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Original Articles

Statistical Literacy as a Function of Online Versus Hybrid Course Delivery Format for an Introductory Graduate Statistics Course

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References

  • Allen, I. E. and Seaman, J. (2015), Grade Level: Tracking Online Learning in the United States, Wellesley, MA: Babson Survey Research Group and Quahog Research Group, LLC.
  • Anastasi, J. S. (2007), “Methods and Techniques: Full-Semester and Abbreviated Summer Courses–An Evaluation of Student Performance,” Teaching of Psychology, 1, 19–22.
  • Artino, A. R. and Stephens, J. M. (2009), “Academic Motivation and Self-Regulation: A Comparative Analysis of Undergraduate and Graduate Students Learning Online,” Internet and Higher Education, 12, 146–151.
  • Austin, A. M. and Gustafson, L. (2006), “Impact of Course Length on Student Learning,” Journal of Economics and Finance Education, 1, 5, 26–37.
  • Bailey, K. D., and Morais, D. B. (2005), “Exploring the Use of Blended Learning in Tourism Education,” Journal of Teaching in Travel and Tourism, 4, 4, 23–36.
  • Barcikowski, R. S. (1981), “Statistical Power with Group Mean as the Unit of Analysis,” Journal of Educational Statistics, 3, 6, 267–285.
  • Billings, D. M., Skiba, D. J., and Connors, H. R. (2005), “Best Practices in Web-based Courses: Generational Differences Across Undergraduate and Graduate Nursing Students,” Journal of Professional Nursing, 2, 21, 126–133.
  • Bowen, W. G., Chingos, M. M., Lack, K. A., and Nygren, T. I. (2014), “Interactive Learning Online at Public Universities: Evidence from a Six-Campus Randomized Trial,” Journal of Policy Analysis and Management, 33, 94–111.
  • Brown, D. G. (2001), “Hybrid Courses are Best,” Syllabus Magazine, 15, 22.
  • Burbules, N. C. and Callister, T. A. (2000), “Universities in Transition: The Promise and the Challenge of New Technologies,” Teachers College Record, 102, 271–293.
  • Carnevale, D. (2002), “Online Students don't Fare as Well as Classroom Counterparts, Study Finds,” The Chronicle of Higher Education, 48, 38.
  • Chametzky, B. (2013), Offsetting the Affective Filter: A Classic Grounded Theory Study of Post-secondary Online Foreign Language Learners. Prescott Valley, AZ: Northcentral University.
  • Chance, B. (2002), “Components of Statistical Thinking and Implications for Instruction and Assessment,” Journal of Statistics Education, 10.
  • Daniel, E. L. (2000), “A Review of Time-Shortened Courses Across Disciplines,” College Student Journal, 34, 298–306.
  • delMas, R. C. (2002), “Statistical Literacy, Reasoning, and Learning: A Commentary,” Journal of Statistics Education, 10.
  • delMas, R., Garfield, J., Ooms, A., and Chance, B. (2006), “Assessing Students' Conceptual Understanding After a First Course in Statistics,” Paper presented at American Educational Research Association Annual Conference, April 9 at San Francisco, CA.
  • DelMas, R., Garfield, J., Ooms, A., and Chance, B. (2007), “Assessing Students' Conceptual Understanding after a First Course in Statistics,” SERJ, 2, 28–58.
  • Dereshiwsky, M. I. (1998), “Go Figure: The Surprising Successes of Teaching Statistics Courses via the Internet,” in Proceedings of the Teaching in the Community Colleges Online Conference, Honolulu, HI.
  • Dutton, J. and Dutton, M. (2005), “Characteristics and Performance of Students in an Online Section of Business Statistics,” Journal of Statistics Education, 3.
  • Dutton, J., Dutton, M., and Perry, J. (2001), “Do Online Students Perform as well as Lecture Students?,” Journal of Engineering Education, 90, 131–136.
  • Dziuban, C. D. (2016), “Assessing Outcomes in Online and Blended Learning Research,” in Conducting Research in Online and Blended Learning Environments, eds. C. D. Dziuban, A. G. Picciano, C. R. Graham, and P. D. Moskal, New York, NY: Routledge Taylor and Francis, pp. 158–172.
  • Ferguson, J. M. and DeFelice, A. E. (2010), “Length of Online Course and Student Satisfaction, Perceived Learning, and Academic Performance,” International Review of Research in Open and Distance Learning, 2, 73–84.
  • Gal, I. (2002), “Adults' Statistical Literacy: Meanings, Components, Responsibilities,” International Statistical Review, 70, 1–25.
  • Garfield, J. (2002), “The Challenge of Developing Statistical Reasoning,” Journal of Statistics Education, 10.
  • Graham, J. W. (2009), “Missing Data Analysis: Making it Work in the Real World,” Annual Review of Psychology, 60, 549–576.
  • Green, J. A. and Azevedo, R. (2007), “A Theoretical Review of Winne and Hadwin's Model of Self-Regulated Learning: New Perspectives and Directions,” Review of Educational Research, 77, 334–372.
  • Haughton, J. and Kelly, A. (2015), “Student Performance in an Introductory Business Statistics Course: Does Delivery Mode Matter?,” Journal of Education for Business, 90, 31–43.
  • James, S., Swan, K., and Daston, C. (2016), “Retention, Progression and the Taking of Online Classes,” Online Learning, 2, 75–96.
  • Kakish, K., Pollacia, L., Heinz, A., Sinclair, J. L., and Thomas, A. (2012), “Analysis of the Effectiveness of Traditional Versus Hybrid Student Performance of an Elementary Statistics Course,” International Journal for the Scholarship of Teaching and Learning, 6, 1–9.
  • Keefe, T. J. (2003), “Using Technology to Enhance a Course: The Importance of Interaction,” EDUCAUSE Quarterly, 26, 24–34.
  • Kwak, D. W., Menezes, F. M., and Sherwood, C. (2015), “Assessing the Impact of Blended Learning on Student Performance,” Economic Record, 91, 91–106. doi: 10.1111/1475-4932.12155.
  • Lee, N., and Horsfall, B. (2010), “Accelerated Learning: A Study of Faculty and Student Experiences,” Innovative Higher Education, 35, 191–202.
  • Margulieux, L. E., Bujak, K. R., McCracken, W. M., and Majerich, D. M. (2014), “Flipped, Blended, Flipped, and Inverted: Defining Terms in a Two Dimensional Taxonomy,” Paper presented at 12th Annual Hawaii International Conference on Education, January 5–9, at Honolulu, HI.
  • Means, B., Toyama, Y., Murphy, R., Bakia, M., and Jones, K. (2010), Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies, Washington, DC: U.S. Department of Education.
  • Mensch, S. (2013), “The Impact of Course Length on Online Numeric-Based Course Grades,” Contemporary Issues in Education Research, 6, 4.
  • Mortenson, T. G. (2005), State Tax Fund Appropriations for Higher Education: FY1961 to FY2005. Oskaloosa, LA: Postsecondary Education Opportunity.
  • Nunnally, J. C. and Berstein, I. H. (1994), Psychometric Theory (3rd ed.), New York: McGraw-Hill.
  • Oblender, T. E. (2002), “A Hybrid Course Model: One Solution to the High Online Drop-out Rate,” Learning & Leading with Technology, 6, 42–46.
  • Onwuegbuzie, A. J. (2001), “Critical Thinking Skills: A Comparison of Doctoral- and Master's-Level Students,” College Student Journal, 3, 477–481.
  • Parker, R. (2009), “A Learning Community Approach to Doctoral Education in the Social Sciences,” Teaching in Higher Education, 1, 14, 43–54.
  • Picciano, A. G. (2015), “Research in Online and Blended Learning: New Challenges, New Opportunities,” in Conducting Research in Online and Blended Learning Environments, eds. C. D. Dziuban, A. G. Picciano, C. R. Graham, and P. D. Moskal, New York: Routledge Taylor & Francis, pp. 1–11.
  • Postman, N. (2011), Technopoly: The Surrender of Culture to Technology, New York: Random House Digital, Inc.
  • Raftery, A. E. (1995), “Bayesian Model Selection in Social Research,” Sociological Methodology, 25, 111–163.
  • Rumsey, D. J. (2002), “Statistical Literacy as a Goal for Introductory Statistics Courses,” Journal of Statistics Education, 10.
  • Russell, T. L. (2001). The No Significant Difference Phenomenon (5th ed.), Chapel Hill, NC: Office of Instructional Telecommunication, North Carolina State University Press.
  • Sami, F. (2011), “Course Format Effects on Learning Outcomes in an Introductory Statistics Course,” MathAMATYC Educator, 2, 48–51.
  • Scherrer, C. R. (2011), “Comparison of an Introductory Level Undergraduate Statistics Course Taught with Traditional, Hybrid, and Online Delivery Methods,” INFORMS Transactions on Education, 11, 106–110.
  • Scherrer, C. R. (2015), “Comparison of an Introductory Level Undergraduate Statistics Course Taught with Traditional, Hybrid, and Online Delivery Methods,” INFORMS Transactions on Education, 11, 106–110.
  • Scott, P. A. (1996), “Attributes of High-Quality Intensive Course Learning Experiences: Student Voices and Experiences,” College Student Journal, 30, 69–77.
  • Seamon, M. (2004), “Short- and Long-Term Differences in Instructional Effectiveness Between Intensive and Semester-Length Courses,” Teachers College Record, 4, 106, 852–874. doi: 10.1111/j.1467-9620.2004.00360.x.
  • Shaw, M., Chametzky, B., Burrus, S. W., and Walters, K. J. (2013), “An Evaluation of Student Outcomes by Course Duration in Online Higher Education,” Online Journal of Distance Learning Administration[ online]. Available at http://www.westga.edu/∼distance/ojdla/winter164/shaw_chametzky_burrus_walters164.
  • Snijders, T. A. B. and Berkhof, J. (2008), “Diagnostic Checks for Multilevel Models,” in Handbook of Multilevel Analysis, eds. J. de Leeuw, and E. Meijer, New York: Springer, pp. 141–175.
  • Star, S. L. and Griesemer, J. R. (1989), “Institutional Ecology, Translations and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertegrate Zoology, 1907–39,” Social Studies of Science, 3, 387–420.
  • Twigg, C. A. (2013), “Improving Learning and Reducing Costs: Outcomes from Changing the Equation,” Change: The Magazine of Higher Learning, 45, 6014.
  • Utts, J., Sommer, B., Acredolo, C., Maher, M. W., and Matthews, H. R. (2003), “A Study Comparing Traditional and Hybrid Internet-Based Instruction in Introductory Statistics Classes,” Journal of Statistics Education, 3.
  • Ward, B. (2004), “The Best of Both Worlds: A Hybrid Statistics Course,” Journal of Statistics Education, 3.
  • Watson, J. and Callingham, R. (2003), “Statistical Literacy: A Complex Hierarchical Construct,” Statistics Education Research Journal, 2, 3–46.
  • Watson, J. M. (2011), “Foundations for Improving Statistical Literacy,” Statistical Journal of the IAOS, 27, 197–204. doi: 10.3233/SJI20110728.
  • Wisker, G., Robinson, G., and Shacham, M. (2007), “Postgraduate Research Success: Communities of Practice Involving Cohorts, Guardian Supervisors, and Online Communities,” Innovations in Education and Teaching International, 44, 301–320.
  • Young, J. R. (2002), “‘Hybrid’ Teaching Seeks to End the Divide Between Traditional and Online Instruction,” The Chronicle of Higher Education, 48, A33–A34.