This study investigates how teachers use dashboards in primary school classrooms. While learners practice on a tablet real-time data indicating learner progress and performance is displayed on teacher dashboards. This study examines how teachers use the dashboards, applying Verberts' learning analytics process model. Teacher dashboard consultations and resulting pedagogical actions were observed in 38 mathematics lessons. In stimulated recall interviews, the 38 teachers were asked to elaborate on how they reflect on and make sense of the information on the dashboard. The results showed that teachers consulted the dashboard on average 8.3 times per lesson. Teachers activated existing knowledge about students and the class to interpret dashboard information. Task and process feedback were the pedagogical actions most often used following dashboard consultation. Additionally, teachers who consulted the dashboard more often activated more and more diverse pedagogical knowledge to interpret the data and, consequently, gave more and more diverse feedback. These results indicated that teacher dashboards were indeed influencing teachers' pedagogical actions in their daily classroom activities. This study provided the first evidence that dashboards progressively impact teaching practice and initiate more profound behavioral changes as teachers become more proficient in using them.
Extending past research showing that regulative activities (metacognitive and relational) can aid learning, this study tests whether sequences of cognitive, metacognitive and relational activities affect subsequent cognition. Scaffolded by a computer avatar, 54 primary school students (working in 18 groups of 3) discussed writing a report about a foreign country for 51,338 turns. Statistical discourse analysis (SDA) of these sequences of talk showed that after low cognition, high cognition, planning or evaluation, both low and high cognition were more likely (some effects lasted 6 conversation turns). After monitoring or positive relational activities (confirm, engage), low cognition was more likely. After a denial however, high cognition was less likely. These results suggest that metacognitive planning organizes subsequent cognitive activities and facilitates the transition between acquisition of knowledge and meaning making, while relational activities help enact them. These insights can inform micro-temporal theories of social regulation and shared knowledge construction.
Many students in primary education learn mathematics using adaptive learning technologies (ALTs) on tablets every day. Driven by developments in the emerging field of learning analytics, these technologies adjust problems based on learners' performance. Yet, until now it is largely unclear how students regulate their learning with ALTs. Hence, we explored how learners regulate their effort, accuracy and learning with an ALT using moment-by-moment learning curves. The results indicated that moment-by-moment learning curves did reflect students' accuracy and learning, but no associations with effort were found. Immediate drops were associated with high prior knowledge and suboptimal learning. Immediate peaks were associated with robust learning and pointed to effective student regulation. Close multiple spikes showed moderate learning and lower initial levels of accuracy but, with system support, these students seemed able to regulate their learning. Separated multiple spikes indicated reduced learning and accuracy and potentially signal the inability of students to regulate their learning. In this light, moment-by-moment learning curves seem to be valuable indicators of accuracy regulation during learning with ALTs and could potentially be used in interventions to support SRL with personalized visualizations.
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