think-aloud protocols from…

Open-ended learning environments (OELEs) allow students to freely interact with the content and to discover important principles and concepts of the learning domain on their own. However, only some students possess the necessary skills for efficient and effective exploration. Guidance in the form of targeted interventions or feedback therefore has…

The purpose of this non-experimental, quantitative study was to investigate the relationship of course-taking patterns of community college students enrolled in a major's biology sequence to successful transfer into a biology or biology-related degree track at four-year institutions. The research was guided by the seminal work of Adelman (1999,…

This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…

One of the most challenging tasks in the field of Educational Data Mining (EDM) is to cluster students directly based on system-student sequential moment-to-moment interactive trajectories. The objective of this study is to build a general temporal clustering framework that captures the distinct characteristics of students' sequential behaviors…

This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

Collaborative learning has long been proved to be a crucial agent for enhancing students' social skills, problem-solving abilities and individual learning performance. Understanding how students move from one phase to another in their collaboration process can inform educators of how best to facilitate such learning. However, this is still an area…