An interactive point pattern analysis web application and teaching exercise

References

• Adams, N. A., & Holcomb, W. R. (1986). Analysis of the relationship between anxiety about mathematics and performance. Psychological Reports, 59, 943–948.
   PubMed Web of Science ®Google Scholar
• AlAmmary, J. (2012). Educational technology: A way to enhance student achievement at the University of Bahrain. Procedia - Social and Behavioral Sciences, 55(5), 248–258.
   Google Scholar
• Almaiah, M. A., & Jalil, M. A. (2014). Investigating students’ perceptions on mobile learning services. International Journal of Interactive Mobile Technologies, 8(4), 31–36.
   Google Scholar
• Baddeley, A., & Turner, R. (2005). spatstat: An R package for analyzing spatial point patterns. Journal of Statistical Software, 12(6), 1–42.
   Web of Science ®Google Scholar
• Bailey, T. C., & Gatrell, A. C. (1995). Interactive spatial data analysis. Harlow, UK: Longman.
   Google Scholar
• Baker, T. R., Battersby, S., Bednarz, S. W., Bodzin, A. M., Kolvoord, B., Moore, S., … Uttal, D. (2015). A research agenda for geospatial technologies and learning. Journal of Geography, 114(3), 118–130.
   Web of Science ®Google Scholar
• Baloğlu, M., Deniz, M. E., & Kesici, Ş. (2011). A descriptive study of individual and cross-cultural differences in statistics. Learning and Individual Differences, 21(4), 387–391.
   Web of Science ®Google Scholar
• Brunsdon, C., & Chen, H. (2014). GISTools: Some further GIS capabilities for R. (R package version 0.7-4.). Retrieved from https://cran.r-project.org/web/packages/GISTools/index.html
   Google Scholar
• Brunsdon, C., & Comber, L. (2015). An introduction to R for spatial analysis and mapping. London, U.K.: Sage Publications.
   Google Scholar
• Burt, J. E., Barber, G. M., & Rigby, D. L. (2009). Elementary statistics for geographers (3rd ed.). New York, NY: Guilford Press.
   Google Scholar
• Carrera, C. C., Saorín, J. L., & Medler, S. H. (2018). Pokémon GO and improvement in spatial orientation skills. Journal of Geography. Advance online publication. doi: 10.1080/00221341.2018.1470663.
   Web of Science ®Google Scholar
• Chang, W., Cheng, J., Allaire, J., Xie, Y., & McPherson, J. (2018). Shiny: Web application framework for R. (R package version 1.1.0.). Retrieved from https://cran.r-project.org/web/packages/GISTools/index.html
   Google Scholar
• Chew, P. K. H., & Dillon, D. B. (2014). Statistics anxiety update: Refining the construct and recommendations for a new research agenda. Perspectives on Psychological Science, 9(2), 196–208.
   Web of Science ®Google Scholar
• Clark, P. J., & Evans, F. C. (1954). Distance to nearest neighbor as a measure of spatial relationships in populations. Ecology, 35(4), 445–453.
   Web of Science ®Google Scholar
• Clements, F. E. (1904). The development and structure of vegetation. Lincoln, NE: The Woodriff-Collins Printing Company.
   Google Scholar
• Clements, F. E. (1905). Research methods in ecology. Lincoln, NE: The University Publishing Company.
   Google Scholar
• Clements, F. E. (1907). Plant physiology and ecology. New York, NY: Henry and Holt Company.
   Google Scholar
• Collins, L. (2018). The impact of paper versus digital map technology on students’ spatial thinking skill acquisition. Journal of Geography, 117(4), 137–152.
   Web of Science ®Google Scholar
• Core Team, R. (2018). R: A language and environment for statistical computing (version 3.5.0). Vienna, AT: R Foundation for Statistical Computing.
   Google Scholar
• Curtis, J., & McIntosh, R. (1950). The interrelations of certain analytic and synthetic phytosociological characters. Ecology, 31(3), 434–455.
   Web of Science ®Google Scholar
• DiBiase, D., DeMers, M., Johnson, A., Kemp, K., Luck, A. T., Plewe, B., & Wentz, E. (2006). Geographic information science and technology body of knowledge. Washington, D.C.: Association of American Geographers.
   Google Scholar
• Dicheva, D., Dichev, C., Agre, G., & Angelova, G. (2015). Gamification in education: A systematic mapping study. Educational Science and Technology, 18(3), 75–88.
   Google Scholar
• Dodd, M. (2011). Where are my quadrats? Positional accuracy in fieldwork. Methods in Ecology and Evolution, 2(6), 576–584.
   Web of Science ®Google Scholar
• Fiksl, M., Flogie, A., & Aberšek, B. (2017). Innovative teaching/learning methods to improve science, technology, and engineering classroom climate and interest. Journal of Baltic Science Education, 16(6), 1009–1019.
   Web of Science ®Google Scholar
• Fortin, M., Dale, M. R. T., & Ver Hoef, J. M. (2016). Spatial analysis in ecology. In N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri, & J. L. Teugels (Eds.), Wiley statsRef: Statistics reference online. Wiley. Retrieved from https://onlinelibrary.wiley.com/browse/book/10.1002/9781118445112/topic?ConceptID=13439&seriesKey=mrwseries&tagCode= 
   Google Scholar
• Fox, J., & Leanage, A. (2016). R and the journal of statistical software. Journal of Statistical Software, 73(2), 1–13.
   Web of Science ®Google Scholar
• Freeman, M. (2016). Central limit theorem. Retrieved from http://mfviz.com/central-limit/
   Google Scholar
• Gonser, R. A., Jensen, R., & Wolf, S. E. (2009). The spatial ecology of deer-vehicle collisions. Applied Geography, 29(4), 527–532.
   Web of Science ®Google Scholar
• Goodchild, M. F., & Janelle, D. G. (2010). Toward critical spatial thinking in the social sciences and humanities. GeoJournal, 75(1), 3–13.
   PubMedGoogle Scholar
• Gould, R. (2010). Statistics and the modern student. International Statistical Review, 78(2), 297–315.
   Web of Science ®Google Scholar
• Griffith, D. A. (1987). Teaching spatial autocorrelation by simulation. Journal of Geography in Higher Education, 11(2), 143–153.
   Web of Science ®Google Scholar
• Hanna, D., & Dempster, M. (2009). The effect of statistics anxiety on students’ predicted and actual test scores. The Irish Journal of Psychology, 30(3–4), 201–209.
   Google Scholar
• Heffron, S. G., & Downs, R. M. (2012). Geography for life: National geography standards (2nd ed.). Washington, DC: National Council for Geographic Education.
   Google Scholar
• Hung, K., Kalantari, M., & Rajabifard, A. (2016). Methods for assessing the credibility of volunteered geographic information in flood response: A case study in Brisbane, Australia. Applied Geography, 68, 37–47.
   Web of Science ®Google Scholar
• Kapp, K. (2012). The gamification of learning and instruction: Game-based methods and strategies for training and education. San Francisco, CA: Pfeiffer.
   Google Scholar
• Lane, D. M. (2006). Simulations/demonstrations. Rice Virtual Lab in Statistics. Retrieved from: http://onlinestatbook.com/stat_sim/index.html
   Google Scholar
• Lesser, L. M., Wall, A. A., Carver, R. H., Pearl, D. K., Martin, N., Kuiper, S., … Weber, J. J., III. (2013). Using fun in the statistics classroom: An exploratory study of college instructors’ hesitations and motivations. Journal of Statistics Education, 21(1), 1–33.
   Google Scholar
• Li, F., & Zhang, L. (2007). Comparison of point pattern analysis methods for classifying the spatial distributions of spruce-fir stands in the north-east USA. Forestry: An International Journal of Forest Research, 80(3), 337–349.
   Google Scholar
• Libes, D., & Long, A. (n.d.). Spatial autocorrelation game. Retrieved from: http://ceadserv1.nku.edu/longa//cgi-bin/cgi-tcl-examples/generic/SA/SA.cgi
   Google Scholar
• Lunn, J., & Keen, J. (2018a). Disciplinary data dashboard: Geographers by gender. Washington, DC: American Association of Geographers.
   Google Scholar
• Lunn, J., & Keen, J. (2018b). Disciplinary data dashboard: Geographers by race and ethnicity. Washington, DC: American Association of Geographers.
   Google Scholar
• McGrew, J. C., Jr., Lembo, A. J., Jr, & Monroe, C. B. (2014). An introduction to statistical problem solving in geography (3rd ed.). Long Grove, IL: Waveland Press.
   Google Scholar
• National Research Council. (2006). Learning to think spatially: The incorporation of geographic information science across the K-12 curriculum. Washington, D.C.: The National Academies Press.
   Google Scholar
• Onwuegbuzie, A., & Wilson, C. B. (2003). Statistics anxiety: nature, etiology, antecedents, effects, and treatments - a comprehensive review of the literature. Teaching in Higher Education, 8(2), 195–209.
   Google Scholar
• Onwuegbuzie, A. J. (1999). Statistics anxiety among African American graduate students: An affective filter? Journal of Black Psychology, 25(2), 189–209.
   Google Scholar
• Pound, R., & Clements, F. E. (1898). A method of determining the abundance of secondary species. Minnesota Botany Studies, 2, 19–24.
   Google Scholar
• Pound, R., & Clements, F. E. (1900). Phytogeography of Nebraska (2nd ed.). Lincoln, NE: Jacob North & Co.
   Google Scholar
• Rogerson, P. (2001). Statistical methods for geography: A student’s guide. London, UK: Sage Publications.
   Google Scholar
• Rogerson, P. (2015). Statistical methods for geography: A student’s guide (4th ed.). London, UK: Sage Publications.
   Google Scholar
• Salinas, M. F., Kane-Johnson, S. E., & Vasil-Miller, M. A. (2008). Long-term learning, achievement tests, and learner centered instruction. Journal of the Scholarship of Teaching and Learning, 8(3), 20–28.
   Google Scholar
• Sanjerehei, M. M. (2001). Determination of an appropriate quadrat size and shape for detecting association between plant species. Ecological Modelling, 222(10), 1790–1792.
   Google Scholar
• Shraim, K., & Crompton, H. (2015). Perceptions of using smart mobile devices in higher education teaching: A case study from Palestine. Contemporary Educational Technology, 6(4), 301–318.
   Google Scholar
• Sinton, D. S. (2011). Spatial thinking. In J. Stoltman (Ed.), 21st century geography: A reference handbook (pp. 733–744). Thousand Oaks, CA: Sage Publications.
   Google Scholar
• Sung, Y., Chang, K., & Liu, T. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers and Education, 94, 252–275.
   Web of Science ®Google Scholar
• Thompson, J., Licklider, B., & Jungst, S. (2003). Learner-centered teaching: Postsecondary strategies that promote “thinking like a professional”. Theory Into Practice, 42(2), 133–141.
   Web of Science ®Google Scholar
• Wai, J., Lubinkski, D., & Benbow, C. P. (2009). Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its importance. Journal of Educational Psychology, 101(4), 817–835.
   Web of Science ®Google Scholar
• Weaver, J. E. (1918). The quadrat method in teaching ecology. The Plant World, 21(11), 267–283.
   Google Scholar
• Yee, S., & Chu, T. (n.d.). R2d3: A visual introduction to machine learning. Retrieved from: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/
   Google Scholar