Periodic Reporting for period 2 - ENVISAGE (ENhance VIrtual learning Spaces using Applied Gaming in Education)
Okres sprawozdawczy: 2017-10-01 do 2018-09-30
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 use 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, ENVISAGE 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, with the intention to track learners behavioral data and 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
Recent advances in ICT have enabled the widespread use 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, ENVISAGE 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, with the intention to track learners behavioral data and 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 user 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 virtual-lab design environment. Two workshops were organized involving educators and developers, whose feedback was collected through surveys. This resulted in a set of educational scenarios to be implemented during the pilots that focused on the development of virtual labs for Wind Energy and Chemical Processes.
In WP2 a set of tools for collecting user data, analyzing them to extract analytics and visualize the latter was developed. 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 on the client side. A framework for swallow analytics calculation from raw usage data was also developed that: a) identifies the learning goals of the labs; b) translates these goals into indicators of learning; and c) data/metrics (e.g. time-on-task, time-to-completion and travel-path) are analyzed.
WP3 introduced unsupervised and supervised learning algorithms for deep analytics within the educational context. The work on unsupervised learning focused on the clustering of students in the 2D Wind Energy Lab as an application. As examples for supervised learning, WP3 introduced the prediction of at-risk students as well as the prediction of the student’s proficiency level at a particular virtual lab. Moreover, WP3 introduced approaches for dynamic content adaptation for the personalization of virtual lab authoring and, in turn, for the personalization of learning.
WP4 produced a virtual labs authoring tool that allows educators to design Virtual labs and observe the behaviour of the learners. This authoring environment integrates all technical modules and offers a single product for educational organizations. 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.
WP5 performed the pilot testing and evaluation of the authoring tool with respect to its effectiveness, functionality, usability and user experience. Results from the Analytics and Visualizations evaluation showed that most educators understood the functionality of the analytics but needed more practical examples and instructions to be able to apply it on their own. The results for the virtual labs showed that the student expected the labs to be less fun than what they actually experienced.
Regarding exploitation, we initially identify the main target groups of potential applications of the ENVISAGE outcomes, which are formal primary and secondary education systems, of general or vocational type, adult learning, formal and informal extra-curriculum initiatives, etc. Then, we have identified the exploitation aspects of: a) the virtual labs authoring tool, b) the back-end system of the authoring tool, c) the data analytics and visualization tools, d) the specialized training of educators on professional design and development of virtual labs. Lastly, we have developed business cases for the project assets and proposed a business strategy for their exploitation.
In WP2 a set of tools for collecting user data, analyzing them to extract analytics and visualize the latter was developed. 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 on the client side. A framework for swallow analytics calculation from raw usage data was also developed that: a) identifies the learning goals of the labs; b) translates these goals into indicators of learning; and c) data/metrics (e.g. time-on-task, time-to-completion and travel-path) are analyzed.
WP3 introduced unsupervised and supervised learning algorithms for deep analytics within the educational context. The work on unsupervised learning focused on the clustering of students in the 2D Wind Energy Lab as an application. As examples for supervised learning, WP3 introduced the prediction of at-risk students as well as the prediction of the student’s proficiency level at a particular virtual lab. Moreover, WP3 introduced approaches for dynamic content adaptation for the personalization of virtual lab authoring and, in turn, for the personalization of learning.
WP4 produced a virtual labs authoring tool that allows educators to design Virtual labs and observe the behaviour of the learners. This authoring environment integrates all technical modules and offers a single product for educational organizations. 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.
WP5 performed the pilot testing and evaluation of the authoring tool with respect to its effectiveness, functionality, usability and user experience. Results from the Analytics and Visualizations evaluation showed that most educators understood the functionality of the analytics but needed more practical examples and instructions to be able to apply it on their own. The results for the virtual labs showed that the student expected the labs to be less fun than what they actually experienced.
Regarding exploitation, we initially identify the main target groups of potential applications of the ENVISAGE outcomes, which are formal primary and secondary education systems, of general or vocational type, adult learning, formal and informal extra-curriculum initiatives, etc. Then, we have identified the exploitation aspects of: a) the virtual labs authoring tool, b) the back-end system of the authoring tool, c) the data analytics and visualization tools, d) the specialized training of educators on professional design and development of virtual labs. Lastly, we have developed business cases for the project assets and proposed a business strategy for their exploitation.
ENVISAGE advanced the state-of-the-art, in the following ways:
- Designed, developed and supported an iterative virtual lab authoring and design process, which is based on data analytics and 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.
- Coupled gaming and learning analytics to predict learning outcomes and learner behaviour 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 visualisation.
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 optimised operating level and its flexibility to adjust to different learning disciplines, it can be easily absorbed by educational organisations, offering SMEs the possibility to seize new business opportunities.
- Designed, developed and supported an iterative virtual lab authoring and design process, which is based on data analytics and 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.
- Coupled gaming and learning analytics to predict learning outcomes and learner behaviour 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 visualisation.
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 optimised operating level and its flexibility to adjust to different learning disciplines, it can be easily absorbed by educational organisations, offering SMEs the possibility to seize new business opportunities.