Distributed Awareness for Class Orchestration

The orchestration process consists of managing classroom interactions at multiple levels: individual activities, teamwork and class-wide sessions. We study the process of orchestration in recitation sections, i.e. when Students work on their assignments individually or in small groups with the presence of: teaching assistants who give help on demand. Our empirical study revealed that recitation sections suffer from inefficient orchestration. Too much attention is devoted to the management of the relationship between Students and teaching assistants, which prevent both sides from concentrating on their mail) task. We present a model of students' activities during recitation sections that emphasize the issue Of Mutual awareness, i.e. monitoring help needs and TA's availability. To tackle these difficulties, we developed two awareness tools. Both tools convey the same information: which exercise each group is working on, whether it has asked for help and for how long. In the centralized version, named Shelf, students provide information with a personal response system and the Status Of each team is juxtaposed on a central display. In the distributed version, named Lantern, each team provides information by interacting with a lamp placed oil its table. The display is distributed over the classroom, the information being spatially associated to each group. We are now comparing these two versions ill an empirical study with two first year undergraduate classes in Physics. Preliminary results show that both versions increase the efficiency of interaction between students and teaching assistants. This contribution focused on the distributed version.

Pierre Dillenbourg, Frédéric Kaplan, Hamed Seiied Alavi

The orchestration process consists of managing classroom interactions at multiple levels: individual activities, teamwork and class-wide sessions. We study the process of orchestration in recitation sections, i.e. when students work on their assignments individually or in small groups with the presence of teaching assistants who give help on demand. Our empirical study revealed that recitation sections suffer from inefficient orchestration. Too much attention is devoted to the management of the relationship between students and teaching assistants, which prevent both sides from concentrating on their main task. We present a model of students’ activities during recitation sections that emphasize the issue of mutual awareness, i.e. monitoring help needs and TA's availability. To tackle these difficulties, we developed two awareness tools. Both tools convey the same information: which exercise each group is working on, whether it has asked for help and for how long. In the centralized version, named Shelf, students provide information with a personal response system and the status of each team is juxtaposed on a central display. In the distributed version, named Lantern, each team provides information by interacting with a lamp placed on its table. The display is distributed over the classroom, the information being spatially associated to each group. We are now comparing these two versions in an empirical study with two first year undergraduate classes in Physics. Preliminary results show that both versions increase the efficiency of interaction between students and teaching assistants. This contribution focused on the distributed version.

Springer2009

Ambient Awareness for the Orchestration of Collaborative Problem Solving

Hamed Seiied Alavi

Classroom orchestration refers to the teacher's (or tutor's) responsibility to identify and manage the evolving learning opportunities and constraints, in real-time. We study the use of computer technology to support this orchestration task in a multi-constraint pedagogical practice: "recitation section". In university teaching, recitation sections complement lecture sessions by providing an opportunity for students to practice the course material in teams, under the supervision of the tutors. We start by analyzing recitation sections as they are held in our university and identify the causes of their inefficiencies. We show that lack of information on the progress and the current status of the students makes the orchestration task difficult for the tutors, and on the students' side results in a hesitation to interact with their peers. Thus, we propose an ambient awareness tool that makes this information available. Our tool, called Lantern, is an interactive lamp which is placed on each group's table that shows its status, namely the specific exercise that the group is currently working on, if assistance is needed, and, if so, for how long this assistance has been needed. Several questions are raised about how Lantern can facilitate the orchestration task and increase collaboration within and between teams. To answer these questions, we describe two user studies. In the first study, we show how Lantern can help the tutors share their resources between teams, enhance students' productivity, increase collaboration among students, and improve the structure of inter-team communication. In the second study, we compare Lantern with another tool, Shelf, which provides the same information but on a single screen in front of the classroom. It appears that Shelf, instead of encouraging collaboration, creates a competitive atmosphere among students. We relate the differences between Lantern and Shelf as to how they position the displayed information in the classroom space. In a second version of Lantern, the lamps are equipped with a wireless communication module that connects them to a server. The server receives every user action and controls the lamps by specifying what should be displayed on each of them. This allows for flexibility both in terms of the variety of the learning scripts that Lantern can implement and also in terms of integration with other technologies inside and outside of the classroom. Finally, we explore the possibilities of using Lantern in other learning contexts, such as high school courses, training workshops, or open learning spaces.

EPFL2012

The impact of study load on the dynamics of longitudinal email communications among students

Beat Adrian Schwendimann

With the advent of information technology, emails have gained wide acceptability among students as an asynchronous communication tool. According to the current pedagogy literature the overall trend of the use of email communication by university students has been increasing significantly since its inception, despite the rapid growth of the popularity and acceptability of other social mediums (e.g. Mobile phone and Facebook). In this study, we explore a longitudinal email communication network, which evolved under an increasing study load among 38 students throughout a university semester, using measures of social network analysis (SNA) and exponential random graph (ERG) models. This longitudinal network was divided into three waves, where each wave represents the portion of the complete longitudinal network that evolves between two consecutive observations. An increased study load was imposed through the assessment components of the course. SNA measures of degree centrality (i.e. the activity of an actor or actor popularity), betweenness centrality (i.e. the capacity to control the flow of information in a network), closeness centrality (i.e. reachable to other nodes) and reciprocity (i.e. tendency to make reciprocal links) are considered to explore this longitudinal network. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks. From the analysis of this email communication network, we notice that students’ network positions and behaviours change with the changes in their study load. In particular, we find that (i) students make an increased number of email communications with the in-crease of study load; (ii) the email communication network become sparse with the increase of study load; and (iii) the 2-star parameter (a subset of three nodes in which one node is connected to each of the other two nodes) and the triangle parameter (a subset of three nodes in which each node is connected to the other two nodes) can effectively explain the formation of network in wave3; whereas, the 3-star parameter (a subset of four nodes in which one node is connected to each of other three nodes) can effectively explain the formation of network in wave1 and wave2. Interpretations of these findings for the monitoring of student behaviour in online learning environments, as well as the implications for the design of assessment and the use of asynchronous tools are discussed in this paper.