Analytics of self-regulated learning scaffolding: effects on learning processes.

Self-regulated learning (SRL) is the ability to regulate cognitive, metacognitive, motivational, and emotional states while learning and is posited to be a strong predictor of academic success. It is therefore important to provide learners with effective instructions to promote more meaningful and effective SRL processes. One way to implement SRL instructions is through providing real-time SRL scaffolding while learners engage with a task. However, previous studies have tended to focus on fixed scaffolding rather than adaptive scaffolding that is tailored to student actions. Studies that have investigated adaptive scaffolding have not adequately distinguished between the effects of adaptive and fixed scaffolding compared to a control condition. Moreover, previous studies have tended to investigate the effects of scaffolding at the task level rather than shorter time segments-obscuring the impact of individual scaffolds on SRL processes. To address these gaps, we (a) collected trace data about student activities while working on a multi-source writing task and (b) analyzed these data using a cutting-edge learning analytic technique- ordered network analysis (ONA)-to model, visualize, and explain how learners' SRL processes changed in relation to the scaffolds. At the task level, our results suggest that learners who received adaptive scaffolding have significantly different patterns of SRL processes compared to the fixed scaffolding and control conditions. While not significantly different, our results at the task segment level suggest that adaptive scaffolding is associated with earlier engagement in SRL processes. At both the task level and task segment level, those who received adaptive scaffolding, compared to the other conditions, exhibited more task-guided learning processes such as referring to task instructions and rubrics in relation to their reading and writing. This study not only deepens our understanding of the effects of scaffolding at different levels of analysis but also demonstrates the use of a contemporary learning analytic technique for evaluating the effects of different kinds of scaffolding on learners' SRL processes.

Investigating learning processes through analysis of navigation behavior using log files.

The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining can predict learning outcomes. This work aims to provide support for learners and instructors regarding efficient learning with computer-based learning environments (CBLEs). We evaluated log file and questionnaire data from students (N = 58) who used a CBLE for two weeks. Results show a significant learning increase after studying with the CBLE with a very high effect size (p < .001, g = 1.71). A cluster analysis revealed two groups with significantly different learning outcomes accompanied by different navigation patterns. The time spent on learning-relevant pages and the interactivity with a CBLE are meaningful indicators for Recall and Transfer performance. Our results show that navigation behaviors indicate both beneficial and detrimental learning processes. Moreover, we could demonstrate that navigation behaviors impact the learning outcome. We present an easy-to-use approach for learners as well as instructors to promote successful learning by tracking the duration spent in a CBLE and the interactivity.

Temporal Assessment of Self-Regulated Learning by Mining Students' Think-Aloud Protocols.

It has been widely theorized and empirically proven that self-regulated learning (SRL) is related to more desired learning outcomes, e.g., higher performance in transfer tests. Research has shifted to understanding the role of SRL during learning, such as the strategies and learning activities, learners employ and engage in the different SRL phases, which contribute to learning achievement. From a methodological perspective, measuring SRL using think-aloud data has been shown to be more insightful than self-report surveys as it helps better in determining the link between SRL activities and learning achievements. Educational process mining on the basis of think-aloud data enables a deeper understanding and more fine-grained analyses of SRL processes. Although students' SRL is highly contextualized, there are consistent findings of the link between SRL activities and learning outcomes pointing to some consistency of the processes that support learning. However, past studies have utilized differing approaches which make generalization of findings between studies investigating the unfolding of SRL processes during learning a challenge. In the present study with 29 university students, we measured SRL via concurrent think-aloud protocols in a pre-post design using a similar approach from a previous study in an online learning environment during a 45-min learning session, where students learned about three topics and wrote an essay. Results revealed significant learning gain and replication of links between SRL activities and transfer performance, similar to past research. Additionally, temporal structures of successful and less successful students indicated meaningful differences associated with both theoretical assumptions and past research findings. In conclusion, extending prior research by exploring SRL patterns in an online learning setting provides insights to the replicability of previous findings from online learning settings and new findings show that it is important not only to focus on the repertoire of SRL strategies but also on how and when they are used.

Can driver education be improved by computer based training of cognitive skills?

Deficits in cognitive skills, such as hazard perception, appear to have a tremendous influence on accident involvement of younger drivers. However, conventional forms of driver training have largely failed to build skills that extend beyond the provision of a descriptive knowledge of how to drive. Computer based training (CBT) has the potential to provide new ways to deal with this problem. In this study, a CBT module was developed to complement existing driver training programs by addressing critical cognitive skills. The CBT made use of video sequences of potentially hazardous driving situations, including multiple-choice questions with adaptive feedback, to increase levels of elaboration and understanding. To test effects, a sample of learner drivers completed either CBT, paper based training with similar content, or no training at all. A simulator experiment confirmed that CBT participants exhibited earlier glances towards critical cues and relevant areas in the visual field than participants of the other two groups. It is concluded that CBT can potentially assist instruction of cognitive skills necessary for save driving.

Accuracy of confidence judgments: stability and generality in the learning process and predictive validity for learning outcome.

One aspect of metacognition is the monitoring of memory or comprehension measured with retrospective confidence judgments after test taking. The research questions of the present study were whether different measures for the accuracy of such confidence judgments are stable over learning time, whether they generalize over two different tests, and whether they predict the learning outcome. In order to answer these questions, a study was conducted in which university students (N = 113) learned about the basic concepts of operant conditioning for 30 min. Knowledge tests with confidence judgments presented after each item were obtained before learning, after 10 min, and at the end of the learning session. Bias and absolute bias were calculated as absolute measures of accuracy, and gamma, Pearson's r, and d(a) were calculated as relative measures of accuracy. The results showed that the absolute measures were stable, but that the relative measures were not. Furthermore, absolute bias, gamma, and Pearson's r obtained 10 min after the beginning of the learning process predicted the learning outcome. The results are discussed with regard to research on different measures of accuracy for confidence judgments.