Livrables
This deliverable will incorporate an initial implementation of the educational scenarios and will report on the evaluation results obtained during the execution of the pilots as received and codified by the stakeholders (e.g., teachers) carrying out the pilots. This deliverable will feed directly to WP1 in re-defining the educational scenarios and the requirements and will trigger the initiation of the second requirements phase. The results of the second phase pilot execution and evaluation will be delivered on M21 completing the second evaluation phase.
Architecture and interface designReport on the architecture that will be adopted for integrating all technologies under the joint cause of supporting the “Virtual labs authoring tool”. Mockups specifying the design and workflow of the final application will be also included, discussing how they manage to address the functional requirements reported in D1.3.
Educational scenarios and stakeholder analysisDefinition of the types of educational scenarios that the authoring tool should support. Analysis of the stakeholders involved in virtual labs.
Data structure and functional requirements (update)An updated version of the requirements will be delivered in response to the evaluation process in WP5.
Dissemination and Communication planReport including a detailed version of the preliminary plan described in Sections 2.2.1 and 2.2.2 with concrete plans for the dissemination and communication activities of each partner.
Pilot execution plan and evaluation protocolThis deliverable will report the plan that will be agreed among the partners for conducting the small-scale pilots and the adopted protocol for the evaluation of all developed modules.
Implementation of the educational scenarios and evaluation report (second phase)The results of the second phase pilot execution and evaluation will be delivered on M21 completing the second evaluation phase.
Educational scenarios and stakeholder analysis (update)An updated version of the educational scenarios will be delivered in response to the evaluation process in WP5.
Data structure and functional requirementsDefinition of the behavioral data that should be captured from online virtual learning labs in order to enable baseline learning analytics as well as profiling, prediction, A/B testing and retention modeling. This considering the different types of educational scenarios in use in online environments. Definition of the several functional requirements that will enable the implementation of the educational scenarios and the execution of the small-scale pilots (WP5). As part of this deliverable, a collection of several telemetry datasets from currently running virtual labs at EA and their partners will be delivered.
Impact assessment and updated dissemination planReport summarizing the project dissemination activities, assessing their impact and suggesting potential corrections to the adopted dissemination strategy.
AIV test plan and integration resultsReport on the integration protocol that will be established between the individual components (game-visual analytics, Unity3D, Web interface), as well as on the integration tests that have been undertaken to verify the operational capacity of each module.
Improved version of the initial implementation encompassing the results of the second development cycle, as well as introducing optimizations with respect to the quality of the generated content and the integrity of the generated labs for each platform (desktop, console, mobile, web).
Visualization strategies for course project reportsInitial implementation of the visualization and reporting techniques for visual exploration of the learning data that will provide useful insights into the learners’ profiles.
Updated predictive analytics and course adaptation methodsThis deliverable will update the machine learning algorithms and course material adaptation methods based on the revised requirements and the updated shallow analytics after the first evaluation phase.
Updated shallow analytics and visualization strategiesThis deliverable will update the shallow analytics tools and visualization techniques based on the revised requirements after the first phase of evaluation.
First version of the “Virtual labs authoring tool”Software implementation of the tool for authoring virtual labs in 3D space. This tool will encompass software components as resulted from the game and visual analytics work packages WP2 and WP3.
Preliminary predictive analytics and course material adaptation methodsThis deliverable will review the state of the art and build the appropriate machine learning algorithms in order to group learners into segments and predict their future behavior. It will also provide an initial definition and implementation of methods for adapting course material to the learners’ needs.
User profiling and behavioral modeling based on shallow analyticsInitial implementation of models and algorithms for capturing core user behavioral patterns and profiles.
This deliverable will determine the strategy by which the research data generated by the project will be made open for maximizing their re-use.
Initial project publicity material consisting of the project web-site, poster, leaflet and factsheet, as well as the project’s social media accounts (i.e. Twitter, LinkedIn and Facebook).
Evaluated and finalized ENVISAGE tool, including authoring tool, execution package and analytics package, including documentation and best practice documentation. The package then moves to the dissemination phases of WP6.
Publications
Auteurs:
Panagiotis Migkotzidis, Dimitrios Ververidis, Eleftherios Anastasovitis, Spiros Nikolopoulos, Ioannis Kompatsiaris, Georgios Mavromanolakis, Line Ebdrup Thomsen, Marc Mller, and Fabian Hadiji
Publié dans:
Interactive Collaborative Learning, 2018, 2018
Éditeur:
Springer
DOI:
10.5281/zenodo.1692885
Auteurs:
Dimitrios Ververidis, Giannis Chantas, Panagiotis Migkotzidis, Eleftherios Anastasovitis, Anastasios Papazoglou-Chalikias, Efstathios Nikolaidis, Spiros Nikolopoulos, Ioannis Kompatsiaris, Georgios Mavromanolakis, Line Ebdrup Thomsen, Antonios Liapis, Georgios Yannakakis, Marc Müller, and Fabian Hadiji
Publié dans:
Interactive Collaborative Learning, 2018, 2018
Éditeur:
Springer
DOI:
10.5281/zenodo.1691787
Auteurs:
Daniele Gravina, Antonios Liapis, Georgios N. Yannakakis
Publié dans:
Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18, Numéro 2018-07-02, 2018, Page(s) 93-100, ISBN 9781-450356183
Éditeur:
ACM Press
DOI:
10.1145/3205455.3205503
Auteurs:
Falko Weigert Petersen, Line Ebdrup Thomsen, Pejman Mirza-Babaei, Anders Drachen
Publié dans:
Proceedings of the Annual Symposium on Computer-Human Interaction in Play - CHI PLAY '17, Numéro 2017-10-15, 2017, Page(s) 377-388, ISBN 9781-450348980
Éditeur:
ACM Press
DOI:
10.1145/3116595.3125499
Auteurs:
Georgios N. Yannakakis, Roddy Cowie, Carlos Busso
Publié dans:
IEEE Transactions on Affective Computing, 2018, Page(s) 1-1, ISSN 1949-3045
Éditeur:
Institute of Electrical and Electronics Engineers
DOI:
10.1109/TAFFC.2018.2879512
Auteurs:
Kyung-Joong Kim, DuMim Yoon, JiHoon Jeon, Seong-il Yang, Sang-Kwang Lee, EunJo Lee,
Yoonjae Jang, Dae-Wook Kim, Pei Pei Chen, Anna Guitart, Paul Bertens, África Periáñez, Fabian Hadiji, Marc Müller, Youngjun Joo, Jiyeon Lee, and Inchon Hwang
Publié dans:
arXiv, 2018
Éditeur:
arXiv
DOI:
10.5281/zenodo.1696795
Auteurs:
Anastasios Karakostas, Anastasios Maronidis, Dimitrios Ververidis, Efstathios Nikolaidis, Anastasios Papazoglou Chalikias, Spiros Nikolopoulos, Ioannis Kompatsiaris
Publié dans:
Software Data Engineering for Network eLearning Environments, Numéro 11, 2018, Page(s) 115-137, ISBN 978-3-319-68317-1
Éditeur:
Springer International Publishing
DOI:
10.1007/978-3-319-68318-8_6
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