Designing for the co-Orchestration of Social Transitions between Individual, Small-Group and Whole-Class Learning in the Classroom

Educational technologies are often developed such that students work on specific social levels (e.g., individual, small group, whole class) at specific times. However, in the reality of the classroom, learning activities are not so cleanly divided, with transitions occurring between social levels for students at different times. To support these social transitions in a way that can promote student learning, we need to lower the teacher’s orchestration load around managing fluid social transitions. Co-orchestration, in which the orchestration decisions are shared between different parties, can help to lower the orchestration load when it is designed according to the teacher’s values and classroom culture. In this paper, we present a taxonomy of social transitions and investigate how the responsibilities of orchestration can be divided between primary school teachers and a co-orchestration system in order to support the extension from rigid social transitions to fluid transitions in technology-enhanced classrooms. Across two studies, we used a design process involving co-design and prototyping with teachers. We uncovered and refined co-orchestration design desires that balance teachers’ orchestration loads while providing them with a sense of control. We present six design desires for maintaining a balance between teacher and system responsibilities regarding the orchestration of social transitions that can be implemented, such as in our mid-fidelity prototype, to support the range of social transitions. The list of desires contributes to co-orchestration research and more broadly technology design for classrooms by highlighting the changing balance of teacher control depending on what is the focus of the orchestration support.

An integrated way of using a tangible user interface in a classroom

Sébastien Cuendet, Pierre Dillenbourg

Despite many years of research in CSCL, computers are still scarcely used in classrooms today. One reason for this is that the constraints of the classroom environment are neglected by designers. In this contribution, we present a CSCL environment designed for a classroom usage from the start. The system, called TapaCarp, is based on a tangible user interface (TUI) and was designed to help train carpenter apprentices. A previous study (Cuendet and Dillenbourg 2013) showed that the tangible nature of TapaCarp helped integrate it in the classroom environment, but that this did not guarantee a meaningful learning activity. In this article, we describe the process that led us to design a new learning classroom activity for the particular context of dual carpentry apprenticeships. One innovative aspect of the activity is that TapaCarp is used only for a small part of it. This contrasts with the mainstream CSCL approach that assumes that the system must be used from beginning to end of the activity. This new activity was used in a classroom study with 3 classes of carpenter apprentices over two days for each class. Despite its many steps, the activity proved usable and fostered many connections to the workplace, which was one of its main purposes. The teacher and the students were positive and showed high engagement in the activity. The learning gain results were mixed: the performance of the students improved from day 1 to day 2, but the learning gain measured with a pre-test/post-test mechanism did not show any significant difference compared to that of a control group.

Springer2015

A Bayesian Model of Individual Differences and Flexibility in Inductive Reasoning for Categorization of Examples

Pierre Dillenbourg, Louis Pierre Faucon, Jennifer Kaitlyn Olsen

Inductive reasoning is an important educational practice but can be difficult for teachers to support in the classroom due to the high level of preparation and classroom time needed to choose the teaching materials that challenge students' current views. Intelligent tutoring systems can potentially facilitate this work for teachers by supporting the automatic adaptation of examples based on a student model of the induction process. However, current models of inductive reasoning usually lack two main characteristics helpful to adaptive learning environments, individual differences of students and tracing of students' learning as they receive feedback. In this paper, we describe a model to predict and simulate inductive reasoning of students for a categorization task. Our approach uses a Bayesian model for describing the reasoning processes of students. This model allows us to predict students' choices in categorization questions by accounting for their feature biases. Using data gathered from 222 students categorizing three topics, we find that our model has a 75% accuracy, which is 10% greater than a baseline model. Our model is a contribution to learning analytics by enabling us to assign different bias profiles to individual students and tracking these profile changes over time through which we can gain a better understanding of students' learning processes. This model may be relevant for systematically analysing students' differences and evolution in inductive reasoning strategies while supporting the design of adaptive inductive learning environments.

ASSOC COMPUTING MACHINERY2020

Technology for Classroom Orchestration

Pierre Dillenbourg, Patrick Jermann

We use different criteria to judge teaching methods and learning environments as researchers and teachers. As researchers, we tend to rely on learning gains measured in controlled conditions. As teacher, the skilled management of classroom constraints results in the impression that a specific design “works well”. We describe fourteen design factors related to the metaphors of classroom orchestration and education ecosystems and illustrate their embodiment in three learning environments. These design factors provide a teacher-centric, integrated view of educational technologies in the classroom. We expand this list of factors to include the main constraints that designers should consider to address the difficult methodological issue of generalizing research results about the effectiveness of methods and designs.

Springer Science+Business Media2010