The Efficacy of Virtual Reality in Climate Change Education Increases with Amount of Body Movement and Message Specificity
Abstract
:1. Introduction
2. Materials and Methods
2.1. Developing Remote Data Collection
2.2. Stanford Ocean Acidification Experience (SOAE) Versions
2.3. Measuring Subjective Variables
2.4. Measuring Movement
2.5. Statistics
2.6. Participants
3. Results
4. Discussion
Limitations
5. Conclusions and Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Hypothesis | Subhypothesis | Test Statistic, Significance Level (Uncorrected), Effect Size, and Confidence Interval | Result | Conclusion |
---|---|---|---|---|
H1: Participants in segmented conditions will score higher for learning than participants in non-segmented conditions. | F (1, 276) = 0.276 p = 0.599 η2 p < 0.001 [0.00, 0.02] | Not supported | There was no significant difference in learning between having pauses or not during the experience. | |
H2: Participants in non-segmented conditions will score higher for presence than participants in segmented conditions. | F (1, 292) = 0.042 p = 0.837 η2 p < 0.001 [0.00, 0.01] | Not supported | Adding pauses to the experience did not significantly influence participants’ feelings of presence. | |
H3: Participants in standing conditions will score higher for learning, behavior, concern, risk perception, causes, beliefs about increased carbon dioxide emissions, presence, self-efficacy, and trust than participants in seated conditions. | (a) learning | F (1, 289) = 0.210 p = 0.647 η2 p < 0.001 [0.00, 0.01] | Not supported | Having a standing VR experience elicited higher feelings of presence and self-efficacy than having a seated VR experience. |
(b) behavior | χ2(1) = 0.857 p = 0.354 Std. coef = −0.46 [−1.44, 0.51] | Not supported | ||
(c) concern | F (1, 223) = 0.065 p = 0.798 η2 p < 0.001 [0.00, 0.01] | Not supported | ||
(d) risk perception | F (1, 292) = 0.485 p = 0.487 η2 p < 0.01 [0.00, 0.02] | Not supported | ||
(e) causes | Estimate = 0.455 p = 0.347 Std. coef = 0.46 [−0.50, 1.41] | Not supported | ||
(f) beliefs about increased carbon dioxide emissions | F (1, 292) = 0.003 p = 0.986 η2 p < 0.001 [0.00, 0.00] | Not supported | ||
(g) presence | F (1, 292) = 4.541 p = 0.034 η2 p = 0.02 [0.00, 0.05] | Supported | ||
(h) self-efficacy | F (1, 292) = 12.540 p < 0.001 η2 p = 0.04 [0.01, 0.08] | Supported | ||
(i) trust | F (1, 143) = 1.632 p ≤ 0.203 η2 p = 0.01 [0.00, 0.06] | Not supported | ||
H4: Participants in female-voiced conditions will score higher for learning than participants in male-voiced conditions. | F (1, 275) = 0.004 p = 0.952 η2 p < 0.001 [0.00, 0.00] | Not supported | The sex of the voice-over did not influence learning. | |
H5: Results for self-efficacy comparing female-voiced and male-voiced conditions will be gender-dependent, with females scoring higher than males in female-voiced conditions and vice versa. | (a) women will score higher than men for self-efficacy in female-voiced narration conditions | F (1, 147) = 10.45 p = 0.001 η2 p = 0.07 [0.02, 0.14] | Not supported | Men scored higher for self-efficacy toward science than women, regardless of the sex of the voice-over. |
(b) men will score higher than women for self-efficacy in male-voiced narration conditions | F (1, 143) = 9.261 p = 0.002 η2 p = 0.06 [0.01, 0.13] | Supported | ||
H6: Participants in male-voiced conditions will score higher for trust than participants in female-voiced conditions. | F (1, 289) = 0.526 p = 0.469 η2 p < 0.001 [0.00, 0.02] | Not supported | The gender of the voice-over had no significant effect on how much participants trusted the information received. | |
H7: Participants in climate change framing conditions who score higher in the political spectrum (i.e., left/liberal) will score higher for learning, behavior, concern, risk perception, causes, beliefs about increased carbon dioxide emissions, and trust than participants that score lower in the political spectrum (i.e., right/conservative). | (a) behavior | χ2(1) = 0.270 p = 0.869 Std. coef = 0.04 [−0.41, 0.50] | Not supported | Participants with a tendency for a left/liberal political view scored higher for their risk perception, concern, and beliefs about OA and how much they trusted the information received than participants with a right/conservative political view. |
(b) concern | F (1, 149) = 5.044 p = 0.026 η2 p = 0.03 [0.00, 0.09] | Supported | ||
(c) risk perception | F (1, 150) = 22.533 p < 0.001 η2 p = 0.13 [0.06, 0.22] | Supported | ||
(d) causes | Estimate = 0.576 p = 0.007 Std. coef = 0.76 [0.21, 1.32] | Supported | ||
(e) beliefs | F (1, 150) = 4.756 p = 0.031 η2 p = 0.03 [0.00, 0.09] | Supported | ||
(f) learning | F (1, 146) = 0.103 p = 0.749 η2 p < 0.001 [0.00, 0.02] | Not supported | ||
(g) trust | F (1, 148) = 5.453 p = 0.021 η2 p = 0.04 [0.00, 0.10] | Supported |
References
- Heating up. Nat. Clim. Chang. 2022, 12, 693. [CrossRef]
- Masson-Delmotte, V.; Zhai, P.; Pirani, A.; Connors, S.L.; Péan, C.; Berger, S.; Caud, N.; Chen, Y.; Goldfarb, L.; Gomis, M.I.; et al. (Eds.) IPCC Summary for Policymakers. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2021; pp. 3–32. [Google Scholar]
- Burger, F.A.; Terhaar, J.; Frölicher, T.L. Compound Marine Heatwaves and Ocean Acidity Extremes. Nat. Commun. 2022, 13, 4722. [Google Scholar] [CrossRef] [PubMed]
- King, A.D.; Peel, J.; Ziehn, T.; Bowen, K.J.; McClelland, H.L.O.; McMichael, C.; Nicholls, Z.R.J.; Sniderman, J.M.K. Preparing for a Post-Net-Zero World. Nat. Clim. Chang. 2022, 12, 775–777. [Google Scholar] [CrossRef]
- McKinley, G.A.; Fay, A.R.; Eddebbar, Y.A.; Gloege, L.; Lovenduski, N.S. External Forcing Explains Recent Decadal Variability of the Ocean Carbon Sink. AGU Adv. 2020, 1, e2019AV000149. [Google Scholar] [CrossRef]
- Doney, S.C.; Fabry, V.J.; Feely, R.A.; Kleypas, J.A. Ocean Acidification: The Other CO2 Problem. Ann. Rev. Mar. Sci. 2009, 1, 169–192. [Google Scholar] [CrossRef] [Green Version]
- Doney, S.C.; Busch, D.S.; Cooley, S.R.; Kroeker, K.J. The Impacts of Ocean Acidification on Marine Ecosystems and Reliant Human Communities. Annu. Rev. Environ. Resour. 2020, 45, 83–112. [Google Scholar] [CrossRef]
- Goldenberg, S.U.; Nagelkerken, I.; Ferreira, C.M.; Ullah, H.; Connell, S.D. Boosted Food Web Productivity through Ocean Acidification Collapses under Warming. Glob. Chang. Biol. 2017, 23, 4177–4184. [Google Scholar] [CrossRef]
- Guest, H.; Lotze, H.K.; Wallace, D. Youth and the Sea: Ocean Literacy in Nova Scotia, Canada. Mar. Policy 2015, 58, 98–107. [Google Scholar] [CrossRef]
- Grothmann, T.; Patt, A. Adaptive Capacity and Human Cognition: The Process of Individual Adaptation to Climate Change. Glob. Environ. Chang. 2005, 15, 199–213. [Google Scholar] [CrossRef]
- Kasperson, R.E.; Renn, O.; Slovic, P.; Brown, H.S.; Emel, J.; Goble, R.; Kasperson, J.X.; Ratick, S. The Social Amplification of Risk: A Conceptual Framework. Risk Anal. 1988, 8, 177–187. [Google Scholar] [CrossRef] [Green Version]
- Lindell, M.K.; Perry, R.W. The Protective Action Decision Model: Theoretical Modifications and Additional Evidence. Risk Anal. 2012, 32, 616–632. [Google Scholar] [CrossRef]
- Renn, O. The Social Amplification/Attenuation of Risk Framework: Application to Climate Change. WIREs Clim. Chang. 2011, 2, 154–169. [Google Scholar] [CrossRef]
- van Valkengoed, A.M.; Steg, L. Meta-Analyses of Factors Motivating Climate Change Adaptation Behaviour. Nat. Clim. Chang. 2019, 9, 158–163. [Google Scholar] [CrossRef] [Green Version]
- Nisa, C.F.; Bélanger, J.J.; Schumpe, B.M.; Faller, D.G. Meta-Analysis of Randomised Controlled Trials Testing Behavioural Interventions to Promote Household Action on Climate Change. Nat. Commun. 2019, 10, 4545. [Google Scholar] [CrossRef] [Green Version]
- Nielsen, K.S.; Marteau, T.M.; Bauer, J.M.; Bradbury, R.B.; Broad, S.; Burgess, G.; Burgman, M.; Byerly, H.; Clayton, S.; Espelosin, D.; et al. Biodiversity Conservation as a Promising Frontier for Behavioural Science. Nat. Hum. Behav. 2021, 5, 550–556. [Google Scholar] [CrossRef]
- Mickle, T.; Chen, B.X. Apple Starts Connecting the Dots for Its next Big Thing. The New York Times, 26 June 2022. [Google Scholar]
- Bailenson, J.N. Experience on Demand: What Virtual Reality Is, How It Works, and What It Can Do, 1st ed.; W.W. Norton & Company: New York, NY, USA, 2018; ISBN 0393253694. [Google Scholar]
- Fauville, G.; Queiroz, A.C.M.; Bailenson, J.N. Chapter 5 - Virtual Reality as a Promising Tool to Promote Climate Change Awareness. In Technology and Health: Promoting Attitude and Behavior Change; Academic Press: Cambridge, MA, USA, 2020; pp. 91–108. ISBN 9780128169582. [Google Scholar] [CrossRef]
- Box-Steffensmeier, J.M.; Burgess, J.; Corbetta, M.; Crawford, K.; Duflo, E.; Fogarty, L.; Gopnik, A.; Hanafi, S.; Herrero, M.; Hong, Y.; et al. The Future of Human Behaviour Research. Nat. Hum. Behav. 2022, 6, 15–24. [Google Scholar] [CrossRef]
- Markowitz, D.M.; Laha, R.; Perone, B.P.; Pea, R.D.; Bailenson, J.N. Immersive Virtual Reality Field Trips Facilitate Learning about Climate Change. Front. Psychol. 2018, 9, 2364. [Google Scholar] [CrossRef]
- Queiroz, A.C.M.; Fauville, G.; Herrera, F.; da Leme, M.I.d.S.; Bailenson, J.N. Do Students Learn Better with Immersive Virtual Reality Videos Than Conventional Videos? A Comparison of Media Effects with Middle School Girls. Technol. Mind Behav. 2022, 3, 82. [Google Scholar] [CrossRef]
- Mirauda, D.; Capece, N.; Erra, U. Sustainable Water Management: Virtual Reality Training for Open-Channel Flow Monitoring. Sustainability 2020, 12, 757. [Google Scholar] [CrossRef] [Green Version]
- Makransky, G.; Mayer, R.E. Benefits of Taking a Virtual Field Trip in Immersive Virtual Reality: Evidence for the Immersion Principle in Multimedia Learning. Educ. Psychol. Rev. 2022, 34, 1771–1798. [Google Scholar] [CrossRef]
- Ahn, S.J.; Bostick, J.; Ogle, E.; Nowak, K.L.; McGillicuddy, K.T.; Bailenson, J.N. Experiencing Nature: Embodying Animals in Immersive Virtual Environments Increases Inclusion of Nature in Self and Involvement with Nature. J. Comput. Commun. 2016, 21, 399–419. [Google Scholar] [CrossRef]
- Nelson, K.M.; Anggraini, E.; Schlüter, A. Virtual Reality as a Tool for Environmental Conservation and Fundraising. PLoS ONE 2020, 15, e0223631. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Fonseca, D.; Kraus, M. A Comparison of Head-Mounted and Hand-Held Displays for 360° Videos with Focus on Attitude and Behavior Change. In Proceedings of the Academic Mindtrek 2016—Proceedings of the 20th International Academic Mindtrek Conference, Tampere, Finland, 17–18 October 2016; pp. 287–296. [Google Scholar]
- Plechatá, A.; Morton, T.; Perez-Cueto, F.J.A.; Makransky, G. A Randomized Trial Testing the Effectiveness of Virtual Reality as a Tool for Pro-Environmental Dietary Change. Sci. Rep. 2022, 12, 14315. [Google Scholar] [CrossRef] [PubMed]
- Sundar, S.S.; Kang, J.; Oprean, D. Being There in the Midst of the Story: How Immersive Journalism Affects Our Perceptions and Cognitions. Cyberpsychol. Behav. Soc. Netw. 2017, 20, 672–682. [Google Scholar] [CrossRef] [PubMed]
- Lo, S.-C.; Tsai, H.-H. Design of 3D Virtual Reality in the Metaverse for Environmental Conservation Education Based on Cognitive Theory. Sensors 2022, 22, 8329. [Google Scholar] [CrossRef]
- Plechatá, A.; Morton, T.; Perez-Cueto, F.J.A.; Makransky, G. Why Just Experience the Future When You Can Change It: Virtual Reality Can Increase Pro-Environmental Food Choices Through Self-Efficacy. Technol. Mind Behav. 2022, 3. [Google Scholar] [CrossRef]
- Monroe, M.C.; Plate, R.R.; Oxarart, A.; Bowers, A.; Chaves, W.A. Identifying Effective Climate Change Education Strategies: A Systematic Review of the Research. Environ. Educ. Res. 2019, 25, 791–812. [Google Scholar] [CrossRef]
- Landrum, A.R.; Eaves, B.S.; Shafto, P. Learning to Trust and Trusting to Learn: A Theoretical Framework. Trends Cogn. Sci. 2015, 19, 109–111. [Google Scholar] [CrossRef]
- Sweller, J. Implications of Cognitive Load Theory for Multimedia Learning. Camb. Handb. Multimed. Learn. 2005, 3, 19–30. [Google Scholar] [CrossRef]
- Mayer, R.E.; Colvin Clark, R. Instructional Strategies for Receptive Learning Environments. In Handbook of Improving Performance in the Workplace; Wiley: New York, NY, USA, 2009; Volume 1–3, pp. 298–328. [Google Scholar]
- Clark, R.C.; Mayer, R.E. Learning by Viewing versus Learning by Doing: Evidence-Based Guidelines for Principled Learning Environments. Perform. Improv. 2008, 47, 5–13. [Google Scholar] [CrossRef]
- Mayer, R.E.; Moreno, R. Nine Ways to Reduce Cognitive Load in Multimedia Learning. Educ. Psychol. 2003, 38, 43–52. [Google Scholar] [CrossRef] [Green Version]
- Nelson, B.C.; Erlandson, B.E. Managing Cognitive Load in Educational Multi-User Virtual Environments: Reflection on Design Practice. Educ. Technol. Res. Dev. 2008, 56, 619–641. [Google Scholar] [CrossRef]
- Parong, J.; Mayer, R.E. Learning Science in Immersive Virtual Reality. J. Educ. Psychol. 2018, 110, 785–797. [Google Scholar] [CrossRef]
- Wang, Y.; Wang, F.; Mayer, R.E.; Hu, X.; Gong, S. Benefits of Prompting Students to Generate Summaries during Pauses in Segmented Multimedia Lessons. J. Comput. Assist. Learn. 2023. [Google Scholar] [CrossRef]
- Sanchez-Vives, M.V.; Slater, M. From Presence to Consciousness through Virtual Reality. Nat. Rev. Neurosci. 2005, 6, 332. [Google Scholar] [CrossRef]
- Ahn, S.J.; Nowak, K.L.; Bailenson, J.N. Unintended Consequences of Spatial Presence on Learning in Virtual Reality. Comput. Educ. 2022, 186, 104532. [Google Scholar] [CrossRef]
- Mayer, R.E.; Makransky, G.; Parong, J. The Promise and Pitfalls of Learning in Immersive Virtual Reality. Int. J. Human Comput. Interact. 2022. [Google Scholar] [CrossRef]
- Barsalou, L.W. Grounded Cognition. Annu. Rev. Psychol. 2008, 59, 617–645. [Google Scholar] [CrossRef] [Green Version]
- Glenberg, A.M. Embodiment as a Unifying Perspective for Psychology. WIREs Cogn. Sci. 2010, 1, 586–596. [Google Scholar] [CrossRef]
- Goldin-Meadow, S. Hearing Gesture; Harvard University Press: Cambridge, MA, USA, 2003; ISBN 9780674010727. [Google Scholar]
- Goldin-Meadow, S.; Cook, S.W.; Mitchell, Z.A. Gesturing Gives Children New Ideas About Math. Psychol. Sci. 2009, 20, 267–272. [Google Scholar] [CrossRef] [Green Version]
- Hostetter, A.B.; Alibali, M.W. Visible Embodiment: Gestures as Simulated Action. Psychon. Bull. Rev. 2008, 15, 495–514. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Niedenthal, P.M.; Barsalou, L.W.; Winkielman, P.; Krauth-Gruber, S.; Ric, F. Embodiment in Attitudes, Social Perception, and Emotion. Personal. Soc. Psychol. Rev. 2005, 9, 184–211. [Google Scholar] [CrossRef] [PubMed]
- Stern, E. Embodied Cognition: A Grasp on Human Thinking. Nature 2015, 524, 158–159. [Google Scholar] [CrossRef] [Green Version]
- Clark, A. An Embodied Cognitive Science? Trends Cogn. Sci. 1999, 3, 345–351. [Google Scholar] [CrossRef] [PubMed]
- Kilteni, K.; Groten, R.; Slater, M. The Sense of Embodiment in Virtual Reality. Presence Teleoperators Virtual Environ. 2012, 21, 373–387. [Google Scholar] [CrossRef] [Green Version]
- David, N.; Newen, A.; Vogeley, K. The “Sense of Agency” and Its Underlying Cognitive and Neural Mechanisms. Conscious. Cogn. 2008, 17, 523–534. [Google Scholar] [CrossRef]
- Wahlheim, C.N.; Eisenberg, M.L.; Stawarczyk, D.; Zacks, J.M. Understanding Everyday Events: Predictive-Looking Errors Drive Memory Updating. Psychol. Sci. 2022, 33, 765–781. [Google Scholar] [CrossRef]
- Roselli, C.; Ciardo, F.; De Tommaso, D.; Wykowska, A. Human-Likeness and Attribution of Intentionality Predict Vicarious Sense of Agency over Humanoid Robot Actions. Sci. Rep. 2022, 12, 13845. [Google Scholar] [CrossRef]
- Bandura, A. Self-Efficacy in Changing Societies; Cambridge University Press: Cambridge, MA, USA, 1995. [Google Scholar]
- Moser, S.C. Communicating Climate Change: History, Challenges, Process and Future Directions. Wiley Interdiscip. Rev. Clim. Chang. 2010, 1, 31–53. [Google Scholar] [CrossRef]
- Crowelly, C.R.; Villanoy, M.; Scheutzz, M.; Schermerhornz, P. Gendered Voice and Robot Entities: Perceptions and Reactions of Male and Female Subjects. In Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA, 10–15 October 2009; pp. 3735–3741. [Google Scholar]
- Ghazali, A.S.; Ham, J.; Barakova, E.I.; Markopoulos, P. Effects of Robot Facial Characteristics and Gender in Persuasive Human-Robot Interaction. Front. Robot. AI 2018, 5, 73. [Google Scholar] [CrossRef] [Green Version]
- Sandygulova, A.; O’Hare, G.M.P. Age- and Gender-Based Differences in Children’s Interactions with a Gender-Matching Robot. Int. J. Soc. Robot. 2018, 10, 687–700. [Google Scholar] [CrossRef]
- Nass, C.; Moon, Y.; Green, N. Are Machines Gender Neutral? Gender-Stereotypic Responses to Computers With Voices. J. Appl. Soc. Psychol. 1997, 27, 864–876. [Google Scholar] [CrossRef]
- Lee, E.J.; Nass, C.; Brave, S. Can Computer-Generated Speech Have Gender? An Experimental Test of Gender Stereotype. In Proceedings of the CHI ’00 Extended Abstracts on Human Factors in Computing Systems, The Hague, The Netherlands, 1–6 April 2000; Association for Computing Machinery: New York, NY, USA, 2000; pp. 289–290. [Google Scholar]
- Nass, C.; Moon, Y. Machines and Mindlessness: Social Responses to Computers. J. Soc. Issues 2000, 56, 81–103. [Google Scholar] [CrossRef]
- Khashe, S.; Lucas, G.; Becerik-Gerber, B.; Gratch, J. Buildings with Persona: Towards Effective Building-Occupant Communication. Comput. Human Behav. 2017, 75, 607–618. [Google Scholar] [CrossRef]
- Liu, S.R. Gendered Science Communication: The Role of Speaker Gender & Pitch in Perceived Credibility and Persuasion of Climate Science. Doctoral Dissertation, University of Pennsylvania, Philadelphia, PA, USA, 2022. [Google Scholar]
- Entman, R.M. Framing: Toward Clarification of a Fractured Paradigm. J. Commun. 1993, 43, 51–58. [Google Scholar] [CrossRef]
- Nisbet, M.C. Communicating Climate Change: Why Frames Matter for Public Engagement. Environ. Sci. Policy Sustain. Dev. 2009, 51, 12–23. [Google Scholar] [CrossRef]
- Boykoff, M.T. Who Speaks for the Climate?: Making Sense of Media Reporting on Climate Change; Cambridge University Press: Cambridge, UK, 2011. [Google Scholar]
- Morton, T.A.; Rabinovich, A.; Marshall, D.; Bretschneider, P. The Future That May (or May Not) Come: How Framing Changes Responses to Uncertainty in Climate Change Communications. Glob. Environ. Chang. 2011, 21, 103–109. [Google Scholar] [CrossRef]
- Whitmarsh, L.; Xenias, D.; Jones, C.R. Framing Effects on Public Support for Carbon Capture and Storage. Palgrave Commun. 2019, 5, 17. [Google Scholar] [CrossRef] [Green Version]
- Eslen-Ziya, H. Humour and Sarcasm: Expressions of Global Warming on Twitter. Humanit. Soc. Sci. Commun. 2022, 9, 240. [Google Scholar] [CrossRef]
- Davis, J.J. The Effects of Message Framing on Response to Environmental Communications. J. Mass Commun. Q. 1995, 72, 285–299. [Google Scholar] [CrossRef]
- Ahn, S.J.; Fox, J.; Dale, K.R.; Avant, J.A. Framing Virtual Experiences: Effects on Environmental Efficacy and Behavior Over Time. Commun. Res. 2015, 42, 839–863. [Google Scholar] [CrossRef]
- Dickinson, J.L.; Crain, R.; Yalowitz, S.; Cherry, T.M. How Framing Climate Change Influences Citizen Scientists’ Intentions to Do Something About It. J. Environ. Educ. 2013, 44, 145–158. [Google Scholar] [CrossRef]
- Diamond, E.; Urbanski, K. The Impact of Message Valence on Climate Change Attitudes: A Longitudinal Experiment. Environ. Commun. 2022, 16, 1046–1058. [Google Scholar] [CrossRef]
- Bain, P.G.; Hornsey, M.J.; Bongiorno, R.; Jeffries, C. Promoting Pro-Environmental Action in Climate Change Deniers. Nat. Clim. Chang. 2012, 2, 600–603. [Google Scholar] [CrossRef]
- Audretsch, D.B.; Feldman, M.P. R&D Spillovers and the Geography of Innovation and Production. Am. Econ. Rev. 1996, 86, 630–640. [Google Scholar]
- Cooke, S.L.; Kim, S.C. Exploring the “Evil Twin of Global Warming”: Public Understanding of Ocean Acidification in the United States. Sci. Commun. 2019, 41, 66–89. [Google Scholar] [CrossRef]
- Kahan, D.M. Ideology, Motivated Reasoning, and Cognitive Reflection: An Experimental Study. Judgm. Decis. Mak. 2012, 8, 407–424. [Google Scholar] [CrossRef]
- Guilbeault, D.; Becker, J.; Centola, D. Social Learning and Partisan Bias in the Interpretation of Climate Trends. Proc. Natl. Acad. Sci. USA 2018, 115, 9714–9719. [Google Scholar] [CrossRef] [Green Version]
- Google Google Sheets API Overview. Available online: https://developers.google.com/sheets/api (accessed on 10 March 2023).
- Fauville, G.; Strang, C.; Cannady, M.A.; Chen, Y.-F. Development of the International Ocean Literacy Survey: Measuring Knowledge across the World. Environ. Educ. Res. 2019, 25, 238–263. [Google Scholar] [CrossRef] [Green Version]
- Li, B.J.; Bailenson, J.N.; Pines, A.; Greenleaf, W.J.; Williams, L.M. A Public Database of Immersive VR Videos with Corresponding Ratings of Arousal, Valence, and Correlations between Head Movements and Self Report Measures. Front. Psychol. 2017, 8, 2116. [Google Scholar] [CrossRef]
- Kuznetsova, A.; Brockhoff, P.B.; Christensen, R.H.B. Package ‘Lmertest’. R Packag. Version 2015, 2, 734. [Google Scholar]
- Lüdecke, D.; Lüdecke, M.D. Package ‘SjPlot’. R Packag. Version 2015, 1. [Google Scholar]
- Fox, J.; Weisberg, S.; Adler, D.; Bates, D.; Baud-Bovy, G.; Ellison, S.; Firth, D.; Friendly, M.; Gorjanc, G.; Graves, S.; et al. Package ‘Car’. Vienna R Found. Stat. Comput. 2012, 16. [Google Scholar]
- Vatcheva, K.P.; Lee, M.; McCormick, J.B.; Rahbar, M.H. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies. Epidemiology 2016, 6, 227. [Google Scholar] [CrossRef] [Green Version]
- Ben-Shachar, M.S.; Lüdecke, D.; Makowski, D. Effectsize: Estimation of Effect Size Indices and Standardized Parameters. J. Open Source Softw. 2020, 5, 2815. [Google Scholar] [CrossRef]
- Lakens, D. Calculating and Reporting Effect Sizes to Facilitate Cumulative Science: A Practical Primer for t-Tests and ANOVAs. Front. Psychol. 2013, 4, 863. [Google Scholar] [CrossRef] [Green Version]
- Villena-Taranilla, R.; Tirado-Olivares, S.; Cózar-Gutiérrez, R.; González-Calero, J.A. Effects of Virtual Reality on Learning Outcomes in K-6 Education: A Meta-Analysis. Educ. Res. Rev. 2022, 35, 100434. [Google Scholar] [CrossRef]
- Jensen, L.; Konradsen, F. A Review of the Use of Virtual Reality Head-Mounted Displays in Education and Training. Educ. Inf. Technol. 2018, 23, 1515–1529. [Google Scholar] [CrossRef] [Green Version]
- Queiroz, A.C.M.; Tori, R.; Moreira, N.A.; da Silva Leme, M.I. Using HMD-Based Immersive Virtual Environments in Primary/K-12 Education. Commun. Comput. Inf. Syst. 2018, 840, 160–173. [Google Scholar]
- Makransky, G.; Petersen, G.B. The Cognitive Affective Model of Immersive Learning (CAMIL): A Theoretical Research-Based Model of Learning in Immersive Virtual Reality. Educ. Psychol. Rev. 2021, 33, 937–958. [Google Scholar] [CrossRef]
- Heilbron, M.; Armeni, K.; Schoffelen, J.-M.; Hagoort, P.; de Lange, F.P. A Hierarchy of Linguistic Predictions during Natural Language Comprehension. Proc. Natl. Acad. Sci. USA 2022, 119, e2201968119. [Google Scholar] [CrossRef]
- Dickinson, J.L. The People Paradox: Self-Esteem Striving, Immortality Ideologies, and Human Response to Climate Change. Ecol. Soc. 2009, 14, 34. [Google Scholar] [CrossRef] [Green Version]
- Pyszczynski, T.; Greenberg, J.; Solomon, S. A Dual-Process Model of Defense against Conscious and Unconscious Death-Related Thoughts: An Extension of Terror Management Theory. Psychol. Rev. 1999, 106, 835–845. [Google Scholar] [CrossRef] [PubMed]
- Lakoff, G.; Johnson, M. The Metaphorical Structure of the Human Conceptual System. Cogn. Sci. 1980, 4, 195–208. [Google Scholar] [CrossRef]
- Krange, O.; Kaltenborn, B.P.; Hultman, M. “Don’t Confuse Me with Facts”—How Right Wing Populism Affects Trust in Agencies Advocating Anthropogenic Climate Change as a Reality. Humanit. Soc. Sci. Commun. 2021, 8, 255. [Google Scholar] [CrossRef]
- Sparkman, G.; Geiger, N.; Weber, E.U. Americans Experience a False Social Reality by Underestimating Popular Climate Policy Support by Nearly Half. Nat. Commun. 2022, 13, 4779. [Google Scholar] [CrossRef]
- Abeles, A.T.; Howe, L.C.; Krosnick, J.A.; MacInnis, B. Perception of Public Opinion on Global Warming and the Role of Opinion Deviance. J. Environ. Psychol. 2019, 63, 118–129. [Google Scholar] [CrossRef]
- Ehret, P.J.; Van Boven, L.; Sherman, D.K. Partisan Barriers to Bipartisanship: Understanding Climate Policy Polarization. Soc. Psychol. Personal. Sci. 2018, 9, 308–318. [Google Scholar] [CrossRef] [Green Version]
- McCright, A.M. Political Orientation Moderates Americans’ Beliefs and Concern about Climate Change. Clim. Chang. 2011, 104, 243–253. [Google Scholar] [CrossRef]
- McCright, A.M.; Dunlap, R.E. The Politicization of Climate Change and Polarization in the American Public’s Views of Global Warming, 2001–2010. Sociol. Q. 2011, 52, 155–194. [Google Scholar] [CrossRef]
- Bergkvist, L. Appropriate Use of Single-Item Measures Is Here to Stay. Mark. Lett. 2015, 26, 245–255. [Google Scholar] [CrossRef]
- Allen, M.S.; Iliescu, D.; Greiff, S. Single Item Measures in Psychological Science: A Call to Action. Eur. J. Psychol. Assess. 2022, 38, 1–5. [Google Scholar] [CrossRef]
Variable | Question | Coding |
---|---|---|
Learning | 1. The ocean absorbs and stores which of the following from the atmosphere? | 0 (incorrect) or 1 (correct) |
Learning | 2. Which of the following causes ocean acidification? | 0 (incorrect) or 1 (correct) |
Learning | 3. Which of the following is a result of human-caused carbon dioxide emissions? | 0 (incorrect) or 1 (correct) |
Learning | 4. Clams, oysters, and other marine organisms use the carbon dissolved in the ocean to: | 0 (incorrect) or 1 (correct) |
Learning | 5. The formula for carbonic acid is: | 0 (incorrect) or 1 (correct) |
Learning | 6. Which human activity contributes a significant amount to greenhouse gas emissions? | 0 (incorrect) or 1 (correct) |
Learning | 7. What can scientists observe in the rocky reef off the coast of Naples, Italy? | 0 (incorrect) or 1 (correct) |
Learning | 8. How does ocean acidification impact all shelled species? | 0 (incorrect) or 1 (correct) |
Subjective knowledge | After this experience, how much, if anything, would you say you know about ocean acidification? | 5-point Likert scale: 1 (nothing) to 5 (a great deal) |
Concern | How concerned, if at all, are you about the health of the ocean? | 5-point Likert scale: 1 (not at all) to 5 (extremely) |
Risk perception | How serious of a problem do you think the increased amount of carbon dioxide in the atmosphere is for the health of the ocean? | 5-point Likert scale: 1 (not at all) to 5 (extremely) |
Beliefs | Do you think the amount of carbon dioxide in the atmosphere has been going up over the past 100 years, or do you think this has not been happening? | 4-point Likert scale: 1 (definitely not) to 4 (definitely yes) |
Causes | The increased amount of carbon dioxide in the atmosphere was caused: | Ordinal response: (1) mostly by natural causes; (2) about equally by things people did and natural causes; (3) mostly by things people did. |
Self-efficacy | How confident are you that you can understand most complex material in science courses? | 5-point Likert scale: 1 (not at all) to 5 (extremely) |
Presence | To what extent did you feel you were really inside the virtual world? | 5-point Likert scale: 1 (not at all) to 5 (very strongly) |
Trust | How much do you trust the information that you got from this virtual reality experience? | 5-point Likert scale: 1 (not at all) to 5 (completely) |
Political view | Some people talk about politics in terms of left, center, and right. On a left–right scale from 0 to 6, with 0 indicating extreme left (or extreme liberal) and 6 indicating extreme right (or extreme conservative), where would you place yourself? | From 1 (extreme right/conservative) to 7 (extreme left/liberal) |
Petition | People have started the following petition to ask the international community to take action to combat ocean acidification. Please read the petition. You will then have an opportunity to sign it. Tell the United Nations: It Is Time to Address Ocean Acidification Dear Secretary General Guterres, Right now, the ocean absorbs about a quarter of all carbon dioxide emissions, and this carbon dioxide changes the chemistry of the ocean. Without intervention, the ocean’s acidity level is expected to more than double by 2100. This will negatively impact shellfish, coral reefs, and all the people and organisms around the globe that depend on them. It is time for the United Nations to take meaningful steps to address ocean acidification. With scientific and technological advancements we, as a global community, can address this pressing issue. Please dedicate significant funding to support an international research agenda that aims to address and understand the threats we face from ocean acidification. You can sign this petition in the space below by holding down the trigger button. Signing this petition is completely optional, and your decision to sign or not sign will not affect your ability to continue participation in the research. Finally, your name will not be collected by us or connected with any of your survey responses. | 0 (not signed) or 1 (signed) |
Country | n = 305 | Gender | n = 305 | Race | n = 305 |
---|---|---|---|---|---|
U.S. | 262 (85.9%) | Woman | 171 (56%) | Afro-American | 16 (5.2%) |
Denmark | 20 (6.6%) | Man | 132 (43.3%) | Chinese | 15 (4.9%) |
Canada | 16 (5.2%) | Other | 2 (0.7%) | Filipino | 3 (1.0%) |
U.K. | 7 (2.3%) | Hispanic/Latinx | 11 (3.6%) | ||
Indian | 10 (3.3%) | ||||
Japanese | 3 (1.0%) | ||||
Korean | 4 (1.3%) | ||||
Mexican | 11 (3.6%) | ||||
Middle Eastern | 10 (3.3%) | ||||
Native American | 7 (2.3%) | ||||
Southeast Asian | 15 (4.9%) | ||||
White | 176 (58%) | ||||
More than one | 7 (2.3%) | ||||
Decline to answer | 8 (2.6%) | ||||
Unknown | 9 (3.0%) |
Segmentation | Movement | Voice-Over | Framing | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Variables | Non-Segmented (n = 140) | Segmented (n = 165) | Seated (n = 92) | Standing (n = 213) | Female (n = 156) | Male (n = 149) | Climate Change (n = 159) | Ocean Acidification (n = 146) | ||||||||
M | SD | M | SD | M | SD | M | SD | M | SD | M | SD | M | SD | M | SD | |
Learning | 0.77 | 0.21 | 0.79 | 0.23 | 0.83 | 0.18 | 0.76 | 0.23 | 0.77 | 0.23 | 0.79 | 0.22 | 0.76 | 0.23 | 0.80 | 0.21 |
Self-efficacy | 3.34 | 0.93 | 3.34 | 1.00 | 3.09 | 0.95 | 3.45 | 0.96 | 3.30 | 0.92 | 3.38 | 1.02 | 3.33 | 0.98 | 3.35 | 0.96 |
Behavior | 0.81 | 0.39 | 0.84 | 0.37 | 0.91 | 0.28 | 0.79 | 0.41 | 0.84 | 0.37 | 0.82 | 0.39 | 0.86 | 0.35 | 0.80 | 0.40 |
Presence | 3.76 | 0.87 | 3.80 | 0.91 | 3.58 | 0.92 | 3.87 | 0.86 | 3.70 | 0.90 | 3.87 | 0.88 | 3.75 | 0.88 | 3.81 | 0.91 |
Trust | 4.13 | 0.78 | 4.10 | 0.78 | 4.01 | 0.72 | 4.16 | 0.80 | 4.10 | 0.76 | 4.12 | 0.80 | 4.12 | 0.81 | 4.10 | 0.74 |
Concern | 3.96 | 0.90 | 3.98 | 0.88 | 4.00 | 0.85 | 3.96 | 0.91 | 3.94 | 0.87 | 4.01 | 0.91 | 4.03 | 0.90 | 3.90 | 0.88 |
Risk perception | 4.37 | 0.70 | 4.39 | 0.76 | 4.46 | 0.62 | 4.35 | 0.78 | 4.38 | 0.70 | 4.38 | 0.77 | 4.41 | 0.71 | 4.35 | 0.76 |
Beliefs | 3.66 | 0.54 | 3.74 | 0.52 | 3.73 | 0.47 | 3.69 | 0.56 | 3.66 | 0.58 | 3.75 | 0.46 | 3.73 | 0.52 | 3.68 | 0.54 |
Variable | M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
---|---|---|---|---|---|---|---|---|---|---|
1. Knowledge | 0.78 | 0.22 | ||||||||
2. Self-efficacy | 3.34 | 0.97 | 0.14 * | |||||||
[0.02, 0.24] | ||||||||||
3. Presence | 3.78 | 0.89 | 0.01 | 0.18 ** | ||||||
[−0.10, 0.12] | [0.07, 0.28] | |||||||||
4. Trust | 4.11 | 0.78 | 0.11 | 0.23 ** | 0.25 ** | |||||
[−0.00, 0.22] | [0.12, 0.33] | [0.15, 0.36] | ||||||||
5. Concern | 3.97 | 0.89 | 0.32 ** | 0.21 ** | 0.29 ** | 0.30 ** | ||||
[0.21, 0.41] | [0.10, 0.32] | [0.18, 0.39] | [0.19, 0.40] | |||||||
6. Risk perception | 4.38 | 0.74 | 0.27 ** | 0.20 ** | 0.18 ** | 0.40 ** | 0.58 ** | |||
[0.16, 0.37] | [0.09, 0.30] | [0.07, 0.29] | [0.30, 0.49] | [0.50, 0.65] | ||||||
7. Beliefs | 3.70 | 0.53 | 0.36 ** | 0.16 ** | 0.12 * | 0.26 ** | 0.39 ** | 0.48 ** | ||
[0.26, 0.46] | [0.05, 0.27] | [0.00, 0.22] | [0.16, 0.37] | [0.29, 0.48] | [0.38, 0.56] | |||||
8. Behavior | 0.83 | 0.38 | 0.14 * | −0.07 | −0.00 | 0.21 ** | 0.21 ** | 0.25 ** | 0.21 ** | |
[0.03, 0.25] | [−0.04, 0.18] | [−0.12, 0.11] | [0.10, 0.32] | [0.10, 0.32] | [0.14, 0.35] | [0.10, 0.31] | ||||
9. Political view | 4.39 | 1.26 | 0.23 ** | −0.10 | −0.12 * | 0.09 | 0.19 ** | 0.31 ** | 0.22 ** | 0.14 * |
[0.12, 0.33] | [−0.21, 0.01] | [−0.23, −0.00] | [−0.02, 0.20] | [0.08, 0.30] | [0.20, 0.41] | [0.11, 0.33] | [0.03, 0.25] |
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Queiroz, A.C.M.; Fauville, G.; Abeles, A.T.; Levett, A.; Bailenson, J.N. The Efficacy of Virtual Reality in Climate Change Education Increases with Amount of Body Movement and Message Specificity. Sustainability 2023, 15, 5814. https://doi.org/10.3390/su15075814
Queiroz ACM, Fauville G, Abeles AT, Levett A, Bailenson JN. The Efficacy of Virtual Reality in Climate Change Education Increases with Amount of Body Movement and Message Specificity. Sustainability. 2023; 15(7):5814. https://doi.org/10.3390/su15075814
Chicago/Turabian StyleQueiroz, Anna C. M., Géraldine Fauville, Adina T. Abeles, Aaron Levett, and Jeremy N. Bailenson. 2023. "The Efficacy of Virtual Reality in Climate Change Education Increases with Amount of Body Movement and Message Specificity" Sustainability 15, no. 7: 5814. https://doi.org/10.3390/su15075814
APA StyleQueiroz, A. C. M., Fauville, G., Abeles, A. T., Levett, A., & Bailenson, J. N. (2023). The Efficacy of Virtual Reality in Climate Change Education Increases with Amount of Body Movement and Message Specificity. Sustainability, 15(7), 5814. https://doi.org/10.3390/su15075814