Contextual Background:
Two key academic skills that are core to the completion of the MSc Applied Psychology in Fashion course are English skills (given the writing- and reading-intense assessments) and numeric skills (statistics being a core taught and assessed component). The ideal student (as it were) should be equipped with both skillsets in evaluating psychological theories critically and creatively. Yet the students who enter the course come from a diverse range of academic backgrounds and each student has a different way and pace of learning.
Evaluation:
Regarding English skills, the course offers an optional language development course. Here, a language tutor meets students once every week or two weeks to teach and discuss a broad range of English language-related topics – often topics that directly relate to upcoming assessments, e.g., academic/scientific writing and academic presentations. However, broader UAL-level language courses are currently not advertised to the students. Regarding numeric skills, the course offers a number of additional workshops to analyse datasets from published papers. Yet while the statistics lectures – aimed at the whole student body – are written to be interactive and hands-on, and despite the fact that the statistics lectures receive high student satisfaction ratings every year, more could be done to address the diverse range of student needs in relation to numeric skills and experiences. This may especially be an urgent matter to resolve for next year – the student numbers are expected to rise by 50%, which will accompany greater diversity in academic skills.
Moving forwards
Given that a university lecture is distinguishable from a personal tutorial, there are inevitable constraints to meeting all the personal needs of students. However, the first step is to understand the students before taking any action (Wansart, 1995). This can be achieved by the course leader closely interacting with the student representatives regularly to gather student opinions – for the clarity of information, the level of consensus of each opinion will also be collected. Opinions can also be gathered as part of the bi-annual course committee meetings.
The gathered information can then be used to create responses to students. Responses may include both the incoming/prospective and current students. Regarding the former, the course leader may identify recurring gaps in knowledge and advertise appropriate textbooks during open day events or equivalent – this way, not only can potential knowledge gaps be narrowed, but student expectations can also be managed. Empirical research points towards the general direction that improved student expectations can be beneficial for both student achievement and satisfaction (Paechter, Maier, & Macher, 2010; Slavin, 1980).
The academic diversity among current students can be addressed by creating supplementary academic sessions, e.g., UAL-wide language courses and additional statistical workshops. Equally important is to instil the importance of self-directed studies and guide students to a selection of resources (e.g., textbooks and multimedia resources). The justifications/benefits of this approach are the following: the current QAA Subject Benchmark Statement for Psychology promotes self-directed studies (QAA, 2023); self-efficacy (or the students having control of their own studies) is an important marker of learning (Gibbs, 2014); the approach is inclusive to students who benefit from independent, “silent” learning (Harris, 2022). Based on recent student surveys that expressed online lectures to be detrimental to their learning, all sessions will also be carried out in person.
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Reference
Gibbs, G., 2014. Maximising student learning gain. In A Handbook for Teaching and Learning in Higher Education (pp. 215-230). Routledge.
Harris, K., 2022. Embracing the silence: introverted learning and the online classroom. Spark: UAL Creative Teaching and Learning Journal, 5(1), pp.101-104.
Paechter, M., Maier, B. and Macher, D., 2010. Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computers & education, 54(1), pp.222-229.
Quality Assurance Agency. 2023. “Psychology.” https://www.qaa.ac.uk/the-quality-code/subject-benchmark-statements/subject-benchmark-statement-psychology
Slavin, R.E., 1980. Effects of individual learning expectations on student achievement. Journal of Educational Psychology, 72(4), p.520.
Wansart, W.L., 1995. Teaching as a way of knowing: Observing and responding to students’ abilities. Remedial and Special Education, 16(3), pp.166-177.