Visual Modelling of Collaborative Learning Processes

2008 ◽  
pp. 280-297 ◽  
Author(s):  
Andreas Harrer ◽  
H. Ulrich Hoppe
Keyword(s):  
Collaborative Learning ◽  
Visual Learning ◽  
Learning Processes ◽  
Learning Activity ◽  
Collaboration Scripts ◽  
Web Based ◽  
Tutoring Systems ◽  
Modelling Languages ◽  
Research Fields ◽  
Learning Scenarios

The modelling of learning processes and its use in computer-supported learning scenarios attracted attention in a wide variety of research fields in the last years, e.g. in web based education, computer supported collaboration scripts, and intelligent tutoring systems (ITS). Most of the discussion is either focused on the conceptual level of instructional design for exchange between designers or on the automated execution of predefined designs and learning scripts. In this chapter we will elaborate on the whole spectrum of different uses that visual learning models provide for teachers, learners, and researchers. Based on our discussions in an international research project on computer-supported collaboration scripts we identify desired properties for such modelling languages especially considering the needs of the practitioners. Finally we propose MoCoLADe (MOdel for COllaborative Learning Activity Design), an exemplary approach of a visual language for collaborative learning processes that was designed according to the presented principles.

Scripts for Facilitating Computer Supported Collaborative Learning

2011 ◽  
pp. 745-750
Author(s):  
Bernhard Ertl ◽  
Heinz Mandl
Keyword(s):  
Distance Learning ◽  
Collaborative Learning ◽  
Learning Strategies ◽  
Text Comprehension ◽  
Comprehension Strategies ◽  
Computer Supported Collaborative Learning ◽  
Collaboration Scripts ◽  
Collaboration Skills ◽  
Learning Scenarios ◽  
Collaboration Process

Many distance learning scenarios, for example, virtual seminars, use collaborative arrangements for learning. By applying them, they offer learners the chance to construct knowledge collaboratively. However, learners often do not possess the skills necessary for a beneficial collaboration. It is therefore important that learners are offered support in these learning scenarios. Scripts for collaborative learning can provide support. They can guide learners through their collaboration process (Ertl, Kopp, & Mandl, 2007b) and help them to acquire collaboration skills (Rummel & Spada, 2005). Scripts for collaboration were originally developed in order to support text comprehension. They facilitate two or more learners—who are similar as far as their existing knowledge and learning strategies are concerned— in their efforts to understand contents provided by theory texts. Collaboration scripts split this process into a sequence of smaller steps, assign each learner to a particular role, and offer a number of comprehension strategies, such as questions, feedback, and elaboration. Each one of these learners has a defined role to play, which in turn is associated with certain strategies and varies within the different phases.

A Semantic Web-based authoring tool to facilitate the planning of collaborative learning scenarios compliant with learning theories

2013 ◽  
Vol 63 ◽  
pp. 267-284 ◽  
Author(s):  
Seiji Isotani ◽  
Riichiro Mizoguchi ◽  
Sadao Isotani ◽  
Olimpio M. Capeli ◽  
Naoko Isotani ◽  
...  
Keyword(s):  
Collaborative Learning ◽  
Semantic Web ◽  
Authoring Tool ◽  
Learning Theories ◽  
Web Based ◽  
Learning Scenarios

scholarly journals The Metano Modeling Toolbox MMTB: An Intuitive, Web-Based Toolbox Introduced by Two Use Cases

Metabolites ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 113
Author(s):  
Julia Koblitz ◽  
Sabine Will ◽  
S. Riemer ◽  
Thomas Ulas ◽  
Meina Neumann-Schaal ◽  
...  
Keyword(s):  
Metabolic Networks ◽  
Point Of View ◽  
Use Cases ◽  
Mathematical Methods ◽  
State Behavior ◽  
Web Based ◽  
Research Fields ◽  
Balance Analysis ◽  
Metabolic Models ◽  
User Friendly

Genome-scale metabolic models are of high interest in a number of different research fields. Flux balance analysis (FBA) and other mathematical methods allow the prediction of the steady-state behavior of metabolic networks under different environmental conditions. However, many existing applications for flux optimizations do not provide a metabolite-centric view on fluxes. Metano is a standalone, open-source toolbox for the analysis and refinement of metabolic models. While flux distributions in metabolic networks are predominantly analyzed from a reaction-centric point of view, the Metano methods of split-ratio analysis and metabolite flux minimization also allow a metabolite-centric view on flux distributions. In addition, we present MMTB (Metano Modeling Toolbox), a web-based toolbox for metabolic modeling including a user-friendly interface to Metano methods. MMTB assists during bottom-up construction of metabolic models by integrating reaction and enzymatic annotation data from different databases. Furthermore, MMTB is especially designed for non-experienced users by providing an intuitive interface to the most commonly used modeling methods and offering novel visualizations. Additionally, MMTB allows users to upload their models, which can in turn be explored and analyzed by the community. We introduce MMTB by two use cases, involving a published model of Corynebacterium glutamicum and a newly created model of Phaeobacter inhibens.

scholarly journals Promoting regulation of equal participation in online collaboration by combining a group awareness tool and adaptive prompts. But does it even matter?

2021 ◽  
Author(s):  
Sebastian Strauß ◽  
Nikol Rummel
Keyword(s):  
Collaborative Learning ◽  
Online Collaboration ◽  
Online Course ◽  
Group Awareness ◽  
Web Based ◽  
Equal Distribution ◽  
Action Sequences ◽  
Awareness Tool ◽  
University Level ◽  
Additional Support

AbstractUnequal participation poses a challenge to collaborative learning because it reduces opportunities for fruitful collaboration among learners and affects learners’ satisfaction. Social group awareness tools can display information on the distribution of participation and thus encourage groups to regulate the distribution of participation. However, some groups might require additional explicit support to leverage the information from such a tool. Therefore, this study investigated the effect of combining a group awareness tool and adaptive collaboration prompts on the distribution of participation during web-based collaboration. In this field experiment, students in a university level online course collaborated twice for two-weeks (16 groups in the first task; 13 groups in the second task) and either received only a group awareness tool, a combination of a group awareness tool and adaptive collaboration prompts, or no additional support. Our results showed that students were more satisfied when the participation in their group was more evenly distributed. However, we only found tentative support that the collaboration support helped groups achieve equal participation. Students reported rarely using the support for shared regulation of participation. Sequence alignment and clustering of action sequences revealed that groups who initiated the collaboration early, coordinated before solving the problem and interacted continuously tended to achieve an equal distribution of participation and were more satisfied with the collaboration. Against the background of our results, we identify potential ways to improve group awareness tools for supporting groups in their regulation of participation, and discuss the premise of equal participation during collaborative learning.

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