STATISTICS ATTITUDES AFTER USING GUIDED PROJECT-BASED LEARNING AS AN ANDRAGOGICAL STRATEGY IN A GRADUATE STATISTICS COURSE

Authors

  • ADAM ELDER Southeastern Louisiana University

DOI:

https://doi.org/10.52041/serj.v22i3.436

Keywords:

Statistics education research, Graduate research, Instructional techniques, Assessment, Attitude towards statistics

Abstract

This study builds on previous studies that have examined guided project-based learning in undergraduate statistics courses to examine students’ attitudes toward statistics after participating in a graduate-level statistics course that used guided project-based learning as an andragogical technique. This phenomenological qualitative case study utilized multiple student interviews and reflections over a semester-long statistics course in a doctoral education degree program. The results showed that guided project-based learning immersed students in the quantitative inquiry process and emboldened them to read and use statistics in their academic and professional lives. It also revealed several elements of guided project-based learning that are important for instructors looking to implement this approach in their own courses.

References

Acee, T., & Weinstein, C. (2010). Effects of a value-reappraisal intervention on statistics students’ motivation and performance. Journal of Experimental Education, 78(4), 487–512. https://doi.org/10.1080/00220970903352753

American Statistical Association. (2016). Guidelines for assessment and instruction in statistics education college report 2016. http://www.amstat.org/education/gaise

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191

Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122–147. https://doi.org/10.1037/0003-066X.37.2.122

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.

Bayer, T. J. (2016). Effects of guided project-based learning activities on students’ attitudes toward statistics in an introductory statistics course. [Doctoral dissertation, Old Dominion University, Norfolk, VA] https://doi.org/10.25777/9g35-yy29

Budé, L., Imbos, T., van de Wiel, M. W. J., Broers, N. J., & Berger, M. P. F. (2009). The effect of directive tutor guidance in problem-based learning of statistics on students’ perceptions and achievement. Higher Education, 57(1), 23–36. https://doi.org/10.1007/s10734-008-9130-8

Chiesi, F., & Primi, C. (2010). Cognitive and non-cognitive factors related to students’ statistics achievement. Statistics Education Research Journal, 9(1), 6–26. https://doi.org/10.52041/serj.v9i1.385

Dempster, M., & McCorry, N. K. (2009). The role of previous experience and attitude toward statistics in statistics assessment outcomes among undergraduate psychology students. Journal of Statistics Education, 17(2). https://doi.org/10.1080/10691898.2009.11889515

Groth, R. E. (2010). Situating qualitative modes of inquiry within the discipline of statistics education research. Statistics Education Research Journal, 9(2), 7–21. https://doi.org/10.52041/serj.v9i2.372

Hays, D. G., & Singh, A. A. (2012). Qualitative inquiry in clinical and educational settings. Guilford Press.

Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266. https://doi.org/10.1023/B:EDPR.0000034022.16470.f3

Ishtiaq, M., Iqbal, N., Malik, N., Rubab, H., & Hashim, M. (2017). Project-based and case-based learning of statistics in undergraduate nursing students-Islamabad: A mixed method study. Annals of Pakistan Institute of Medical Sciences, 13(1), 61–67.

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 411(2), 75–86. https://doi.org/10.1207/s15326985ep4102_1

Knowles, M. S. (1980). The modern practice of adult education: From pedagogy to andragogy (2nd ed.). Cambridge Books.

Knowles, M. S. (1984). The adult learner: A neglected species (3rd ed.). Gulf.

Lambie, G. W., Hayes, B. G., Griffith, C., Limberg, D., & Mullen, P. R. (2014). An exploratory investigation of the research self-efficacy, interest in research, and research knowledge of Ph.D. in education students. Innovative Higher Education, 39(2), 139–153. https://doi.org/10.1007/s10755-013-9264-1

Lee, J. S., Blackwell, S., Drake, J., & Moran, K. A. (2014). Taking a leap of faith: Redefining teaching and learning in higher education through project-based learning. The Interdisciplinary Journal of Problem-based Learning, 8(2), 19–34. https://doi.org/10.7771/1541-5015.1426

Leech, N. L., & Onwuegbuzie, A. J. (2007). An array of qualitative data analysis tools: A call for data analysis triangulation. School Psychology Quarterly, 22(4), 557–584. https://doi.org/10.1037/1045-3830.22.4.557

Lehman, J. D., George, M., Buchanan, P., & Rush, M. (2006). Preparing teachers to use problem-centered, inquiry-based science: Lessons from a four-year professional development project. Interdisciplinary Journal of Problem-Based Learning, 1(1), 76–99. https://doi.org/10.7771/1541-5015.1007

Leppink, J., Broers, N. J., Imbos, T., van der Vleuten, C. P. M., & Berger, M. P. F. (2014). The effect of guidance in problem-based learning of statistics. The Journal of Experimental Education, 82(3), 391–407. https://doi.org/10.1080/00220973.2013.813365

Nadolski, R. J., Kirschner, P. A., & van Merriënboer, J. J. G. (2005). Optimizing the number of steps in learning tasks for complex skills. British Journal of Educational Psychology, 75(2), 223–237. https://doi.org/10.1348/000709904X22403

Onwuegbuzie, A. J., & Collins, K. M. T. (2007). A typology of mixed methods sampling designs in social science research. The Qualitative Report, 12(2), 281–316. https://files.eric.ed.gov/fulltext/EJ800183.pdf

Onwuegbuzie, A. J., Slate, J. R., Paterson, F. R. A., Watson, M. H., & Schwartz, R. A. (2000). Factors associated with achievement in educational research courses. Research in the Schools, 7(1), 53–65.

Onwuegbuzie, A. J., & Wilson, V. A. (2003). Statistics anxiety: Nature, etiology, antecedents, effects and treatments: A comprehensive review of the literature. Teaching in Higher Education, 8, 195–209. https://files.eric.ed.gov/fulltext/ED448202.pdf

Savery, J. (2006). Overview of problem-based learning: Definitions and distinctions. The Interdisciplinary Journal of Problem-based Learning, 1(1), 9–20. https://doi.org/10.7771/1541-5015.1002

Schau, C. (2003). Survey of attitudes toward statistics (SATS-36). www.evaluationandstatistics.com

Wild, C. J., & Pfannkuch, M. (1999). Statistical thinking in empirical enquiry. International Statistical Review, 67(3), 223–265.

Whitaker, D., Unfried, A., & Bond, M. E. (2022). Challenges associated with measuring attitudes using the SATS family of instruments. Statistics Education Research Journal, 21(1), 1–23. https://doi.org/10.52041/serj.v21i1.88

Wood, R., & Bandura, A. (1989). Impact of conceptions of ability on self-regulatory mechanisms and complex decision making. Journal of Personality and Social Psychology, 56(3), 407–415. http://www.uky.edu/~eushe2/Bandura/Bandura1989JPSP.pdf

Xu, C., & Schau, C. (2019). Exploring method effects in the six-factor structure of the Survey of Attitudes Toward Statistics (SATS-36). Statistics Education Research Journal, 18(2), 39–53. https://doi.org/10.52041/serj.v18i2.139

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Published

2023-12-01

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Section

Regular Articles