Is the Teaching of Statistical Calculations Helpful to Students' Statistical Thinking?

Seabrook, Rachel

doi:10.2304/plat.2005.5.2.153

Cited by 7 publications

(6 citation statements)

References 9 publications

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“…Psychology students were chosen for this study as, while the course is not mathematics-based, it nevertheless consists of a heavy quantitative component involving statistics. Despite the importance of statistics in the psychology curriculum, it nevertheless remains one of the least liked and poorly performed components of the course (Dempster & McCorry, 2009;Seabrook, 2005) with students tending to do very badly on statistics exams (British Psychological Society, 2003).…”

Section: Participantsmentioning

confidence: 99%

Maths anxiety in psychology undergraduates: A mixed–methods approach to formulating and implementing interventions

Thompson¹,

Wylie²,

Hanna³

et al. 2016

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Due to the empirical nature of the discipline, psychology students, during the course of their degree, are required to become proficient with a range of quantitative methods. Unfortunately many of these students experience high levels of maths anxiety, which can have a damaging effect on this aspect of their educational development. The first study in this paper used focus groups to identify, from psychology undergraduate and postgraduate students, potential interventions that could be used to reduce anxiety in an undergraduate sample. The second study implemented those interventions that were deemed valid and practical on a sample of 246 psychology first and second year undergraduates. The effectiveness of these interventions was mixed, but does suggest further avenues that tertiary educational institutions could take to reduce maths anxiety in their student body, in particular enhancing the use of real–life examples in quantitative methods teaching.

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Section: Participantsmentioning

confidence: 99%

Maths anxiety in psychology undergraduates: A mixed–methods approach to formulating and implementing interventions

Thompson¹,

Wylie²,

Hanna³

et al. 2016

bpsptr

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show abstract

“…A further aim was to promote motivation and engagement with the statistical content. Statistical thinking and metacognitive skills are difficult to measure (Seabrook, 2006) and without an experimental approach, it is difficult to link changes to specific aspects of the assessment strategy. Much more straightforward is asking students about their use of feedback and to do this we distributed a short questionnaire to students just completing the course and to recent students for whom we had contact details.…”

Section: Evaluation and Development Of Assessment Strategymentioning

confidence: 99%

Assessment Methods in Statistical Education

Bidgood¹,

Hunt²,

Jolliffe³

2010

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Statistics is not only a subject in its own right but is also applied to diverse other subjects, including the sciences, geography, psychology, business and economics. Consequently assessment may need to cover a very wide-ranging set of topics and activities taught within a statistics curriculum. In this chapter we consider the implications of the ubiquity of the application of statistics and its pedagogy, the significant impact of this broad 'learning base' on what should be assessed and the plethora of ways assessment and feedback can be provided.

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“…Additionally, instructors may worry that simultaneously teaching programming and challenging statistical concepts may be too burdensome for introductory statistics students (i.e., the high cognitive load would prohibit effective learning; Sweller, 1994). While teaching statistics via hand calculations can contribute to students' computational understanding, the effect is quite small (Seabrook, 2006). Additionally, recent work demonstrated that priming mathematical calculation prompts students to recall and rigidly apply formulae, rather than try to make sense of a problem (Lawson et al, 2021).…”

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confidence: 99%

Technology or tradition? A comparison of students’ statistical reasoning after being taught with R programming versus hand calculations.

Ditta¹,

Woodward²

2024

Scholarship of Teaching and Learning in Psychology

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There has been a recent push to teach introductory statistics for psychology majors using data analysis software that requires programming skills, like R, yet few studies have directly compared the effects of teaching statistics with R versus other popular methods, like hand calculations. While teaching statistics with R helps students develop useful programming skills that are applicable outside of psychology, the challenge of teaching complex statistical content and technical programming skills simultaneously may be overwhelming for first-time statistics students. Under such circumstances, students may focus on learning the programming skills at the expense of the—perhaps more important—statistical interpretation skills. In a tightly controlled classroom study utilizing almost identical course materials, we examined whether students’ understanding of conceptual introductory statistics content was initially hindered through teaching with R versus hand calculations. We compared exam results on statistical interpretation questions across the three exams. Analyses revealed no significant differences in performance between students taught hand calculations versus R programming on any of the exams. Though these results are preliminary and in need of additional testing, it seems feasible that psychology undergraduates can learn introductory statistics while learning R, and that students do not get fixated on the computation at the expense of interpretation. Future work should investigate the long-term effects of teaching statistics with R (compared to hand calculations), as differences in conceptual understanding may not emerge after a single course.

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Is the Teaching of Statistical Calculations Helpful to Students' Statistical Thinking?

Cited by 7 publications

References 9 publications

Maths anxiety in psychology undergraduates: A mixed–methods approach to formulating and implementing interventions

Maths anxiety in psychology undergraduates: A mixed–methods approach to formulating and implementing interventions

Assessment Methods in Statistical Education

Technology or tradition? A comparison of students’ statistical reasoning after being taught with R programming versus hand calculations.

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