logo logo International Journal of Educational Methodology

IJEM is a leading, peer-reviewed, open access, research journal that provides an online forum for studies in education, by and for scholars and practitioners, worldwide.

Subscribe to

Receive Email Alerts

for special events, calls for papers, and professional development opportunities.

Subscribe

Publisher (HQ)

RHAPSODE LTD
Eurasian Society of Educational Research
College House, 2nd Floor 17 King Edwards Road, Ruislip, London, UK. HA4 7AE
RHAPSODE LTD
Headquarters
College House, 2nd Floor 17 King Edwards Road, Ruislip, London, UK. HA4 7AE
active learning math finance adaptive learning traditional learning inclusive learning

An Experiment in Active Learning: The Effects of Teams

Jeffrey Ludwig

In modern times, the importance of education cannot be overstated. Beyond the acquisition of knowledge, perhaps the most important aim of education ma.

I

In modern times, the importance of education cannot be overstated. Beyond the acquisition of knowledge, perhaps the most important aim of education may be the development of character in individuals, including vitality, courage, sensitiveness, and intelligence, from which our society may experience increased prosperity, peace, and freedom. In this paper we address the daunting challenge of achieving successful, widespread, and inclusive university education. How do we enliven and engage the students in our classrooms? How can we help each and every student in the class self-actualize and reach the highest potential for learning? Active learning is one well-established and potent solution for accelerating the accumulation of knowledge. In this paper, an experiment in active learning utilizing team-based adaptive online quizzes in an introductory math finance course involving 378 undergraduate students over two years is conducted to explore the potency of this active learning methodology compared to a control group with traditional teaching. We find active learning unambiguously improves knowledge accumulation in the individual students, while simultaneously bolstering inclusive excellence across all students in the class, as measured by a relevant and meaningful quantitative metric. The paper concludes with a discussion comparing the quality of active vs. traditional teaching methods and offers interpretations of the quantitative results. The results of this paper support the widely accepted theme in the literature that active learning has a positive effect on student performance in STEM (Science, Technology, Engineering, and Math) courses.

Keywords: Active learning, math finance, adaptive learning, traditional learning, inclusive learning.

cloud_download PDF
Cite
Article Metrics
Views
357
Download
623
Citations
Crossref
2

Scopus

References

Ambrose, S. A., Bridges, M. W., DiPietero, M., Lovett, M. C., & Norman, M. K. (2010). How learning works: Seven research-based principles for smart teaching. Jossey-Bass https://doi.org/10. 7899/JCE-12-022

Anthony, G. (1996). Active learning in a constructivist framework. Educational Studies in Mathematics, 31(4), 349-369. https://doi.org/10.1007/BF00369153

Arbelaitz, O., Marti’n, J. I., & Muguerza, J. (2015). Analysis of introducing active learning methodologies in a basic computer architecture course. IEEE Transactions on Education, 58(2), 110-116. https://doi.org/10.1109/TE.2014.2332448

Armbruster, P., Patel, M., Johnson, E., & Weiss, M. (2017). Active learning and student-centered pedagogy improve student attitudes and performance in introductory biology. Life Sciences Education, 8(3), 203-213. https://doi.org/10.1187/cbe.09-03-0025

Bjalkebring, P. (2019). Math anxiety at the university: What forms of teaching and learning statistics in higher education can help students with math anxiety? Frontiers in Education. 4(30). https://doi.org/10.3389/feduc.2019.00030

Bonwell, C., & Eison, J. (1991). Active learning: Creating excitement in the classroom (AEHE-ERIC higher education report, No. 1). Jossey-Boss.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge.

Crimmins, M. T., & Midkiff, B. (2017). High structure active learning pedagogy for the teaching of organic chemistry: Assessing the impact on academic outcomes. Journal of Chemical Education, 94(4), 429-438. https://doi.org/10.1021/acs.jchemed.6b00663

Eddy, S., & Hogan, K. A. (2014). Getting under the hood: How and for whom does increasing course structure work? Life Sciences Education, 13(3), 453-468. https://doi.org/10.1187/cbe.14-03-0050

Freeman, S., Eddy, S., McDonough, M., Smith, M., Okoroafor, N., Jordt, H., & Wenderoth, P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences of the United States of America, 111(23), 8410-8415. https://doi.org/10.1073/pnas.1319030111

Haak, D. C., HilleRisLambers, J., Pitre, E., & Freeman, S. (2011). Increased structure and active learning reduce the achievement gap in introductory biology. Science, 332(6034), 1213-1216. https://doi.org/10.1126/science.1204820

Hart, P. D. (2007). Top ten things employers look for in new college graduates. Association of American Colleges and Universities. https://cut.ly/dD7ughN

Jaschik, S. (2015). Well-prepared in their own eyes. Inside Higher Ed. https://cut.ly/JEV6WLC

Kogan, M., & Laursen, S. L. (2014). assessing long-term effects of inquiry-based learning: A case study from college mathematics. Innovative Higher Education, 39, 183–199. https://doi.org/10.1007/s10755-013-9269-9

Lahdenpera, J., & Nieminen, J. H. (2020). How does a mathematician fit in? A mixed-methods analysis of university students’ sense of belonging in mathematics. International Journal of Research in Undergraduate Mathematics Education, 6, 475-494.

Ludwig, J. (2021). A new mathematical metric for inclusive excellence in teaching applied before and during COVID-19. International Journal of Education, 13(2). Advanced Online Publication.

Lugosi, E., & Uribe, G. (2019). Active learning strategies with positive effects on students’ achievements in undergraduate mathematics education. International Journal of Mathematical Education in Science and Technology. Advanced Online Publication. https://doi.org/10.1080/0020739X.2020.1773555

Mirata, V., Hirt, F., Bergamin, P., & van der Westhuizen, C. (2020). Challenges and contexts in establishing adaptive learning in higher education: findings from a Delphi study. International Journal of Educational Technology in Higher Education, 17(32), 1-25. https://doi.org/10.1186/s41239-020-00209-y

Oishi, M., Svihla, V., & Law, V. (2017, June 25-28). Improved learning through collaborative, scenario-based quizzes in an undergraduate control theory course [Paper Presentation]. 2017 ASEE Annual Conference & Exposition, Columbus, Ohio, USA. 

O’Sullivan, D. W., & Cooper, C. L. (2003). Evaluating active learning: A new initiative for a general chemistry curriculum. Journal of College Science Teaching, 32(7), 448-452.

Peng, H., Ma, S., & Spector, J. M. (2019). Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6, 1-14. https://doi.org/10.1186/s40561-019-0089-y

Roediger, H. L., & Karpicke, J. (2006a). The power of testing memory: Basic research and implications for educational practice. Perspectives on Psychological Science, 1(3), 181-210. https://doi.org/10.1111/j.1745-6916.2006.00012.x

Roediger, H. L., & Karpicke, J. (2006b). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249-255. https://doi.org/10.1111/j.1467-9280.2006.01693.x

Ruiz-Primo, M. A., Briggs, D., Iverson, H., Talbot, R., & Shepard, L. A. (2011). Impact of undergraduate science course innovations on learning. Science, 331(6022), 1269-1270. https://doi.org/10.1126/science.1198976

Sawilowsky, S. (2009). New effect size rules of thumb. Journal of Modern Applied Statistical Methods, 8(2), 597-599. https://doi.org/10.22237/jmasm/1257035100

Sisk, R. J. (2011). Team-based learning: Systematic research review. Journal of Nursing Education, 50(12), 665-669. https://doi.org/10.3928/01484834-20111017-01

Springer, L., Stanne, M. E., & Donovan, S. S. (1999). Effects of small-group learning on undergraduates in science, mathematics, engineering, and technology: A meta-analysis. Review of Educational Research, 69(1), 21-51. https://doi.org/10.3102/00346543069001021

Theobald, E. J., Hill, M. J., Tran, E., Agrawal, S., Arroyo, E. N., Behling, S., Chambwe, N., Cintrón, D. L., Cooper, J. D., Dunster, G., Grummer, J. A., Hennessey, K., Hsiao, J., Iranon, N., Jones, L., Jordt, H., Keller, M., Lacey, M. E., Littlefield, C. E., & Lowe, A. (2020). Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math. Proceedings of the National Academy of Sciences of the United States of America, 117(12), 6476-6483. https://doi.org/10.1073/pnas.1916903117

Urton, J. (2020, March 9). Underrepresented college students benefit more from ‘active learning’ techniques in STEM courses. University of Washington News. https://cut.ly/hupo81G

Volpe, P. (1984). The shame of science education. American Zoologist, 24(2), 433-441.

Weiner, B. (1990). History of motivational research in education. Journal of Educational Psychology, 82(4), 616–622. https://doi.org/10.1037/0022-0663.82.4.616

Zhao, C., & Kuh, G. D. (2004). Adding value: Learning communities and student engagement. Research in Higher Education, 45, 115-128.

...