Curriculum development for quantitative skills in degree programs: a cross-institutional study situated in the life sciences

Matthews, Kelly E.; Belward, Shaun; Coady, Carmel; Rylands, Leanne; Simbag, Vilma

doi:10.1080/07294360.2015.1107875

Cited by 9 publications

(5 citation statements)

References 18 publications

(20 reference statements)

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“…Students who study statistics without sufficent mathematics backgrounds can experience serious problems at university. Students' efforts to comprehend quantitative skills and apply them to a quantitative task in their discipline often lead to feelings of anxiety, stress, and lack of self-confidence (Loughlin, Watters, Brown, & Johnston, 2015;Matthews, Belward, Coady, Rylands, & Simbag, 2016;Chamberlain, Hillier, & Signoretta, 2015). In the literature, statistics anxiety has been found to be associated with factors such as mathematical skills, number of mathematics courses completed, major, academic status, perception of past achievement in mathematics courses, time gap between the previous mathematics course, calculator attitude, student learning, ethnicity and the expected grade (Roberts & Saxe, 1982;Zeidner, 1991;Wilson, 1997;Onwuegbuzie, 2004).…”

Section: Mathematics Background and Statistics Anxietymentioning

confidence: 99%

Developing Statistical Understanding and Overcoming Anxiety via Drop-in Consultations

İntepe

Shearman

2020

SERJ

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Students in many Australian universities start their studies mathematically underprepared as there are no prerequisites for mathematics, and assumed knowledge requirements are often overlooked. Many degrees include at least one statistics subject for which students require a reasonable level of mathematical ability to successfully complete. Students’ efforts to grasp quantitative skills often lead to feelings of anxiety, stress, and lack of self-confidence. The Mathematics Education Support Hub (MESH) at WSU provides free support in mathematics and statistics to all students, both undergraduate and postgraduate, to increase their engagement, understanding, and abilities in statistics as well as to overcome their anxiety. In this paper we focus on the drop-in consultation service, which provides “just in time” help in campus libraries. Data is collected for every consultation, which enabling an investigation in relation to the mathematics background of students and the problematic topics in statistics. Text mining is used to examine students’ queries to identify the topics in statistics subjects that students struggle most with. Outcomes of this analysis can be used by statistics instructors and mathematics support centres to improve students’ experience in learning and to help to reduce statistics anxiety in future generations of statistics students. First published February 2020 at Statistics Education Research Journal Archives

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Section: Mathematics Background and Statistics Anxietymentioning

confidence: 99%

Developing Statistical Understanding and Overcoming Anxiety via Drop-in Consultations

İntepe

Shearman

2020

SERJ

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“…For example, large samples of articles from field-specific journals have been mined for pre-defined statistical terms to inform which concepts are key to graduate training in higher education research [ 17 , 18 ], ecology [ 19 ] and oncology [ 20 ]. In the second approach, there are examples from geoscience departments [ 21 ], life science programs [ 22 ], and business schools [ 23 ] which used faculty meetings or surveys of faculty, graduates, or employers to explicitly define key quantitative skills deemed essential for students in these fields.…”

Section: Introductionmentioning

confidence: 99%

Prioritization of the concepts and skills in quantitative education for graduate students in biomedical science

et al. 2023

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Substantial guidance is available on undergraduate quantitative training for biologists, including reports focused on biomedical science. Far less attention has been paid to the graduate curriculum and the particular challenges of the diversity of specialization within the life sciences. We propose an innovative approach to quantitative education that goes beyond recommendations of a course or set of courses or activities, derived from analysis of the expectations for students in particular programs. Due to the plethora of quantitative methods, it is infeasible to expect that biomedical PhD students can be exposed to more than a minority of the quantitative concepts and techniques employed in modern biology. We collected key recent papers suggested by the faculty in biomedical science programs, chosen to include important scientific contributions that the faculty consider appropriate for all students in the program to be able to read with confidence. The quantitative concepts and methods inherent in these papers were then analyzed and categorized to provide a rational basis for prioritization of those concepts to be emphasized in the education program. This novel approach to prioritization of quantitative skills and concepts provides an effective method to drive curricular focus based upon program-specific faculty input for science programs of all types. The results of our particular application to biomedical science training highlight the disconnect between typical undergraduate quantitative education for life science students, focused on continuous mathematics, and the concepts and skills in graphics, statistics, and discrete mathematics that arise from priorities established by biomedical science faculty. There was little reference in the key recent papers chosen by faculty to classic mathematical areas such as calculus which make up a large component of the formal undergraduate mathematics training of graduate students in biomedical areas.

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“…For example, large samples of articles from field-specific journals have been mined for pre-defined statistical terms to inform which concepts are key to graduate training in higher education research ( 6, 7 ), ecology ( 8 ), or oncology ( 9 ). In the second approach, there are examples from geoscience departments ( 10 ), life science programs ( 11 ), and business schools ( 12 ) which used faculty meetings or surveys of faculty, graduates, or employers to explicitly define key quantitative skills deemed essential for students in these fields. We propose an alternative approach to guide the enhancement of quantitative components of the PhD curriculum based upon local needs as suggested by faculty in relevant units.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Quantitative and Data Science Education for Graduate Students in Biomedical Science

Gross

McCord

LoRe

et al. 2021

Preprint

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Substantial guidance is available on undergraduate quantitative training for biologists, including reports focused on biomedical science, but far less attention has been paid to the graduate curriculum. In this setting, we propose an innovative approach to quantitative education that goes beyond recommendations of a course or set of courses or activities. Due to the diversity of quantitative methods, it is infeasible to expect that biomedical PhD students can be exposed to more than a minority of the quantitative concepts and techniques employed in modern biology. We developed a novel prioritization approach in which we mined and analyzed quantitative concepts and skills from publications that faculty in relevant units deemed central to the scientific comprehension of their field. The analysis provides a prioritization of quantitative skills and concepts and could represent an effective method to drive curricular focus based upon program-specific faculty input for biological science programs of all types. Our results highlight the disconnect between typical undergraduate quantitative education for life science students, focused on continuous mathematics, and the concepts and skills in graphics, statistics, and discrete mathematics that arise from priorities established by biomedical science faculty.One Sentence SummaryWe developed a novel approach to prioritize quantitative concepts and methods for inclusion in a graduate biomedical science curriculum based upon approaches included in faculty-identified key publications.

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Curriculum development for quantitative skills in degree programs: a cross-institutional study situated in the life sciences

Cited by 9 publications

References 18 publications

Developing Statistical Understanding and Overcoming Anxiety via Drop-in Consultations

Developing Statistical Understanding and Overcoming Anxiety via Drop-in Consultations

Prioritization of the concepts and skills in quantitative education for graduate students in biomedical science

Enhancing Quantitative and Data Science Education for Graduate Students in Biomedical Science

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