Augmented Reality-Based Simulators as Discovery Learning Tools: An Empirical Study

This paper reports empirical evidence on having students use AR-SaBEr, a simulation tool based on augmented reality (AR), to discover the basic principles of electricity through a series of experiments. AR-SaBEr was enhanced with knowledge-based support and inquiry-based scaffolding mechanisms, which proved useful for discovery learning in Web-based simulation environments. Learning performance factors evaluated included students' learning behavior while interacting with the system, AR-SaBEr's learning effectiveness, and students' motivation in using the AR-based simulation environment. The study suggests that AR simulators can be exploited as effective learning environments for learning the basic principles of electricity. It would, however, be necessary to consider a number of scaffolding options to improve the learning effectiveness of AR-based simulation environments when used with students who have low levels of either: 1) self-regulation skills, or 2) motivation to engage in AR-based simulation activities.

[1]  Yao-Ting Sung,et al.  Effects of learning support in simulation-based physics learning , 2008, Comput. Educ..

[2]  Philip Smith.  Roger Bakeman John M. Gottman , 1987, Animal Behaviour.

[3]  Jianwei Zhang,et al.  Triple scheme of learning support design for scientific discovery learning based on computer simulation: experimental research , 2004, J. Comput. Assist. Learn..

[4]  Pierre Dillenbourg,et al.  Designing augmented reality for the classroom , 2013, Comput. Educ..

[5]  Dieter Schmalstieg,et al.  Mathematics and geometry education with collaborative augmented reality , 2003, Comput. Graph..

[6]  Susan Pedersen,et al.  Integrating computer- and teacher-based scaffolds in science inquiry , 2011, Comput. Educ..

[7]  Jianwei Zhang,et al.  Supporting scientific discovery learning in a simulation environment , 2003, J. Comput. Assist. Learn..

[8]  Jia Zhang,et al.  The development and evaluation of an augmented reality-based armillary sphere for astronomical observation instruction , 2014, Comput. Educ..

[9]  Ton de Jong,et al.  Co-Lab: research and development of an online learning environment for collaborative scientific discovery learning , 2005, Comput. Hum. Behav..

[10]  Bertrand Schneider,et al.  Benefits of a Tangible Interface for Collaborative Learning and Interaction , 2011, IEEE Transactions on Learning Technologies.

[11]  Hirokazu Kato,et al.  Augmented Reality Learning Experiences: Survey of Prototype Design and Evaluation , 2014, IEEE Transactions on Learning Technologies.

[12]  Blair MacIntyre,et al.  A psychological perspective on augmented reality in the mathematics classroom , 2013, Comput. Educ..

[13]  Joseph Krajcik,et al.  A Scaffolding Design Framework for Software to Support Science Inquiry , 2004, The Journal of the Learning Sciences.

[14]  Nicole Fruehauf.  Flow The Psychology Of Optimal Experience , 2016 .

[15]  Carlos Delgado Kloos,et al.  Experimenting with electromagnetism using augmented reality: Impact on flow student experience and educational effectiveness , 2014, Comput. Educ..

[16]  Chin-Chung Tsai,et al.  Affordances of Augmented Reality in Science Learning: Suggestions for Future Research , 2012, Journal of Science Education and Technology.

[17]  Wouter van Joolingen,et al.  Cognitive tools for discovery learning , 1999 .

[18]  M. Csíkszentmihályi.  Flow: The Psychology of Optimal Experience , 1990 .

[19]  Ton de Jong,et al.  Instruction based on computer simulations , 2010 .

[20]  Vineet R. Kamat,et al.  Collaborative visualization of engineering processes using tabletop augmented reality , 2013, Adv. Eng. Softw..

[21]  Susan Pedersen,et al.  The VELscience project: Middle schoolers' engagement in student-directed inquiry within a virtual environment for learning , 2014, Comput. Educ..

[22]  D. Towne,et al.  Exploring a domain through a computer simulation: traversing variable and relation space with the help of a hypothesis scratchpad , 1993 .

[23]  Randy L. Bell,et al.  The many levels of inquiry , 2008 .

[24]  Wojciech Cellary,et al.  Evaluation of learners' attitude toward learning in ARIES augmented reality environments , 2013, Comput. Educ..

[25]  Jyh-Chong Liang,et al.  Current status, opportunities and challenges of augmented reality in education , 2013, Comput. Educ..

[26]  Chris Dede,et al.  Affordances and Limitations of Immersive Participatory Augmented Reality Simulations for Teaching and Learning , 2009 .

[27]  Michael Theall,et al.  New Directions for Theory and Research on Teaching: A Review of the Past Twenty Years , 1999 .

[28]  D. Ketelhut.  The Impact of Student Self-efficacy on Scientific Inquiry Skills: An Exploratory Investigation in River City, a Multi-user Virtual Environment , 2007 .

[29]  Jan T. van der Veen,et al.  The learning effects of computer simulations in science education , 2012, Comput. Educ..

[30]  Valerie J. Shute,et al.  A Comparison of Learning Environments: All That Glitters , 1992 .

[31]  J. Keller.  Strategies for stimulating the motivation to learn , 1987 .

[32]  Richard E. Clark,et al.  Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching , 2006 .

[33]  Ton de Jong,et al.  Scientific Discovery Learning with Computer Simulations of Conceptual Domains , 1998 .

[34]  Marcelo Milrad,et al.  Integrating Mobile, Web and Sensory Technologies to Support Inquiry-Based Science Learning , 2010, 2010 6th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education.

[35]  R. Mayer.  Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction. , 2004, The American psychologist.

[36]  Ton de Jong,et al.  Instructional environments for simulations. , 1991 .

[37]  P. Pintrich,et al.  Motivational and self-regulated learning components of classroom academic performance. , 1990 .