ABSTRACT
Virtual worlds potentially provide students with a simulated environment that can provide exposure to situations and contexts not possible in reality and allow exploration of concepts, objects and phenomena that is safe both in terms of removing any physical danger or risk of failure if poor choices are made. This is certainly true in science education. However, the exploratory nature of virtual worlds can result in a lack of focus or direction in the learning. Observation of trials with the science-based Omosa Virtual 3D world has revealed that some students lose motivation. This project aims to personalise the learning experience of science-related skills through the incorporation of intelligent agents and asks "How can intelligent agents apply educational scaffolding to the demotivated student to maximise their time and enhance their 3D virtual learning experiences?" Building on the findings of previous studies involving agent-based virtual worlds, adaptive collaborative learning and intelligent agents, an intelligent virtual agent has been designed and partially prototyped so that it provides educational scaffolding to the student learning.
- Burleson, W. and Picard, R., 2006. Affective Agents: Sustaining Motivation to Learn Through Failure and a State of "Stuck". MIT Media Lab, Cambridge, MA, 02139.Google Scholar
- Chen, G.-D., Lee, J.-H., Wang, C.-Y., Chao, P.-Y., Li, L.-Y., and Lee, T.-Y., 2012. An Empathic Avatar in a Computer-Aided Learning Program to Encourage and Persuade Learners. Journal of Educational Technology & Society Apr2012, Vol. 15, Issue 2, p62--72. 11p.Google Scholar
- Collins, A., Joseph, D., and Bielaczyc, K., 2004. Design research: Theoretical and methodological issues. Journal Of The Learning Sciences 01/2004; 13:15--42. DOI:10.1207/s15327809jls1301_2.Google Scholar
- Correia, A., Cassola, F., Azevedo, D., Pinheiro, A., Morgado, L., Martins, P., Fonseca, B., and Paredes, H., 2014. An exploratory research agenda for 3-D virtual worlds as collaborative learning ecosystems: extracting evidences from literature. ResearchGate.Google Scholar
- Eschenbrenner, B., Nah, F.F.-H., and Siau, K., 2009. 3-D Virtual Worlds in Education: Applications, Benefits, Issues, and Opportunities. In Database Technologies: Concepts, Methodologies, Tools, and Applications IGI Global, 2595--2615.Google Scholar
- Hanna, N., Richards, D., and Jacobson, M., 2012. Automatic Acquisition of User Models of Interaction to Evaluate the Usability of Virtual Environments. In Knowledge Management and Acquisition for Intelligent Systems, D. RICHARDS and B. KANG Eds. Springer Berlin Heidelberg, 43--57. Google ScholarDigital Library
- Johnson, W.L., Rickel, J.W., and Lester, J.C., 2000. Animated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments. International Journal of Artificial Intelligence in Education 11, 47--78.Google Scholar
- Kim, Y., 2005. Empathetic virtual peers enhanced learner interest and self-efficacy. Workshop on Motivation and Affect in Educational Software in the 12th International Conference on Artificial Intelligence in Education (AIED 2005).Google Scholar
- Kim, Y. and Baylor, A., 2006. A Social-Cognitive Framework for Pedagogical Agents as Learning Companions. Educational Technology Research and Development 54, 6, 569--596.Google ScholarCross Ref
- Kim, Y., Baylor, A.L., and Shen, E., 2007. Pedagogical agents as learning companions: the impact of agent emotion and gender. Journal of Computer Assisted Learning 23, 3, 220--234.Google ScholarCross Ref
- Lee, M., 2009. How Can 3d Virtual Worlds Be Used To Support Collaborative Learning? An Analysis Of Cases From The Literature. Journal of e-Learning and Knowledge Society {S.l.}, v. 5, n. 1 nov. 2009.Google Scholar
- Leony, D., Muñoz-Merino, P.J., Pardo, A., and Delgado Kloos, C., 2013. Provision of awareness of learners' emotions through visualizations in a computer interaction-based environment. Expert Systems with Applications 40, 13, 5093--5100.Google ScholarCross Ref
- McQuiggan, S., Lee, S., and Lester, J., 2007. Early Prediction of Student Frustration. In Affective Computing and Intelligent Interaction, A.R. PAIVA, R. PRADA and R. PICARD Eds. Springer Berlin Heidelberg, 698--709. Google ScholarDigital Library
- McQuiggan, S.W. and Lester, J.C., 2007. Modeling and evaluating empathy in embodied companion agents. International Journal of Human-Computer Studies 65, 4, 348--360. Google ScholarDigital Library
- Motola, R., Jaques, P.A., Axt, M., and Vicari, R., 2009. Architecture for animation of affective behaviors in pedagogical agents. Journal of the Brazilian Computer Society 15, 3--13.Google ScholarCross Ref
- Paiva, A., Dias, J.o., Sobral, D., Aylett, R., Woods, S., Hall, L., and Zoll, C., 2005. Learning by feeling: evoking empathy with synthetic characters. Applied Artificial Intelligence 19, 3-4, 235--266.Google ScholarCross Ref
- Picard, R.W. and Winslow, B., 2006. Affective learning companions: strategies for empathetic agents with real-time multimodal affective sensing to foster meta-cognitive and meta-affective approaches to learning, motivation, and perseverance. Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences.Google Scholar
- Richards, D., Jacobson, M.J., Taylor, M., Newstead, A., Taylor, C., Porte, J., Kelaiah, I., and Hanna, N., 2012. Learning to be Scientists via a Virtual Field Trip (Demonstration). Proc of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012), Conitzer, Winikoff, Padgham, and van der Hoek (eds.) June, 4--8, 2012. Google ScholarDigital Library
- Robison, J., McQuiggan, S., and Lester, J., 2010. Developing Empirically Based Student Personality Profiles for Affective Feedback Models. In Intelligent Tutoring Systems, V. ALEVEN, J. KAY and J. MOSTOW Eds. Springer Berlin Heidelberg, 285--295. Google ScholarDigital Library
- Rowe, J.P., Mott, B.W., McQuiggan, S.W., Robison, J.L., Lee, S., and Lester, J.C., 2009. CRYSTAL ISLAND: A Narrative-Centered Learning Environment for Eighth Grade Microbiology. Workshop on Intelligent Educational Games - AIED 2009, 19--28.Google Scholar
- Ruggeri, F., Faltin, F., and Kenett, R., 2007. Bayesian Networks. Encyclopedia of Statistics in Quality & Reliability, Wiley & Sons.Google Scholar
- Sabourin, J., Mott, B., and Lester, J., 2011. Computational Models of Affect and Empathy for Pedagogical Virtual Agents. Department of Computer Science, North Carolina State University, Raleigh NC 27695.Google Scholar
- Sklar, E. and Richards, D., 2010. Agent-based systems for human learners. The Knowledge Engineering Review 25, 02, 111--135. Google ScholarDigital Library
- Stasko, J., Abowd, G., Badre, A., Foley, J., Mynatt, E., Pierce, J., Potts, C., Shaw, C., Stasko, J., and Walker, B., 2007. Usability Principles. Georgia Tech HCI faculty.Google Scholar
Index Terms
- Intelligent and Empathic Agent to Support Student Learning in Virtual Worlds
Recommendations
An application of a virtual learning environment in support of teaching and learning for design and technology education
Audiovisual advances in Virtual Reality (VR) technology have given rise to innovative ways to teach and learn. However, so far, teaching and learning processes have been technologically driven as opposed to pedagogically led. This article identifies the ...
Web-Based virtual learning environments: a research framekwork and a preliminary assessment of effectiveness in basic IT skills training
Internet technologies are having a significant impact on the learning industry. For-profit organizations and traditional institutions of higher education have developed and are using web-based courses, but little is known about their effectiveness ...
Student Designed Virtual Teacher Feedback
ICCAE '17: Proceedings of the 9th International Conference on Computer and Automation EngineeringInteractive virtual learning environments (VLEs) have significant potential to influence students' learning achievements. Characters in these VLEs can act as a virtual peers and teachers by providing empathic responses tailored to the affective state of ...
Comments