Learning in Massive Open Online Courses (MOOCs) requires learners to self-regulate their learning process or receive effective self-regulated learning (SRL) interventions to accomplish personal goals. Much attention has thus been paid to how SRL influences learner performance in MOOCs, but research has overlooked a person-centered analysis of how…

In this article, we leverage data from over 1,000 students participating in two different online courses to investigate whether better learning outcomes are associated with student decisions to practice instead of (re-)reading. Consistent with laboratory and classroom findings, we find that students' decisions to practice are related to better…

Background: The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.…

Background: Failure to effectively organize and manage learning time is an important factor influencing online learners' performance. Investigation of time-investment patterns for online learning will provide educators with useful knowledge of how learners engage in and regulate their online learning and support them in tailoring online course…

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)…

The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…

The large-scale and granular interaction data collected in online learning platforms such as massive open online courses (MOOCs) provide unique opportunities to better understand individuals' learning processes and could facilitate the design of personalized and more effective support mechanisms for learners. In this paper, we present two…

Purpose: This study explores ongoing research into self-mapped learning pathways that students utilize to move through a course when given two modalities to choose from: one that is instructor-led and one that is student-directed. Design/methodology/approach: Process mining analysis was utilized to examine and cluster clickstream data from an…

Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning…

This study investigated student learning behaviors in a fully online psychology course in which students controlled their own course content usage. Data collection included students' real usage of the Blackboard course site over three semesters in 2014 and 2015, as well as a course survey at the end of each semester. Data mining techniques, such…