Deconstructing orchestration load: comparing teacher support through mirroring and guiding

Lecture Notes in Computer Science

et al. 2022

Teacher orchestration of technology-enhanced learning has received increasing attention as a factor for enhancing students' learning gains. However, a limited number of studies have investigated the impact of learning settings on teachers' orchestration actions. In this paper, we considered two different settings of computer-supported collaborative learning (CSCL) activities, namely online and in-class, and studied their influence on teachers' orchestration actions. Data was collected from five sessions for each setting. The findings indicated that during the in-class sessions there were more teacher-individual interactions, announcements, checking participation/responses tabs, and dashboard interventions conducted by the teacher. In the online setting, however, more teacher-class interactions occurred when compared to the in-class setting. The implications of this study and its continuation are related to the consideration of the learning setting in the design, redesign, and evaluation processes of orchestration technologies.

Section: Coding Teacher's Orchestration Actionsmentioning

confidence: 99%

Exploring Teacher’s Orchestration Actions in Online and In-Class Computer-Supported Collaborative Learning

Lecture Notes in Computer Science

et al. 2022

“…To this end, in the following, we employ a case study design (Yin, 2009) and analysed two cases of LA for design and orchestration (see Figure 2). In both cases, teachers used the same collaborative authoring and implementation tool called PyramidApp (Amarasinghe et al, 2021), enacted their learning scenarios in authentic settings, and reflected with LA as described below.…”

Section: Design and Orchestration Of Pyramid Learning Designs: La Sol...mentioning

confidence: 99%

Learning analytics support to teachers' design and orchestrating tasks

Computer Assisted Learning

Michos

Crespi

et al. 2022

Self Cite

Background: Data-driven educational technology solutions have the potential to support teachers in different tasks, such as the designing and orchestration of collaborative learning activities. When designing, such solutions can improve teacher understanding of how learning designs impact student learning and behaviour; and guide them to refine and redesign future learning designs. When orchestrating educational scenarios, data-driven solutions can support teacher awareness of learner participation and progress and enhance real time classroom management. Objectives: The use of learning analytics (LA) can be considered a suitable approach to tackle both problems. However, it is unclear if the same LA indicators are able to satisfactorily support both the designing and orchestration of activities. This study aims to investigate the use of the same LA indicators for supporting multiple teacher tasks, that is, design, redesign and orchestration, as a gap in the existing literature that requires further exploration. Methods: In this study, first we refer to the previous work to study the use of different LA to support both tasks. Then we analyse the nature of the two tasks focusing on a case study that uses the same collaborative learning tool with LA to support both tasks. Implications: The study findings led to derive design considerations on LA support for teachers' design and orchestrating tasks.

“…Due to Covid-19, CSCL activities were conducted online using a tool called PyramidApp. PyramidApp implements CSCL scripts based on a particularisation of the Pyramid collaborative learning flow pattern [4]. The main criteria for selecting teachers to participate in this study was having prior knowledge and experience using PyramidApp.…”

Section: A Participants and Environmentmentioning

confidence: 99%

“…However, existing studies refer to orchestration load as a black box from which little is known about its contributing factors [4]. Moreover, there is a lack of instruments to measure this notion [2].…”

Section: Introductionmentioning

confidence: 99%

“…The increasing number of low-cost sensors available for different functionalities like measuring movement, and skin conductivity [11], provides new possibilities to study learning situations, both for teachers and students, such as in [12] [13] [14] [2]. However, we still lack reliable measures to estimate orchestration load [2] [4], which could be useful to inform design decisions for teacher support tools [15].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating Orchestration Load in CSCL Situations Using EDA

Crespi

2022 International Conference on Advanced Learning Technologies (ICALT)

Vujović

et al. 2022

Self Cite

This study investigates the extent to which Electrodermal Activity (EDA) sensor data can be triangulated with self-perception measures to estimate facets of teachers' orchestration load in the context of Computer-Supported Collaborative Learning (CSCL). It was expected to observe variances in the EDA signal as a result of stressful moments and incidents related to orchestration. Study findings indicated that EDA variations concurred with situations in which the teacher reported feeling stressed when orchestrating CSCL Pyramid scripts.