Design and implementation choices > Roles of e-assessment in course design

Question 31
What are the relations between the mode of course instruction and students' performance and activity in e-assessment?

For instance, is there a difference between performance in traditional and flipped or blended learning environments using e-assessment?

What motivates this question?

There is now a large body of research showing that active learning approaches are more effective than traditional lecturing (Freeman et al., 2014), including studies of mathematics teaching (e.g., Maciejewski, 2015). As lecturers are encouraged to adopt active learning approaches, while at the same time e-assessment is increasingly prevalent, it is important to understand whether there are differences in the way that e-assessment operates in the two types of learning environment.

On the one hand, there are reports of positive experiences when using e-assessment as part of a course using a flipped classroom model (e.g. Sangwin, 2019).

On the other hand, Cybinski and Selvanathan (2005) compared the experience of two groups of students enrolled in an introductory statistics module – one group was exposed to the traditional lecturing style, while a second group was exposed to a flexible learning environment. The results of the survey investigating the influence of each learning mode on students’ performances suggest that the group studying under a flexible learning environment experienced a high level of test and performance anxiety.

Investigating this question would help to address the call from Vroom et al. (2022, p. 14) for work to “explore the connection between student perceptions of various classroom characteristics in relation to the assessment approaches of those classes.”

What might an answer look like?

Experiments could be used to compare groups of students experiencing active/traditional learning environments, in terms of their engagement with and performance in e-assessment. This could extend existing work comparing outcomes between active/traditional conditions (e.g. Maciejewski, 2015; Code et al., 2016) to consider e-assessment.

References

Code, W., Merchant, S., Maciejewski, W., Thomas, M., & Lo, J. (2016). The Mathematics Attitudes and Perceptions Survey: an instrument to assess expert-like views and dispositions among undergraduate mathematics students. International Journal of Mathematical Education in Science and Technology, 47(6), 917–937. https://doi.org/10.1080/0020739X.2015.1133854

Cybinski, P. and Selvanathan, S. (2005) Learning experience and learning effectiveness in undergraduate statistics: modeling performance in traditional and flexible learning environments. Decision Sciences Journal of Innovative Education. 3(2), 251-271.

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. 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

Maciejewski, W. (2015). Flipping the calculus classroom: an evaluative study. Teaching Mathematics and Its Applications, 19(4), hrv019. https://doi.org/10.1093/teamat/hrv019

Sangwin, C. (2019). Developing and evaluating an online linear algebra examination for university mathematics. In Eleventh Congress of the European Society for Research in Mathematics Education. Utrecht, Netherlands. Retrieved from https://hal.archives-ouvertes.fr/hal-02430556

Vroom, K., Gehrtz, J., Apkarian, N., Elizondo, T. A., Ellis, B., & Hagman, J. (2022). Characteristics of interactive classrooms that first year students find helpful. International Journal of STEM Education, 9(1). https://doi.org/10.1186/s40594-022-00354-y