Shifting our focus from undergraduate to postgraduate students, RoSE's Deputy Director, Megan, explores the anxieties that postgraduate students face with statistics, especially as they encounter a curriculum novel to their prior degrees. Read on to find out how Megan transformed students' experiences of feeling 'lost at sea' into collaborative initiatives that boost motivation and debunk statistics myths!

Many years ago when I first started teaching, I was given the task of delivering small-group statistics seminars to my institution’s postgraduate taught Psychology students. I went into the task with my own set of misconceptions. Postgraduate students will have the statistics knowledge already, right? After all, they already have an undergraduate degree which suggests they have a good amount of skills under their belt already. As a result they should have less anxiety about statistics… surely?

As my teaching progressed, I realised that these impressions were untrue. Our postgraduate community studies Psychology as part of a Conversion course. As a result they come from a wide range of diverse backgrounds, not just in terms of their geographical background but also their undergraduate degree. Students have a great and varied skill set, but this doesn’t necessarily include a statistical background. Moreover, even though our postgraduate students have at least a level 4 (C grade) Maths GCSE as part of their minimum entry requirements, some may not have touched maths or statistics in years. Why wouldn’t they have studied mathematical subjects for such a long time? Perhaps, because they are just as anxious about statistics as undergraduate populations.

I won’t reiterate the many papers investigating the phenomena that is statistics anxiety in Higher Education, suffice to say that it exists. However, when you look closer at the literature, it is clear that the evidence for this in the postgraduate population is limited at best. What is out there does suggest that a significant proportion of postgraduate students experience statistics anxiety (Onwuebugzie & Wilson, 2003), and have similar perceptions of statistical incompetencies and fears of failure (Amiran & Abbasi-Sosfadi, 2021). Additionally, a negative relationship between statistics anxiety and course achievement exists (Maat, Zakaira, & Rosli, 2016; Ratanaolarn, 2016). Thus, in postgraduate students, statistics anxiety has similar impacts on attitudes and attainment as it does for undergraduates.

Back in 2022, I wanted to understand how attitudes towards statistics impacted our postgraduate Psychology Conversion students. In addition, I also wanted to see how we could help them, particularly during the first few weeks of their degree programme. I wanted to focus specifically on this transitional period for a couple of reasons. Firstly, postgraduate students do not feel they get the support they need during this time (Poobalan, Barrow, and Cleland, 2021), perhaps due to an institutional implicit assumption of experience and expertise for this population (Tobbell & O’Donnell, 2013). Thus, students feel anxiety, worthlessness, and isolation during this time (McPherson, Punch, & Graham, 2017; Demioren et al., 2014). Secondly, it has been reported that the time taken to adapt to postgraduate studies can range anywhere between six (McClure et al., 2007) and 10 months (Coneyworth et al., 2019). Whilst this would still leave plenty of time for students on a three-year undergraduate programme, students on a one-year Masters programme may find they spend their entire degree simply getting used to their studies. By targeting interventions at them during the first few weeks of the course, it would hopefully make them as effective as possible in improving attitudes towards statistics.

What did I do?

I led a three week co-design study aimed at understanding student perceptions of the statistical component of their degree programme, as well as what could be done to improve these attitudes. Each week, I held a one-hour session with a group of students which were structured around the ‘WE-DID-IT’ method of co-design research (Doller & D’Angelo, 2020). This method advises researchers to firstly understand the challenges and experiences of their stakeholders (‘WE’), before constructing and developing solutions to those challenges (‘DID’), and testing and adapting solutions with relevant stakeholders (‘IT’). 

Three students from our Psychology (Conversion) MSc programme volunteered to take part. Their previous undergraduate degrees included French and History, Theology, and Business Studies. Thus, these degrees had little to no inclusion of statistical content. 

In week one, I took a semi-structured focus group approach and asked students about their overall experiences with their statistics modules. Questions covered topics such as levels of support they had received, whether they were confident enough to pass their statistics-based modules, and whether anything else would help them to feel more confident. 

Week Two began with a brainstorming activity. Participants were individually asked to reflect on what had been discussed in the previous session, and with this in mind write down the different types of resources and support they felt would be useful at the beginning of their degree programme. These suggestions were then used as prompts for a subsequent unstructured focus group. As a group, we discussed the benefits and challenges associated with each resource type. These were used by me as inspiration for Week Three; I used the student responses to create a series of prototype resources that the group then tested and gave feedback on during the final session. 

What did I find?

I conducted a semantic thematic approach to analysing the focus group data, and found a few interesting themes. Some of these corroborated previous literature into undergraduate populations, whilst others left me with a lot to think about. I’ve categorised each theme below into my takeaways from the analysis:

Takeaway 1: Students are drowning, and we need to save them quickly

Yes, this is an unusual theme name. However, for some reason, when asking the group how they felt about studying statistics, a lot of water-based analogies emerged. Specifically, students talked a lot about how they quickly felt out of their depth (pun not intended) within the first few weeks of the academic year:

 “So I did the first lecture and I was like, oh yeah, I get this…and then after that was in like at the deep end.” (Participant 2)

As the first few weeks went by student felt they had “been dropped into really deep water” (P1), and like they were “lost at sea” (P3). For one student who was initially looking forward to studying statistics, they pointed out that “it’s been rare that I’ve felt…out of my depth” (P2). Even when discussing the benefits of small-group seminars, students said that they were “just helping me to tread water a bit.” (P1). 

What was striking for me was that these students also said they had been looking forward to studying statistics, and that they initially felt it could be their strongest module. However these quotes show not only how quickly these feelings changed, but how dramatically they changed to the point where they felt like they were drowning.

Takeaway 2: As educators, we need to challenge our assumptions about postgraduate study

As statistics educators, we do our best to understand and improve the student experience. However, my findings suggested that not only do postgraduate students face similar challenges to undergraduate students, but that we need to address their unique experiences with statistical content in order to support their learning.

For example, students pointed out how the use of complex statistical knowledge can be confusing for them. In fact one student asked that we “Talk about ANOVA… kind of in plain English.” (P2). The use of interchangeable language by different lecturers also exacerbated these problems:

“Lecturers will often be like, oh, A, C, whatever, don’t really care. But when you don’t understand what A means, or what C means, or whether they’re the same, it’s so confusing.” (Participant 3)

The use of complex language in statistics has been seen as an issue in previous statistics anxiety research, thus is not unique to postgraduate students. What may be unique, however, is how our assumptions about this group may be counterproductive to their learning. For context, students in the Psychology (Conversion) MSc programme study statistics alongside our second year undergraduate Psychology community. As a result, students felt that it was easily assumed that they would have the same level of statistical knowledge as undergraduates who already had one year’s worth of statistics lectures:

“They would often say phrases like ‘well obviously I won’t go over this too much ‘cause we learned that last year’, and then it’s like, ah, I didn’t learn this last year.” (Participant 1)

Sometimes this assumption came across to students more directly in small-group seminars. The group stated that educators “can be a little bit… cold if you don’t know something that is… a bit basic” (Participant 1). As someone who is passionate about improving the student experience in statistics, this is hard to hear. However, what is clear from this research is that postgraduate and undergraduate students do not have the same experience, and we need to stop assuming they do. Moreover, we need to pay additional attention to the postgraduate community so they not only feel confident in their developing statistical competencies, and included within the wider statistics education community.

Takeaway 3: Resource curation does not equate to student engagement 

This may not be a takeaway that is unique to statistics education, but this was a clear theme nonetheless. When the group discussed the benefits and drawback of curating support resources for statistics education, it was questioned whether students would engage with new or existing support resources, given that they would not form part of a summative assessment. For example, suggested resources or methods for improving confidence and attitudes towards statistics included a personalised welcome booklet and the extension of existing support workshops that were focused on research design. One student pointed out, with regards to the extension of research methods workshops:

“Actually, if you’re not going to be assessed on it, would people engage with it?” (Participant 2)

Another agreed and suggested that whilst they quite like “learning stuff like that… it’d maybe get to a point where people just wouldn’t be turning up to them.” (P1). Another acknowledged they would engage with resources, even though they “appreciate it’s a bit abnormal” (P3).  It was also pointed out that by creating optional, formative resources, students may not put as much effort into using them. An example of a recent formative presentation was given:

“I wasn’t as nervous as I probably would have been if I didn’t know that this was worth 30% of the module” (Participant 1)

The important thing to consider here is that educators, we need to balance out the efforts made into creating supportive resources with the likelihood of student engagement with them. Alternatively, we also need to find ways in which to increase engagement with the content such that the intended changes in statistics attitudes occur, and our efforts as educators are worthwhile.

What have I done in response to this, and what should we look at in the future?

In the summer of 2022, I used my knowledge from this research to design a day-long statistics induction day for new postgraduate students. This was delivered to new postgraduate Psychology (Conversion) students during Induction Week in September 2022. Rather than giving students a day long statistics course, activities focused on increasing motivation and debunking myths associated with the maths needed to succeed in statistics were conducted. A networking lunch was also provided so that postgraduate students could meet members of the teaching team, and students were also told where and how they could access support whilst they were studying statistics on the course. This is now a permanent feature of our Induction Week curriculum for postgraduates, and while there have been some small tweaks over the years, open feedback suggests that this is a useful addition:

“I enjoyed how they made the subject seem simple and how they reduced the anxiety around the subject.” (Anonymous, 2022-2023 Psychology (Conversion) MSc cohort)

This research has been a good start into understanding and acknowledging the postgraduate experience of studying statistics on a Psychology degree. However, I also think that much more research into this population is needed, as many questions remain unanswered. Firstly, the postgraduate student body is diverse. How do we bridge the gap between prior knowledge and course expectations such that all students feel supported? As educators, what exactly are our assumptions and attitudes towards postgraduate students studying statistics, and do these need to be addressed in order to maximise student support? If we do need to curate or provide resources, how do we ensure we do this without providing an overwhelming amount of support? Additionally, how do we actually encourage engagement with these resources in the first place?

I don't know the answers to all of these questions yet. What I do know is that the postgraduate student community are a unique group with a lot of knowledge and enthusiasm. With that in mind, I’ll continue to foster a supportive and encouraging learning environment for my students, knowing that I’m working towards making a difference to their statistics education.