The application of computer aided assessment (CAA) is widely employed across many domains in Higher Education. It is suggested that computer aided methods of assessment offer several benefits in Higher Education such as reduction in lecturer workload for large class groups and the possibility of a higher degree of consistent objectivity in the assessment process. The increasing sophistication offered by CAA systems makes the use of such technologies attractive for assessment purposes. The assessment develops a communication with the student where feedback and estimation of performance are the main components. Research focusing on the assessment technologies (Jordan, 2013; Sangwin, 2012; Narciss et al, 2014) suggests growing maturity in the domain of mathematics and the promise of greater availability of such technologies to lecturing staff. The benefits and positive aspects of online assessment have been outlined in the literature for, mathematics applications (Passmore & Brookshaw, 2011), online quizzing (Jordan, 2013) and formative assessment and feedback (Tempelaar et al, 2014; Cox 2012). The growth of Computer Algebra Systems (CAS) (Sangwin, 2012) extends the mechanics of computer aided assessment systems by introducing greater capability to consider concepts that are too abstract for lower order testing methods; for example, Multiple Choice Questioning. The importance of the role of assessment technologies cannot be understated and their encapsulation within Higher Education curricula is becoming an accepted element of programme design.
In Ireland, the mathematics curriculum was redesigned (Prendergast, 2016) in an attempt to address reported deficiencies in the mathematical skillsets of students at second level. A review of the mathematics provision (McCraith, 2015) raised further issues about the skillset with particular reference to the transition from second level to third level, the use of Information and Communications Technologies, and international comparison. Discussion with lecturing colleagues in a similar Higher Education institution in Finland revealed similar concerns (Rinneheimo, 2010; Cole et al, 2014).
This paper presents the findings from a two year longitudinal study conducted by the partner Higher Education institutes in Finland and Ireland using a mixed methods approach beginning in academic year 2015/2016. The research gathered information from students and lecturers on their respective expectations and perceptions about online assessment of first year engineering mathematics. The basis for the research was anecdotal observation of negative behavioural attributes, prior to, and shortly after, online assessment. Evidence within the literature suggests these attributes may be deeply embedded in students as they make the transition to third level (Gallimore & Stewart, 2014), leading to greater support requirements in third level. The research outputs are forming a baseline for the design of improved programmes utilizing online assessment methods. The interaction of students and staff with the technologies is vital to the success of these programmes, in conjunction with an understanding of the perceptions held by students (Tempel & Newmann, 2014) in relation to barriers, and how students engage online.
The research was designed within the boundaries of a social-cognitive approach, to self-efficacy theory, within engineering mathematics (Bandura, 1977; Martchand, 2012; Artino & Jones, 2012), as the core concept, to help the researchers gain a better understanding of the online assessment experiences, prior to and post assessment. The premise is that the actions and reactions of the students are influenced by their own observations and experiences; these pre-existing attributes are determining factors of self-efficacy and awareness of learning. The study of lecturers as a parallel activity was conducted to determine if any mismatch exists between the expectations and perceptions of lecturers and those of students.
Artino, A.R. & Jones, K.D., 2012, Exploring the complex relations between achievement emotions and self-regulated learning behaviors in online learning, The Internet and Higher Education, 15(3), pp. 170-5 Ashton, H.S., Beevers, C.E., Korabinski, A.A. & Youngson, M.A., 2006, Incorporating partial credit in computer-aided assessment of mathematics in secondary education, Br J Educ Technol, 37 (1), pp. 93 – 119. Bandura, A., 1977, Self-efficacy: Toward a Unifying Theory of Behavioral Change, Psychological Review, 84(2), pp. 191 – 215. Cole, J.S., McCartan, C.D., Tuohi, R. & Steinby, P., 2014, Mathematics background of engineering students in Northern Ireland and Finland, Proceedings of 10th International CDIO Conference, Universitat Politecnica de Catalunya, Barcelona, Spain, June 16 – 19. Gallimore, M. & Stewart, J., 2014, Increasing the impact of mathematics support on aiding student transition in higher education, Teaching Mathematics and its Applications, 33(2), pp. 98-109. Jordan, S., 2013, E-assessment: Past, present and future, New Directions, 9(1), pp. 87-106. Marchand, G.C. & Gutierrez, A.P., 2012, The role of emotion in the learning process: Comparisons between online and face-to-face learning settings, The Internet and Higher Education, 15(3), pp. 150-60 McCraith, B., 2015, Average is no longer good enough – it’s time for a step change in STEM education in Ireland, in Education Matters, Yearbook 2016 – 2016, pp. 13-18. Narciss, S., Sosnovsky, S., Schnaubert, L., Andrès, E., Eichelmann, A., Goguadze, G. & Melis, E., 2014, Exploring feedback and student characteristics relevant for personalizing feedback strategies, Computers & Education, 71, pp. 56-76 Passmore, T. & Brookshaw, L., 2011, A flexible extensible online testing system for mathematics, Australasian Journal of educational Technology, 27(6), pp. 896 – 906 Prendergast, M., Breen, C., Carr, C. & Faulkner, F., 2016, Investigating Third Level Lecturers' Awareness of Second level Curriculum Reform, 13th International Congress on Mathematical Education. Rinneheimo, K., 2010, Methods for teaching mathematics case Tampere University of Applied Sciences, 1st intl workshop on maths and ICT: Education, Research and Applications, Bucharest, pp. 48-55. Sangwin, C., 2012, Computer Aided Assessment Of mathematics Using STACK, 12th International Congress on Mathematical Education, South Korea. Tempel, T. & Neumann, R., 2014, Stereotype threat, test anxiety, and mathematics performance, Social Psychology of Education, 17(3), pp. 491-501. 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, The Internet and Higher Education, 15(3), pp. 161-9.
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