Abstract
Integrating collaborative settings in mathematics classrooms is challenging. The main challenge concerns adaptive guidance—guidance that takes into account the needs of learners. This adaptive guidance depends on the teacher’s understanding of the progression of group work. Understanding this progression when the teacher organizes several groups in a classroom towards conceptual understanding has been impracticable so far. In this paper, we present an environment, the System for Advancing Group Learning in Educational Technologies (SAGLET), which is based on the Virtual Math Teams (VMT) environment. This environment allows teachers to observe multiple groups engaging in problem-solving in geometry. SAGLET relies on the theoretical idea of critical moments in group learning, events whose occurrence may enable or impair co-construction of meanings. We conjecture that the teacher’s identification of critical moments may facilitate further guidance towards conceptual learning among students. Machine learning techniques provide online alerts about critical moments. We checked whether 11 teachers looking at multiple groups working in parallel better understand the progression of group work, upon being informed about critical moments. The results indicate that teachers use alerts about critical moments to understand better the progression of parallel groups but that informing them about critical moments sometimes impairs their observations.
Zusammenfassung
Die Integration kooperativer Lehr-Lern-Arrangements in den Mathematikunterricht ist mit diversen Herausforderungen verbunden. Eine zentrale Herausforderung dabei stellt die adaptive Unterstützung der Lernenden dar, die auf die individuellen Bedürfnisse zugeschnitten ist. Um Kleingruppen adaptiv unterstützen zu können, ist es entscheidend, dass die Lehrkraft einen Einblick in den Arbeitsfortschritt der einzelnen Kleingruppen erlangt. Vertiefte Einblicke in das Kooperationsgeschehen von mehreren, zeitgleich arbeitenden Kleingruppen zu gewinnen, um diese hinsichtlich ihres konzeptuellen Wissenserwerb fördern zu können, war bisher kaum möglich. In diesem Beitrag präsentieren wir die Lehr-Lern-Umgebung „System for Advancing Group Learning in Educational Technologies (SAGLET)“, die auf die Umgebung „Virtual Math Teams (VMT)“ aufbaut. SAGLET erlaubt es Lehrenden, mehrere Gruppen gleichzeitig beim Lösen von Geometrieaufgaben zu beobachten. SAGLET basiert auf der Idee, dass es bestimmte kritische Momente während einer Gruppenarbeit gibt, die entscheidend für eine erfolgreiche Wissens-Ko-Konstruktion während der Aufgabenbearbeitung sind. Wir gehen davon aus, dass Lehrkräfte den Erwerb von konzeptuellem Verständniswissen besser unterstützen können, wenn sie in der Lage ist, solche kritischen Momente zu identifizieren. Mithilfe von Machine Learning-Verfahren können Lehrende über kritische Momente während der Zusammenarbeit von SuS informiert werden. In einer Studie mit 11 Lehrkräften wurde untersucht, ob diese den Arbeitsfortschritt von mehreren parallel arbeitenden Kleingruppen besser einschätzen können, wenn sie vom System auf kritische Momente während der Zusammenarbeit hingewiesen werden. Aus den Ergebnissen geht hervor, dass Lehrende die Benachrichtigungen über kritische Momente nutzen können, um den Fortschritt der parallel arbeitenden Gruppen besser nachzuvollziehen. In einigen Fällen beeinträchtigten die Systemhinweise jedoch die eigenen Beobachtungen der Lehrkräfte.
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Notes
The technoglical design of SAGLET allows teachers to open any number of virtual rooms as they wish, however, the optimal number of virtual rooms should be explored in further research.
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Swidan, O., Prusak, N., Livny, A. et al. Fostering teachers’ understanding of progression of multiple groups towards the orchestration of conceptual learning. Unterrichtswiss 47, 159–176 (2019). https://doi.org/10.1007/s42010-019-00050-x
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DOI: https://doi.org/10.1007/s42010-019-00050-x