IDENTIFYING STUDENTS’ WAYS OF LEARNING OF MATHEMATICS AT UNIVERSITY LEVEL
DOI:
https://doi.org/10.17770/sie2019vol1.3980Keywords:
learning at university level, mathematical knowledge, time, transitionAbstract
The Mathematics study course is one of the core subjects in study programs of Technical Universities. To acquire this course successfully it is necessary to have mathematics background of sufficiently high quality. The authors of this paper recognize the difficulties first year students face due of their insufficient mathematical knowledge.
Today, universities emphasize independent study work by students and allocate special time slots for this. To be successful, students need to plan their study time, use appropriate learning methods, and have motivation. Because of the significance of students’ individual work, a questionnaire was developed to research how students plan their time and activities for learning mathematics.
The authors selected three focus groups of first year students at Riga Technical University (RTU), Latvian Maritime Academy (LMA), and University of Latvia (UL) to collect the data. The comparative analysis of data showed how students use the time slots allocated by institutions. The UL and RTU students on average do not fulfil this time completely, while the LMA students spend more time for learning mathematics. Students highly value individual consultations with teachers; they actively communicate with study mates to solve homework assignments; and students use information technologies in the study process.
References
Accascina, G., Mastrogiovanni, M.. & Rogora, E. (2019). Bridging the gap between high school and university mathematics. Retrieved from:
Anderson, L. W., Krathwohl, D. R., & Bloom, B. S. (2000) Taxonomy for learning, teaching and assessing: A revision of Bloom’s Taxonomy of educational objectives, Complete Edition. London: Longman
Artigue, M. (2016). Mathematics Education Research at University Level: Achievements and Challenges. First conference of International Network for Didactic Research in University Mathematics, Mar 2016, Montpellier, France,
Barzel, B., Leuders, T., Prediger, S.,& Husmann, S. (2013). Designing Tasks for Engaging Students in Active Knowledge Organization. In Watson, Minoru, Ainley, Frant, Doorman, Kieran, Leung, Margolinas, Sullivan, Thompson, Yang (Ed.) ICMI Study 22 on Task Design – Proceedings of Study Conference. Oxford, 285-294. Retrieved from:
https://pdfs.semanticscholar.org/e644/b9f56811ff6d757df2e37ed77c8847113452.pdf
Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. New York: David McKay Company
Charlton, B.G. (2006). Lectures are such an effective teaching method because they exploit evolved human psychology to improve learning. Medical Hypotheses, 67(6), 1261-1265.
Grevholm, B. (2005). Concept maps as a tool in research on student teachers’ learning in mathematics and mathematics education. In Bergsten & Grevholm (Ed.) Proceedings of Norma 01. Third Nordic Conference on Mathematics Education, Kristianstad, Sweden, June 8 – 12, 2001 (127 – 139), Linkoping
Harris, D., Black, L., Hernandez-Martinez, P., Pepin, B., & Williams, J. (2014). Mathematics and its value for engineering students: what are the implications for teaching? International Journal of Mathematical Education in Science and Technology, 46 (3), 321-336. DOI:org/10.1080/0020739X.2014.979893
Heick, T. (2019). A Visual Summary: 32 Learning Theories Every Teacher Should Know. Retrieved from: https://www.teachthought.com/learning/a-visual-summary-the-most-important-learning-theories/
Hoyles, C; Newman, K; & Noss, R; (2001). Changing patterns of transition from school to university mathematics. International Journal of Mathematical Education in Science and Technology, 32(6), 829-845, DOI:org/10.1080/00207390110067635
Lithner, J. (2011). University Mathematics Students’ Learning Difficulties. Education Inquiry, 2(2), 289–303
Nicholas, J., Poladian, L., Mack, J., & Wilson, R. (2015). Mathematics preparation for university: entry, pathways and impact on performance in first year science and mathematics subjects. International Journal of Innovation in Science and Mathematics Education, 23(1), 37-51
Pan, W. & Hawryszkiewycz, I. (2004). A method of defining learning processes. In R. tkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips (Ed.) Beyond the comfort zone: Proceedings of the 21st ASCILITE Conference (734-742). Perth, 5-8 December. Retrieved from: http://www.ascilite.org/conferences/perth04/procs/contents.html
Rensaa, R.J., & Grevholm, B. (2017). A textbook in linear algebra – the use and views of engineering students. In Grevholm (Ed.) Mathematics textbooks, their content, use and influences. Research in Nordic and Baltic countries (447-470), Cappelen Damm Akademisk, Oslo.
Schmidt, H.G., Wagener, S.L., Guus, A.C., Smeets, M., Keemink, L.M. & van der Molen H.T. (2015). On the Use and Misuse of Lectures in Higher Education. Health Professions Education, December 2015, 1(1), 12-18.
Thomas M.O.J., Druck, I. de F., Huillet, D., Ju, M.K., Nardi, E., Rasmussen, C., & Xie, J. (2015). Key Mathematical Concepts in the Transition from Secondary School to University. In: Cho (Ed.) The Proceedings of the 12th International Congress on Mathematical Education. Springer, Cham, DOI: 10.1007/978-3-319-12688-3_18
Wiggins, H., Harding, A., & Engelbrecht, J. (2017) Student enrichment in mathematics: a case study with first year university students. International Journal of Mathematical Education in Science and Technology, 48(S1), S16–S29. DOI:org/10.1080/0020739X.2017.1352046
Downloads
Published
Issue
Section
How to Cite
