Metacognition is the engine of self-regulated learning. At the object level, learners seek information and choose learning tactics and strategies they forecast will develop knowledge. At the meta level, learners gather and analyze data about learning events to draw conclusions, such as: Is this tactic a good fit to conditions? Was it effective?…

This special issue presents a sample of modern work on self-regulated learning (SRL) among high ability and gifted students. It includes diverse views about the construct per se, and gifted students' and their teachers' accounts about SRL and factors they believe moderate it. Zeidner and Stroeger (this issue) set the stage with a sketch of an…

Data used in learning analytics rarely provide strong and clear signals about how learners process content. As a result, learning as a process is not clearly described for learners or for learning scientists. Gaševic, Dawson, and Siemens (2015) urged data be sought that more straightforwardly describe processes in terms of events within learning…

Background: Deep versus surface knowledge is widely discussed by educational practitioners. A corresponding construct, levels of processing, has received extensive theoretical and empirical attention in learning science and psychology. In both arenas, lower levels of information and shallower levels of processing are predicted and generally…

When learners highlight or tag content, they metacognitively monitor information to select and mark it. From a levels-of-processing framework, standards used in metacognitive monitoring could affect learning. We examined effects on recall and transfer of different metacognitive standards -- free highlighting expressing a generic…

Learning analytics are often formatted as visualisations developed from traced data collected as students study in online learning environments. Optimal analytics inform and motivate students' decisions about adaptations that improve their learning. We observe that designs for learning often neglect theories and empirical findings in learning…

The trajectory of scholarship about self-regulated learning (SRL) originates in mid-19th-century writings about learners' sense of responsibility in self education. Although Descartes's 17th-century writings implied mental activities consistent with metacognition, a central feature of SRL, these were inarticulate until Flavell and colleagues'…

New methods for gathering and analyzing data about events that comprise self-regulated learning (SRL) support discoveries about patterns among events and tests of hypotheses about roles patterns play in learning. Five such methodologies are discussed in the context of four key questions that shape investigations into patterns in SRL. A framework…

Our article introduces the "Journal of Educational Data Mining's" Special Issue on Educational Data Mining on Motivation, Metacognition, and Self-Regulated Learning. We outline general research challenges for data mining researchers who conduct investigations in these areas, the potential of EDM to advance research in this area, and…

In theoretical models of self-regulated learning, calibration is one important component in successful learning. Two issues of calibration are explored. First, Nelson (1987) suggested the "G" (gamma) coefficient is the most appropriate measure of calibration (judgment accuracy) and rejected signal detection theory's "d'"…

Articles in this special issue present recent advances in using state-of-the-art software systems that gather data with which to examine and measure features of learning and particularly self-regulated learning (SRL). Despite important advances, there remain challenges. I examine key features of SRL and how they are measured using common tools. I…

Researching self-regulated learning (SRL) as a process that evolves across multiple episodes of studying poses large methodological challenges. While self-report data provide useful information about learners' perceptions of learning, these data are not reliable indicators of studying tactics learners actually use while studying, especially when…

How students develop forms for self-regulating learning is explored. It is suggested that they experiment, bootstrapping newer forms of self-regulated learning from prior forms. Obstacles are obtaining sufficient practice, remembering how learning was enacted, and reasoning about factors that affect learning. (SLD)

Calibration concerns (a) the deviation of a person's judgment from fact, introducing notions of bias and accuracy; and metric issues regarding (b) the validity of cues' contributions to judgments and (c) the grain size of cues. Miscalibration hinders self-regulated learning (SRL). Considering calibration in the context of Winne and Hadwin's…

In the context of continued growth in the accessibility of information through the internet, recent advances in theories of self-regulated learning present an opportunity to reexamine how learners work with networked resources in constructivist approaches such as problem-based learning, project-­based learning, and collaborative problem solving.…