Introduction & Background
My experience refers to an open access class which I deliver to students once a week. This is to offer supportive learning to any difficulties they encounter with statistics, and the application of statistics to data analysis assignments for the Research Methods Unit. I was unaware of the impact of supportive learning on students’ statistical skills and data analysis that their coursework assignments involved. I was unaware of the impact of one-to-one consultation and questions that if students posed in relation to their data analyses would make contribution to their achievements.
Evaluation
In the MSc Applied Psychology in Fashion, students tackled Research methods assignments, focusing on data analysis. While some had prior statistics knowledge, others lacked it. A designated day, Wednesdays from 1pm to 4 pm, offered open access for the statistical software in social sciences (SPSS), and data analysis support. Students reserved 20-minutes slots during this period to address specific issues. They submitted technical consultation forms, seeking guidance on statistical tests.
Some students reported that were not confident in using the software and some additional guidance would be a great use of these sessions ahead of time. In addition, I experienced a few students who requested to guide them as to what they had to state on the consultation record form in relation to questions. Other students reported that they had work on Wednesdays and requested different days to meet up for data support.
Students brought their questions into the class,they exchanged ideas with their classmates and through supervised practice conducted the tests. In my opinion this reinforced a pedagogical relationship where students gained knowledge from myself and also from other classmates (Dall’ Alba, 2004).
To enhance students’ learning outcomes, I also conducted SPSS workshops during which I presented the use of relevant statistical tests via fashion psychology research. Students were involved into dialogue discussions and replicated the tests in class, followed by troubleshooting discussion. This approach promoted transformation of self and enhanced a comprehensive data analysis and skills development.
Moving Forward
I provided additional assistance to MSc students unable to attend Wednesday’s open access due to work or statistical challenges, Those booking outside Wednesdays attended face-to-face, discussing hypotheses and justifying test choices for their dissertation topics at mutually agreed times. In other cases students sought in advance guidance on how to use the statistical software even though they had not yet been taught the program during the teaching sessions. They reported that they lacked confidence. I collaborated with the course leader, and we devised a solution: they were advised to visit the library and consult step-by-step guidebooks. Having familiarized themselves with the suggested course reading, then could bring the questions they developed. Some students came with handy questions based on their statistical needs and were aware of their lack of skills. This reflected a challenge as I had to introduce students to be open to independent learning through a variety of ways and not only dependent on the tutor.
Additionally I will use the Student Needs Framework by Edward Peck and the UK’s Student Policy Network (AdvanceHE, 2023a,b) to address statistical competence and foster a sense of community in my approach. This is how I have translated it to my practice:
- Students require a platform or a place for academic exchange, connecting full-time on campus attendees with their remote counterparts and part-time students at a time outside the Wednesdays’ open access.
- Interacting online they were able to talk about statistical test concerns, building online communities around shared interests in understanding relevant tests. This helped them form supportive peer connections.
- I can direct students to other technicians for specialized technical issues if they cannot attend open access on Wednesdays’ due to work responsibilities. Specialized technical issues like software installation on Mac laptops, license problems and remote learning challenges could be solved by other technicians (AdvanceHE, 2023a).
- Students can share feedback on the pros and cons of peer observation. In open access, I can encourage them to highlight positive outcomes, if any, from discussing statistical queries with peers. This will foster awareness of the implications of peer observation and enhance understanding of knowledge acquisition (Dall’ Alba, 2005). It parallels the teacher’s ontology, emphasizing the need to embody knowledge through diverse teaching methods and competences.
References
AdvanceHE (2023a) Professional Standards Framework for teaching and supporting learning in Higher Education. Advance HE: GuildHE, Universities UK. Available from Professional Standards Framework for teaching and supporting learning in higher education 2023 | Advance HE (advance-he.ac.uk) (Accessed 26 February 2024).
AdvanceHE (2023b) Enhancing Student and Learning in Higher Education: Student Needs framework. AdvanceHE:UK. Available from Student Needs Framework | Advance HE (advance-he.ac.uk) (Accessed 26 February 2024).
CAST (2018). Universal Design for Learning Guidelines version 2.2. Retrieved from http://udlguidelines.cast.org.
Dall Alba, G.(2005) Improving teaching: Enhancing ways of being university teachers. Higher Education Research and Development, 14(4),361-372. Routledge. Available from https://doi.org/10.1080/07294360500284771.