Skip to main content

Prompting Connections Between Content and Context: Blending Immersive Virtual Environments and Augmented Reality for Environmental Science Learning

  • Conference paper
  • First Online:
Immersive Learning Research Network (iLRN 2018)

Abstract

Outdoor field trip experiences are a cornerstone of quality environmental science instruction, yet the excitement and distractions associated with field trips can overwhelm learning objectives. Augmented reality (AR) can focus students’ attention and help them connect the concept rich domain of the classroom with the context rich experiences in the field. In this study, students used an immersive virtual pond, and then participated in a field trip to a real pond augmented by mobile technologies. We are interested in understanding whether and how augmenting a field trip with information via handheld mobile devices can help students connect concepts learned in the classroom with observations during the field trip. Specifically, we are curious about how augmentation allows students to “see the unseen” in concepts such as photosynthesis and respiration as well as apply causal reasoning patterns they learned about in the classroom while using an inquiry-based immersive virtual environment, EcoMUVE. We designed an AR supported field trip with three different treatments: (1) a ‘visual’ treatment in which students were prompted to consider content or perspectives from EcoMUVE using videos and animations (2) a ‘text’ treatment in which students were prompted to consider content or perspectives from EcoMUVE using text and images, and (3) a ‘control’ treatment that did not specifically prompt students to think about content or perspectives from EcoMUVE. We used a mixed-methods research approach and collected data based on pre, mid, and post surveys; student responses to prompts captured in the notes and log files during the field trip; a post-field-trip survey; and performance on an in-class written assignment. On the field trip, we found that students in all three treatments more frequently referred to visible factors and direct effects than to invisible factors and indirect effects. There were few discernible differences between the text and visual prompted treatments based on responses in the notes and log files captured during the field trip. After the field trip, students exposed to the prompted treatments were more likely to describe invisible factors such as wind, weather, and human impacts, while students exposed to the control treatment continued to focus on visible features such as aquatic plants. These findings provide insights to designers who aim to support learning activities in outdoor and immersive learning environments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Shelton, B.E., Hedley, N.R.: Using augmented reality for teaching earth-sun relationships to undergraduate geography students. In: First IEEE International Workshop, Augmented Reality Toolkit, 8-p. IEEE (2002)

    Google Scholar 

  2. Klopfer, E.: Augmented Reality: Research and Design of Mobile Educational Games. The MIT Press, Cambridge (2008)

    Book  Google Scholar 

  3. National Research Council: Taking Science to School: Learning and Teaching Science in Grades K-8. National Academies Press, Washington (2007)

    Google Scholar 

  4. Bitgood, S.: School field trips: an overview. Visit. Behav. 5(2), 3–6 (1989)

    Google Scholar 

  5. Garner, L., Gallo, M.: Field trips and their effects on student achievement and attitudes: a comparison of physical versus virtual field trips to the Indian river lagoon. J. Coll. Sci. Teach. 34(5), 14–17 (2005)

    Google Scholar 

  6. Gottfried, J.: Do children learn on field trips? Curator: Mus. J. 23, 165–174 (1980)

    Article  Google Scholar 

  7. Knapp, D., Barrie, E.: Content evaluation of an environmental science field trip. J. Sci. Educ. Technol. 10(4), 351–357 (2001)

    Article  Google Scholar 

  8. Ballantyne, R., Packer, J.: Nature-based excursions: school students’ perceptions of learning in natural environments. Int. Res. Geograph. Environ. Educ. 11(3), 218–230 (2002)

    Article  Google Scholar 

  9. Manzanal, R.F., Rodriguez Barreiro, L., Casal Jimenez, M.: Relationship between ecology fieldwork and student attitudes toward environmental protection. J. Res. Sci. Teach. 36(4), 431–453 (1999)

    Article  Google Scholar 

  10. Bogner, F.X.: The influence of short-term outdoor ecology education on long-term variables of environmental perspective. J. Environ. Educ. 29(4), 17–29 (1998)

    Article  Google Scholar 

  11. Falk, J.H.: Field trips: a look at environmental effects on learning. J. Biolog. Educ. 17(2), 137–142 (1983). Routledge

    Article  MathSciNet  Google Scholar 

  12. Orion, N., Hofstein, A.: Factors that influence learning during a scientific field trip in a natural environment. J. Res. Sci. Teach. 31(10), 1097–1119 (1994)

    Article  Google Scholar 

  13. Eberbach, C., Crowley, K.: From everyday to scientific observation: how children learn to observe the biologist’s world. Rev. Educ. Res. 79(1), 39–68 (2009). https://doi.org/10.3102/0034654308325899

    Article  Google Scholar 

  14. Dunleavy, M., Dede, C., Mitchell, R.: Affordances and limitations of immersive participatory augmented reality simulations for teaching and learning. J. Sci. Educ. Technol. 18(1), 7–22 (2009)

    Article  Google Scholar 

  15. Kamarainen, A.M., Metcalf, S., Grotzer, T., Browne, A., Mazzuca, D., Tutwiler, M.S., Dede, C.: EcoMOBILE: integrating augmented reality and probeware with environmental education field trips. Comput. Educ. 68, 545–556 (2013)

    Article  Google Scholar 

  16. Perry, J., Klopfer, E., Norton, M., Sutch, D., Sandford, R., Facer, K.: AR gone wild: two approaches to using augmented reality learning games in zoos. In: Proceedings of the International Conference on the Learning Sciences (ICLS), The Netherlands (2008)

    Google Scholar 

  17. Squire, K., Jan, M.: Mad city mystery: developing scientific argumentation skills with a place-based augmented reality game on handheld computers. J. Sci. Educ. Technol. 16(1), 5–29 (2007)

    Article  Google Scholar 

  18. Squire, K., Klopfer, E.: Augmented reality simulations on handheld computers. J. Learn. Sci. 16(3), 371–413 (2007)

    Article  Google Scholar 

  19. Schwartz, D.L., Tsang, J.M., Blair, K.P.: The ABCs of How We Learn: 26 Scientifically Proven Approaches, How They Work, and When to Use Them. WW Norton & Company, New York (2016)

    Google Scholar 

  20. Antonioli, M., Blake, C., Sparks, K.: Augmented reality applications in education. J. Technol. Stud. 40, 96–107 (2014)

    Article  Google Scholar 

  21. Billinghurst, M.: Augmented reality in education. New Horiz. Learn. 12(5), 314 (2002)

    Google Scholar 

  22. Metcalf, S., Kamarainen, A., Tutwiler, M.S., Grotzer, T., Dede, C.: Ecosystem science learning via multi-user virtual environments. Int. J. Gaming Comput.-Mediat. Simul. (IJGCMS) 3(1), 86–90 (2011)

    Article  Google Scholar 

  23. Grotzer, T.A., Kamarainen, A., Tutwiler, M.S., Metcalf, S., Dede, C.: Learning to reason about ecosystems dynamics over time: the challenges of an event-based causal focus. Bioscience 63(4), 288–296 (2013)

    Article  Google Scholar 

  24. Kamarainen, A.M., Metcalf, S., Grotzer, T., Dede, C.: Exploring ecosystems from the inside: how immersive multi-user virtual environments can support development of epistemologically grounded modeling practices in ecosystem science instruction. J. Sci. Educ. Technol. 24(2–3), 148–167 (2015)

    Article  Google Scholar 

  25. Creswell, J.W., Creswell, J.D.: Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage Publications, Thousand Oaks (2017)

    MATH  Google Scholar 

  26. Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33, 159–174 (1977)

    Article  Google Scholar 

  27. Carey, J.W., Morgan, M., Oxtoby, M.J.: Intercoder agreement in analysis of responses to open-ended interview questions: examples from tuberculosis research. Cult. Anthropol. Methods 8(3), 1–5 (1996)

    Google Scholar 

  28. Perkins, D.N., Jay, E., Tishman, S.: Beyond abilities: a dispositional theory of thinking. Merrill-Palmer Q. 39, 1–21 (1993)

    Google Scholar 

  29. Grotzer, T.A., Tutwiler, M.S., Kamarainen, A.M., Derbiszewska, K.M., Metcalf, S.J., Dede, C.J.: Students’ reasoning tendencies about the causal dynamics of ecosystems and the impacts of MUVE vs. non-MUVE instructional contexts. In: The Next Phase of Research in Complex Systems in Science Education, American Educational Research Association (AERA) Conference, Washington D.C, April 2016

    Google Scholar 

  30. Grotzer, T.A., Basca, B.B.: How does grasping the underlying causal structures of ecosystems impact students’ understanding? J. Biol. Educ. 38(1), 16–29 (2003)

    Article  Google Scholar 

Download references

Acknowledgments

We would like to express our appreciation to Lindsay Evans, Jared B. Fries, Ihudiya Ogbonnaya-Ogburu, Shruthi Lakshmi Saravanan, and Mayer Chalom for their assistance in coding the data. EcoMOBILE research was supported by National Science Foundation grant no. 1118530 and by Qualcomm Wireless Reach Initiative. AR activities were developed using FreshAiR by MoGo Mobile, Inc. TI Nspire graphing calculators with Vernier probes were provided by Texas Instruments, Inc. All opinions, findings, conclusions, or recommendations expressed here are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Amy M. Kamarainen .

Editor information

Editors and Affiliations

Appendix

Appendix

Coding scheme applied to the responses collected during the field trip as well as the in-class written paragraphs.

Type of code

Name

Description

Factor

Plants

Trees, shrubs, plants

Factor

Aquatic plants

Underwater plants, duckweed

Factor

Algae

Algae or microscopic plants

Factor

Sunlight

Sun, sunlight, trees blocking the sun, shade

Factor

Animals

Fish, species, animals

Factor

Organisms

Living things (distinguished from animals because it can’t be understood whether it is a net producer or consumer of oxygen)

Factor

Bacteria

 

Factor

Dead matter

 

Factor

Water temperature

 

Factor

Wind/wind speed

 

Factor

Rain

 

Factor

Turbidity

Murky, water is dirty/cloudy

Factor

Location/area

Refers to areas around the pond; “there were woods next to the pond”

Factor

Size of the pond

Depth, amount of water

Factor

Human impact - EcoMUVE

Fertilizer, distance from houses

Factor

Human impact - other

Chemicals, pollution, cars, sewage

Process

Photosynthesis

Describes the process of photosynthesis or calls it by name

Process

Respiration

Describes the process of respiration or calls it by name

Process

Decomposition

Describes the process of decomposition or calls it by name

Process

Mixing

Water movement, mixes oxygen in, flow

Aggregate

Add Oxygen

Factors or processes that have a net positive effect on D.O. concentration. This includes plants, aquatic plants, algae, wind, photosynthesis, mixing

Aggregate

Take Up Oxygen

Factors or processes that have a net negative effect on D.O. concentration. This includes animals, bacteria, dead matter, respiration, decomposition

Aggregate

Weather

Factors related to the weather. This includes rain, wind, air temperature

Aggregate

Direct

Factors that are considered to have a direct impact on dissolved oxygen concentrations. This includes plants, aquatic plants, algae, animals, bacteria, organisms, wind, water temperature, photosynthesis, respiration, decomposition, mixing

Aggregate

Indirect

Factors that are considered to have an indirect impact on dissolved oxygen concentrations. This includes sunlight, dead matter, rain, air temperature, turbidity, human impacts

Aggregate

Visible

Factors that affect dissolved oxygen and are visible. This includes plants, aquatic plants, sunlight, rain, animals, organisms

Aggregate

Invisible

Factors that affect dissolved oxygen and are not visible. This includes algae, bacteria

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kamarainen, A.M., Thompson, M., Metcalf, S.J., Grotzer, T.A., Tutwiler, M.S., Dede, C. (2018). Prompting Connections Between Content and Context: Blending Immersive Virtual Environments and Augmented Reality for Environmental Science Learning. In: Beck, D., et al. Immersive Learning Research Network. iLRN 2018. Communications in Computer and Information Science, vol 840. Springer, Cham. https://doi.org/10.1007/978-3-319-93596-6_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-93596-6_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93595-9

  • Online ISBN: 978-3-319-93596-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics