Supporting the M in STEM Using Online Maths Support Modules
Recently, a range of mathematics support centres and online approaches have emerged in order to address the well-recognised limitations in the mathematical skills of STEM undergraduates (Jackson & Johnson, 2013). Whilst these approaches are often stand-alone without a discipline-specific context, studies have shown that students reported a positive impact of mathematics support on retention, confidence, performance and ability to cope with the various mathematical demands of their courses (Hillock, Jennings, Roberts, & Scharaschkin, 2013; Ní Fhloinn, Fitzmaurice, Mac an Bhaird, & O’Sullivan, 2014). We have developed and implemented a purely online, in-context mathematical support environment, placed in a chemistry and biochemistry context, with 24-h access, termed the Maths Skills Site (MSS), for STEM higher education students undertaking first-year science subjects (Johnston, Watters, Brown, & Loughlin, 2016; Loughlin, Johnston, Watters, Brown, & Harman, 2015). This chapter will review the development of current online learning support scenarios for mathematics in STEM and provide two case study analyses (first-year courses in chemistry and biochemistry), for the outcomes from two years of implementation. The findings from the case studies cover student perceptions, analysis of patterns of student usage of the MSS by mathematical topics and usage over time. Improvements were observed in student achievement of grades of five (credit), upon student usage of the MSS. Finally, we critique this approach to online active learning and identify future directions.
KeywordsThreshold mathematical skills Online learning support Science undergraduate students Chemistry Biochemistry
The authors would like to thank the support of the David Green and David Harman for their invaluable assistance with the development of the Maths Skills Site. This work was supported by a University Learning and Teaching Grant.
- Anderton, R., Hine, G., & Joyce, C. (2017). Secondary school mathematics and science matters: Academic performance for secondary students transitioning into university allied health and science courses. International Journal of Innovation in Science and Mathematics Education, 25(1), 34–47.Google Scholar
- Armstrong, S., Brown, S., & Thompson, G. (Eds.). (2013). Motivating students. Oxford and New York: Routledge.Google Scholar
- Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M., & Abrami, P. C. (2014). A meta-analysis of blended learning and technology use in higher education: From the general to the applied. Journal of Computing in Higher Education, 26(1), 87–122. https://doi.org/10.1007/s12528-013-9077-3.CrossRefGoogle Scholar
- Bradforth, S. E., Miller, E. R., Dichtel, W. R., Leibovich, A. K., Feig, A. L., Martin, D., … & Smith, T. L. (2015). University learning: Improve undergraduate science education. Nature, 523(7560), 282-285.Google Scholar
- Chen, Y., Johri, A., & Rangwala, H. (2018). Running out of STEM: A comparative study across STEM majors of college students at-risk of dropping out early. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 270–279). ACM. Retrieved July 31, 2018, from https://dl.acm.org/citation.cfm?id=3170410.
- Cho, M. H., & Heron, M. L. (2015). Self-regulated learning: The role of motivation, emotion, and use of learning strategies in students’ learning experiences in a self-paced online mathematics course. Distance Education, 36(1), 80–99. https://doi.org/10.1080/01587919.2015.1019963.CrossRefGoogle Scholar
- Crisp, G., Nora, A., & Taggart, A. (2009). Student characteristics, pre-college, and environmental factors as predictors of majoring in and earning a STEM degree: An analysis of students attending a Hispanic serving institution. American Educational Research Journal, 46, 924–942. https://doi.org/10.3102/0002831209349460.CrossRefGoogle Scholar
- Donovan, W. J., & Wheland, E. R. (2009). Comparisons of success and retention in a general chemistry course before and after the adoption of a mathematics prerequisite. School Science and Mathematics, 109(7), 371–382. https://doi.org/10.1111/j.1949-8594.2009.tb17868.x.CrossRefGoogle Scholar
- Dziuban, C., Moskal, P., Johnson, C., & Evans, D. (2017). Adaptive learning: A tale of two contexts. Current Issues in Emerging eLearning, 4(1), 3.Google Scholar
- Groen, L., Coupland, M., Langtry, T., Memar, J., Moore, B., & Stanley, J. (2015). The mathematics problem and mastery learning for first-year, undergraduate STEM students. International Journal of Learning, Teaching and Educational Research, 11(1), 141–160.Google Scholar
- Hine, G. (2017). Exploring reasons why Australian senior secondary students do not enrol in higher-level mathematics courses. In A. Downton, S. Livy, & J. Hall (Eds.), Proceedings of the 40th Annual Conference of the Mathematics Education Research Group of Australasia. Melbourne, Australia (pp. 309–316). Adelaide, Australia: The Mathematics Education Research Group of Australasia Inc.Google Scholar
- Hunt, D. N., & Lawson, D. A. (1996). Trends in mathematical competency of A-level students on entry to university. Teaching Mathematics and its Applications, 15(4), 167–173. Retrieved July 30, 2018, from https://merga.net.au/Public/Publications/Annual_Conference_Proceedings/2017_MERGA_annual_conference_proceedings.aspx.
- Jackson, D. C., Johnson, E. D., & Blanksby, T. M. (2014). A practitioner’s guide to implementing cross-disciplinary links in a mathematics support program. International Journal of Innovation in Science and Mathematics Education, 22(1), 67–80.Google Scholar
- Johnston, P. R., Watters, D. J., Brown, C. L., & Loughlin, W. A. (2016). An investigation into student perceptions towards mathematics and their performance in first year chemistry: Introduction of online maths skills support. Chemistry Education Research and Practice, 17(4), 1203–1214. https://doi.org/10.1039/C6RP00175.CrossRefGoogle Scholar
- Kennedy, J. P., Lyons, T., & Quinn, F. (2014). The continuing decline of science and mathematics enrolments in Australian high schools. Teaching Science, 60(2), 34–46.Google Scholar
- Koenig, J. (2011). A survey of the mathematics landscape within bioscience undergraduate and postgraduate UK higher education (p. 22). Leeds: UK Centre for Bioscience. https://doi.org/10.11467/344.
- Loughlin, W. A., Johnston, P. R., Watters, D. J., Brown, C. L., & Harman, D. (2015). Snapshot of mathematics skills of first year science students from diverse backgrounds. International Journal of Innovation in Science and Mathematics Education, 23(1), 21–36.Google Scholar
- Matthews, K. E., Belward, S., Coady, C., Rylands, L., Simbag, V., Adam, P., & Tariq, V. (2012). The state of quantitative skills in undergraduate science education: Findings from an Australian study. Office for Learning and Teaching: Canberra. Retrieved May 13, 2016, from http://researchonline.jcu.edu.au/26400/1/QS_report_July2012.pdf.
- Mac an Bhaird, C., Fitzmaurice, O., Fhloinn, E. N., & O’Sullivan, C. (2013). Student non-engagement with mathematics learning supports. Teaching Mathematics and Its Applications, 32(4), 191–205.Google Scholar
- MacGillivray, H., & Wilson, T. (2008). Quantitative diversity: Disciplinary and cross-disciplinary mathematics and statistics support in Australian universities. Australian Learning and Teaching Council. Retrieved July 25, 2018, from http://www.olt.gov.au/resource-library?text=mathematics.
- McPhan, G., Morony, W., Pegg, J., Cooksey, R., & Lynch, T. (2008). Maths? Why not? Final report prepared for the Department of Education, Employment and Workplace Relations. Canberra (Australia). Retrieved July 25, 2018, from https://www.aamt.edu.au/content/download/33194/469618/file/MaWhNot_Published.pdf.
- Nakakoji, Y., Wilson, R., & Poladian, L. (2014). Mixed methods research on the nexus between mathematics and science. International Journal of Innovation in Science and Mathematics Education, 22(6), 61–76.Google Scholar
- Overton, T., & Johnson, L. (2016). Evidence-based practice in learning and teaching for STEM disciplines. Retrieved April 20, 2018 from, http://www.acds-tlcc.edu.au/wp-content/uploads/sites/14/2016/07/ACDS-stem-principles-WEB.pdf.
- Park, T., Woods, C. S., Hu, S., Bertrand Jones, T., & Tandberg, D. (2018). What happens to underprepared first-time-in-college students when developmental education is optional? The case of developmental math and intermediate algebra in the first semester. The Journal of Higher Education, 89(3), 318–340. https://doi.org/10.1080/00221546.2017.1390970.CrossRefGoogle Scholar
- Pohjolainen, S., Nykänen, O., Venho, J., & Kangas, J. (2018). Analysing and improving students’ mathematics skills using ICT-tools. Eurasia Journal of Mathematics, Science and Technology Education, 14(4), 1221–1227. https://doi.org/10.29333/ejmste/81869.
- Ramirez-Arellano, A., Bory-Reyes, J., Hernández-Simón, L. M. (2018). Emotions, motivation, cognitive–Metacognitive strategies, and behavior as predictors of learning performance in blended learning. Journal of Educational Computing Research, January, 1–23. https://doi.org/10.1177/0735633117753935.CrossRefGoogle Scholar
- Schoenfeld, A. H. (1992). Learning to think mathematically: Problem solving, metacognition, and sense making in mathematics. In D. Grouws (Ed.), Handbook for research on mathematics teaching and learning (Chap. 15). New York: Macmillan.Google Scholar
- Sen, S., Yilmaz, A., & Yurdagül, H. (2014). An evaluation of the pattern between students’ motivation, learning strategies and their epistemological beliefs: The mediator role of motivation. Science Education International, 25(3), 312–331.Google Scholar
- Tempelaar, D. T., Niculescu, A., Rienties, B., Gijselaers, W. H., & Giesbers, B. (2012). How achievement emotions impact students’ decisions for online learning, and what precedes those emotions. Internet and Higher Education, 15(3), 161–169. https://doi.org/10.1016/j.iheduc.2011.10.003.CrossRefGoogle Scholar
- Wilson, R., & Mack, J. (2014). Declines in high school mathematics and science participation: Evidence of students’ and future teachers’ disengagement with maths. International Journal of Innovation in Science and Mathematics Education, 22(7), 35–48.Google Scholar
- Wienk, M. (2015). Discipline Profile of the Mathematical Sciences 2015, Australian Mathematical Sciences Institute. Retrieved May 13, 2016, from http://amsi.org.au/wp-content/uploads/2015/08/discipline-profile-2015.pdf.
- Wilkes, J., & Burton, L. J. (2015). Get set for success: Applications for engineering and applied science students. International Journal of Innovation in Science and Mathematics Education, 23(1), 94–105.Google Scholar