In this page you will find all available deliverables of ENVISAGE once they have been finished, sorted by delivery date.
|D6.1||Project Communication Kit||D6.1 presents the first version of the project’s publicity material that will be used to disseminate its goal and objectives to the wider public. This material consists of the project web-site, poster and leaflet, as well as the project’s social media accounts. In this report we present the content that has been generated for this purpose and motivate our design and content choices.|
|D1.1||Educational scenarios and stakeholder analysis||The aim of this document is to present the initial requirements from a group of stakeholders (teachers, teacher trainers and school advisors) and to provide a definition of the types of educational scenarios that the authoring tool should support. Analysis of the stakeholders involved in virtual labs. An updated version of the educational scenarios will be delivered on M14. More specifically we have defined the stakeholders involved in a learning situation involving virtual, online learning environments such as virtual labs, focusing on the teachers and learners but also considering other relevant groups in the design/development and learning process (teacher trainers and school advisors). We are analysing the requirements of the different groups of stakeholders in terms of a) behavioural analytics and b) online authoring environments. The stakeholder analysis was based on a workshop with 20 participants, followed by interviews and reviews of best practices with a series of online labs (presented in this document) that EA is already employing in the framework of the offered services (lessons, labs or PD activities). Based on the stakeholder we are presenting a series of educational scenarios that will serve as a pool for the prototype demonstrators. These scenarios are organised at three levels, referring to the complexity level of the tasks that are assigned to the students while using the online labs. These scenarios will feed into WP5 for specifying the virtual labs to be designed and developed using the authoring environment (WP4) and will provide the test bed for evaluating the effectiveness of the developed technologies in WP2-4 to address the stakeholder requirements.|
|D1.2||Data structure requirements for learning analytics||The current document first presents a general compilation of behavioural data collected from virtual learning labs in the framework of the Go-Lab project and their analysis. The comprehensive analysis of the available data provided several deeper qualitative and quantitative understandings of the user behaviour. The experience gathered from the analyses of the available data is directly transferred to the ENVISAGE project in order to guarantee that more effective, thorough and comprehensive metrics will be implemented to collect the behaviour of each user, teacher or student, during the usage of a virtual lab in science teaching and learning. In this context we discuss and propose a list of main metrics that can be collected by the analytics service, their definition and rationale of use. We also propose that the structure of the analytics data and its aggregation level to permit analysis and interpretation similar to the one that is conventionally done in the actual school environment. We also discuss the functional requirements that the virtual lab authoring environment of ENVISAGE should accommodate. These are presented mainly from an end-user perspective being a science teacher. Finally we give a short overview to describe some basic functionalities and use cases of the Go-Lab system in the framework of which we obtained the raw log data of user actions in its authoring environment. This dataset is now available to partners of ENVISAGE for study and analysis. The description of its content is given to help the application of machine learning algorithms and practices for extracting baseline and deeper information on how the environment was utilized.|
|D2.1||Analytics infrastructure installation and data aggregation||This deliverable describes the initial visualization strategies developed for the ENVISAGE project and their implementation. Building from an overview of the state of the art in general Analytics and Game Analytics, it moves on to identify requirements and goals for learning analytics visualization, building from previous deliverables in the project. A number of visualization strategies are presented and their technical implementation is described. software to be integrated into the virtual lab for tracking. The format of the raw data is typically neither sufficient to allow direct visualization nor is it proper input for more sophisticated algorithms. Therefore, there exists a second layer that transforms and aggregates the raw data into a more manageable format. During this process the data is also enriched with additional (meta)data, such as geo-information, and raw events are grouped into user sessions. In an advanced setting, we have a third layer where user data can also be augmented with predictions about future users’ behavior or automatically inferred traits. After this step, the data needs to be made accessible again. To accomplish this in a flexible way, the fourth layer consists of an API that makes all data available in different forms and formats. While raw data access is allowed, the data can also be accessed in an aggregated form or on a user level with all its metadata.|
|D7.3||Data Management Plan||This deliverable is the Data Management Plan document, which describes the various types of data in ENVISAGE, the procedures followed to collect them and the measures that ill be taken in order to ensure that no confidential information will be leaked. Also, the storage, archiving and preservation plan of the data is also sketched, along with our plan to comply with the Open Data Initiative.|
|D2.3||Visualization Strategies for Course Progress Reports||This deliverable describes the initial visualization strategies developed for the ENVISAGE project and their implementation. Building from an overview of the state of the art in general Analytics and Game Analytics, it moves on to identify requirements and goals for learning analytics visualization, building from previous deliverables in the project. A number of visualization strategies are presented and their technical implementation is described.|
|D4.1||Architecture and Interface Design||Relying on the functional requirements gathered in T1.2, we define the architecture of the "Virtual labs authoring tool" that will be capable of integrating the functionalities developed in WP2 and WP3 into a web interface component able to communicate with a game engine remotely in order to produce a lab. As regards the integration with WP2 and WP3, the adopted architecture should make provision for effectively injecting the necessary metrics in the virtual lab project to assess the user behavior during the experience of the virtual lab. The selection of the basic technologies will also be made. Another responsibility of this task is to analyze the functional requirements provided by WP1 in order to deliver an accurate interface design of the authoring tool suitable for the virtual labs. Mockups will be used to simulate the workflow between the supported functionalities and also act as a running exercise between the interface designers and the author-users in defining the look and feel of the authoring tool.|