Charlotte R Brookfield, Malcolm Williams, Luke S Sloan, Emily Maule
{"title":"Engaging Social Science Students with Statistics: Opportunities, Challenges and Barriers","authors":"Charlotte R Brookfield, Malcolm Williams, Luke S Sloan, Emily Maule","doi":"10.5038/1936-4660.14.2.1386","DOIUrl":null,"url":null,"abstract":"In 2012, in a bid to improve the quantitative methods training of social science students in the UK, the £19.5 million Q-Step project was launched. This investment demonstrated a significant commitment to changing how we train social science students in quantitative research methods in the UK. The project has involved eighteen higher education institutions exploring and trialling potential ways of engaging social science students with quantitative approaches.\n This paper reflects on the activities of one Q-Step centre based in the School of Social Sciences at Cardiff University. As well as describing some of the pedagogic changes that have been implemented, the paper draws on data to begin to evaluate the success of new approaches. Specifically, data showing the proportion of students undertaking a quantitative final-year dissertation project is used to measure the impact of these activities. The data presented in this paper suggest that resistance to learning quantitative research methods and engaging with such techniques has decreased. The data also indicates that students see this learning as beneficial for their own employability. Despite this, closer analysis reveals that several students change their mind about employing quantitative methods in their own research part way through their dissertation journey. We argue that while social science students are comfortable learning about quantitative approaches, they are less confident at applying these techniques. Thus, the paper argues that there is a wider challenge of demonstrating the relevance and appropriateness of such approaches to understanding the social world.","PeriodicalId":36166,"journal":{"name":"Numeracy","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Numeracy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5038/1936-4660.14.2.1386","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
In 2012, in a bid to improve the quantitative methods training of social science students in the UK, the £19.5 million Q-Step project was launched. This investment demonstrated a significant commitment to changing how we train social science students in quantitative research methods in the UK. The project has involved eighteen higher education institutions exploring and trialling potential ways of engaging social science students with quantitative approaches.
This paper reflects on the activities of one Q-Step centre based in the School of Social Sciences at Cardiff University. As well as describing some of the pedagogic changes that have been implemented, the paper draws on data to begin to evaluate the success of new approaches. Specifically, data showing the proportion of students undertaking a quantitative final-year dissertation project is used to measure the impact of these activities. The data presented in this paper suggest that resistance to learning quantitative research methods and engaging with such techniques has decreased. The data also indicates that students see this learning as beneficial for their own employability. Despite this, closer analysis reveals that several students change their mind about employing quantitative methods in their own research part way through their dissertation journey. We argue that while social science students are comfortable learning about quantitative approaches, they are less confident at applying these techniques. Thus, the paper argues that there is a wider challenge of demonstrating the relevance and appropriateness of such approaches to understanding the social world.