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.

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.

Inquiry-Based Learning and Conceptual Change in Balance Beam Understanding.

Inquiry-based learning has the potential to foster conceptual change, but whether it can induce an advancement in strategy use is not yet known. Such an advancement seems plausible, because conceptual change can be reflected in the use of new strategies. Whether inquiry-based learning leads to advancement in strategy use can be tested with strategy-based tests, such as the balance beam test. Distinct strategies have been proposed and identified for this test. Therefore, the present study compared response patterns on the balance beam test before and after an inquiry-based lesson. The experimental condition completed a digital inquiry-based lesson about the balance beam (n = 113), and the control condition completed a similar inquiry-based lesson but investigated a different topic (n = 44). The participants were aged 8-13 years old and were unfamiliar with the law of moments. The balance beam test (pretest and posttest) consisted of 25 items. Overall accuracy in solving balance beam problems improved after the inquiry-based lesson in the balance beam (BB) condition but not in the control condition. Classes, identified with latent transition analysis (LTA), appeared to be globally in line with previously identified strategies in the balance beam test. Condition was entered as a covariate in the LTA to identify which changes in strategy use could be attributed to the experimental intervention. First, changes from pretest to posttest were found, which supported that a change in strategy use occurred in some children. Second, there were more improvements in the BB condition, and these improvements indicated larger gains compared to the control condition. This means that in science education, it is important to map out prior knowledge and its effect on learning paths. Overall, results suggested that conceptual change could be measured as a change in strategy use and modeled with LTA to reveal that 26% of the children showed conceptual change after a single inquiry-based lesson.