• They significantly influence achievement [2; 3] and, subsequently, students' career choices [e.g. 4; 5]

• Given its influence, it is quite concerning to see that many psychology students have negative attitudes towards statistics [6] - As many as 84% of student samples fail to see its relevance in psychology [7]! 😱

  • These attitudes are distinct and independent of their attitudes towards the course as a whole [3]

• Current research has also yet to consider undergraduate experiences (especially amongst psychology students), despite it being a pivotal period of students' lives [8]

  • Your experiences and attitudes towards statistics now will probably play a significant role in shaping the career you chose and whether you embrace/denounce statistics in that career! ✳️ [5; 9]

If you're a psychology/social sciences student/educator, Have you encountered these negative sentiments on the ground? 🤔💭

• Because statistics is an important and heavily emphasised skill in psychology and related professions [10] - Bad stats, or even an aversion towards stats in applied settings could have serious implications on the people/issues we're working with!

• Careers, academic or otherwise, should and have been multidisciplinary [11] - I believe that these negative attitudes towards statistics hinder us from embracing this approach.

• These attitudes likely reinforce each other, such that having career goals that are not statistics-inclusive may also predict disengagement, poorer attitudes and achievement in statistics modules [12]

Current research has yet to look at whether and how longer-term variables/goals influence students' attitudes (+ achievement and engagement) in statistics

• Research has only centred around achievement and experiences/attitudes within the period of students' degrees

• But research into younger samples and within STEM subjects has found that students do think ahead about what careers they want to pursue and that it influences their educational experiences and attitudes [12]

Perhaps addressing and capitalising on this relationship in teaching could be an effective intervention strategy in improving attitudes and subsequent achievement? 💭

We know and see the impact of our work, but how do we measure it? Does it really exist? Would this impact whether or not we get funding?

Have you had similar personal experiences? Or have your peers expressed similar sentiments, where their attitudes towards statistics pushed them away from certain careers? 💭

Think of what you're doing now - A degree or a career centred around a discipline/topic. Are you doing it because you find it important/useful/not too costly, and because you believe you can do well in it? Do these two considerations affect each other? 💭

• It has been originally hypothesised that these two beliefs are not mutually exclusive - If one belief was low, high values on the other belief will be of little or no consequence for motivation and behaviour [17]

• Expectancy and value beliefs "combine multiplicatively to determine force" [18]

• And the little studies that address this have empirically validated these hypotheses [e.g. 19; 20]

Would you become a data scientist if you dislike statistics/do not find it important, even if you believed you would do well in it? 💭

This also has implications for teaching (and other) interventions!

• Lauermann and colleagues' (2017) paper pointed out a few failed interventions, where a focus on one type of belief in the absence of (or lessened emphasis) the other failed to produce desired outcomes

Would you strive to become a researcher if your lecturer repeatedly encourages you that it's achievable, but doesn't explain how this career could benefit you/society? 💭

• As mentioned, previous studies have found that expectancy-value beliefs and career goals influence each other over time - Adolescents' attitudes towards maths and their career plans changed as they progressed through high school [12]

• This further reinforces the wide-ranging implications of this relationship on teaching and achievement

Using multiple methods of data collection and having them corroborate each other is also good research practice, and really cool 😎

• If we had gone with a purely quantitative approach, we wouldn't have found the more positive attitudinal aspects that we seldom see in stats ed research... Isn't that cool?! Doesn't that open up more avenues of research?!

• Robust models and coefficients were obtained, which were very similar to our original moderation model

• Errors appear to be homoscedastic

• Our sample is normally distributed

• And there were no concerning outliers

• This is a small-medium effect size [21]

• Which basically means that we coded and categorised the data for the presence of expectancy-value variables (top-down), as well as any additional themes (bottom-up)

• To answer our key question on a potential reciprocal relationship, we counted the frequency of agreement for each direction of the relationship (Q9.5 + Q9.6) and ran that through a simple chi-square test

• Supported by previous findings [31], this highlights the role of curriculum in influencing how students perceive their field of study and their career goals

😀 “I personally have always either like maths or at the least find it easy. This means my brain has landed itself quite easily to stats and influenced me to look into data analysis as a potential career.”

😀 “I used to think statistics and handling data sets is quite daunting but now I feel confident in this, which has probably made me more interested in research”

😥 “Yes as I’m not very stats inclined I wouldn’t be confident in research as in clinical”

😥 “I've found the mathematics parts and R coding quite difficult, so it's definitely made me more apprehensive to pursuing a career in psychology”

In twenty-two instances, the liking/enjoyment and utility of statistics [value beliefs] were cited as influencing participants to consider a statistics-inclusive career, and vice versa

😀 “I don't mind statistics (mostly) as I used to enjoy maths, so I am willing to learn what I need to for my future career.”

😀 “It has influenced my career goals as I enjoyed the module so thought of maybe having a career in that instead.”

😀 "I believe so. This is because i know have a new career i could choose that is not very related to psychology (data analyst).”

😥 “Doing statistics has made me realise that I'd prefer to not do a job in my career where I have to do a lot of computer-based statistics and analysing data, I prefer the social modules more.”

😥 “I don’t like statistics so will stay away from jobs concerning them”

“maybe, i know to be able to achieve my career goals, i will need to achieve all things including statistics, so therefore i try to put on a positive attitude towards it”

“Yes, I want to succeed and do well so I put effort into understanding statistics instead of just passively taking them in”

“I am aware that statistics will increasingly be more important as I progress in this career aspiration, so I am more determined to try to understand statistics albeit any struggle.”

“My career goals have emphasised the importance of statistics to me and so i would really like to do well in it, no matter how hard or scary it is”

Coded instances of value beliefs were substantially more than those of expectancy beliefs (44 instances).

• The majority of participants in this group elaborated on the importance of statistics, where having statistics-inclusive career goals led participants to emphasise the importance of doing well in statistics, followed by utility and interest

“Yes, as I know statistics are useful in my career goals I want to achieve good grades in order to make it in the field”

“Additionally my career goals have made me view statistics as much more important in society than I previously did”

“Possibly, as I knew before starting statistics that I wouldn't prefer to use them in my career, so maybe this makes me enjoy it less learning it now as I know already I'd rather not have to.”

“Yes, previously i would have avoided stats believing I wouldn't be able to understand it but since my goals required it, and thus making me engage in statistics, I realised how much I enjoy statistics. Additionally my career goals have made me view statistics as much more important in society than I previously did”

• It also emphasises that yes, longer-term and seemingly more 'distal' variables do play a part in how students experience and engage in statistics

• Past studies have also found that those with career-specific/related goals adopt more positive academic beliefs [32]

Could we benefit from teaching/other interventions that highlight the relevance of statistics across different careers? How can we do this? (e.g. provide scenario-based problems) 💭

• As mentioned in the poster, doubt and uncertainty do in fact influence students' academic attitudes and engagement [33, 34]

• This is something we didn't account for when developing our hypotheses, but rather only emerged and was coded for during analysis

• Therefore this would be great to expand on for further study - Maybe career-relevant interventions will have an additional benefit of bridging this uncertainty in students?

• 🔵 posts expand more into the background of my study

• 🟢 posts elaborate a bit more on the quantitative analysis

• 🟣 posts discuss the quantitative findings

• 🟡 posts discuss and expand on the qualitative findings

• ⚪️ posts are just extra contextual information

• 💭 When you see this emoji - I want you to share your thoughts!

Please note that what I have here is not exhaustive and is not meant to replace/represent a write-up! They more so reflect the questions I would ask myself if I saw this poster and/or learnt about this study.

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