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ENhance VIrtual learning Spaces using Applied Gaming in Education

Periodic Reporting for period 1 - ENVISAGE (ENhance VIrtual learning Spaces using Applied Gaming in Education)

Reporting period: 2016-10-01 to 2017-09-30

Learning is the subjective process of acquiring knowledge and skills. Defining an optimal learning pathway that would fit everybody is not possible nor would be effective, since it is generally recognized that different learning styles and tools fit the needs, backgrounds, competencies and personalities of different persons. Tailoring the learning process so as to meet the needs of each learner is a significant concept that can improve education and enhance social skills. However, personalization of learning using conventional ways, e.g. book-based learning, has been the exclusive privilege of merely a tiny subset of people who could afford the accompanying cost of such a service. Even in this case though, the personalized service is far from being optimal and individualized due to inherent constraints of traditional face-to-face tutoring, e.g. limited available time, lack of devotion, etc.

Recent advances in ICT have enabled the widespread of personalized learning. In this context, a number of virtual labs, emulating real lab environments, where users can accomplish a number of learning tasks and conduct various experiments with no cost or risk, have been recently developed. Online virtual labs have the potential to revolutionize the educational landscape by providing students with distance courses and curricula that otherwise would be difficult, if not infeasible, to be offered. The main challenge with such tools is to find effective and innovative ways to boost the learning experience and motivate the students to engage with the learning system, preventing them from churning out.

To this end, the overarching goal of ENVISAGE is to enhance the design and functionalities of virtual labs leading to optimal personalized learning processes. The project aims to develop an authoring environment for virtual lab design and development, which, equipped with data analytics methods and visualization tools that have been developed and reached maturity in the gaming industry, is suitable for iteratively evolving the design of virtual labs and for dynamically adapting the learning content to users.

In reaching this goal, ENVISAGE migrates knowledge from the digital games domain, where analytics are used to profile users, provide insights into the game design and adapt games to users, to the design of virtual labs, where tracking of learner behavioral data is used to model the students’ current behavior, predict their future behavior, and recognize the weaknesses and strengths of the learning path. Learning analytics are used to facilitate decision-making during the design of a lab by an educator and also support content adaptation to the personal needs and requirements of students.
In WP1, a set of initial requirements was defined based on literature review and stakeholder analysis, focusing on the learning analytics to be collected in the virtual labs and the functionalities and interface of the authoring environment. To analyze the needs of the different stakeholders, two workshops were organized involving educators and developers, whose feedback was collected through surveys and discussions. This resulted in the definition of a set of educational scenarios to be implemented during the small-scale pilots. These scenarios focused on the development of virtual labs for Wind Energy and Chemical Processes.

Based on the analytics requirements, a set of tools for collecting user data, analyzing them to extract analytics and visualize the latter was developed in WP2. More specifically, the existing tracking infrastructure was extended so as to facilitate learning analytics, via the installation of tracking points in the existing virtual labs and the integration of tracking software components on the client side. Every pre-defined event triggered by a user’s action is tracked by the tracking infrastructure. The collected raw data are then stored in an aggregated form in a database, before being enriched with additional information and accessed by the authoring tool. A framework for swallow analytics calculation from raw usage data was proposed, following a bottom-up approach, which was applied in the existing 2D and the newly developed 3D Wind Energy Labs. First, the learning goals of the labs were identified; then, the goals were translated into indicators of learning; and lastly, the data/metrics that need to be collected in order to measure the learning indicators were analyzed. These metrics (e.g. time-on-task, time-to-completion and travel-path) are used to create profiles of students or classes. Moreover, software implementing several strategies for visualizing learning analytics has been developed.

In WP3, several machine learning approaches were examined for mining raw user data and swallow analytics collected from long-term virtual lab usage, in order to extract deep learning analytics, i.e. cluster students in groups and predict or simulate their behavior. These techniques were implemented as a service that other components of ENVISAGE can interface with.

A first version of the virtual labs authoring tool was designed and developed in WP4. The tool is a plugin for WordPress that allows educators to design experiments with an easy to manipulate graphic user interface. The educators are able to design the experiment in 3D space with drag-n-drop functionalities. The authoring tool has an interface in a web browser that it is able to generate virtual labs in a certain game engine, i.e. Unity3D, which can be compiled either for Web or for desktop use. This is achieved through game project templates that are split into pieces of code to re-design a new game. These templates have embedded the necessary metrics measurement mechanisms that monitor a learners’ behavior and communicate with the game and visual analytics components.

The authoring tool has been evaluated in terms of effectiveness, functionality, usability and user experience in small-scale pilots organized under WP5. A group of teachers assessed the developed tools through user testing based on predefined educational scenarios, focus groups, and questionnaires, and proposed ways in which these tools can be improved.
ENVISAGE succeeds to advance the state-of-the-art, in the following ways:
- Supports an iterative virtual lab design process, which based on data analytics progressively enhances virtual learning spaces, through the use of an innovative, flexible and user-friendly authoring tool that can be used by educators without requiring special programming skills.
- Couples gaming and learning analytics to predict learning outcomes and learner behavior and, thus, to support enhanced game design and adaptation of the learning process and content to the user’s needs. Proposes new methods for learning analytics visualization.

The integrated ENVISAGE solution offers both social and economic benefits: through the enhancement of virtual labs it permits easy and effective access to education and learning to the student community, promoting equal opportunities for qualitative effective life-long learning and fostering creativity and innovation at all levels of education; moreover, due to its optimized operating level and its flexibility to adjust to different learning disciplines, it can be easily absorbed by educational organizations, offering SMEs the possibility to seize new business opportunities.
Concept diagram of ENVISAGE