A Capstone Course for Undergraduate Statistics Majors

Lazar, Nicole A.; Reeves, Jaxk; Franklin, Christine

doi:10.1198/tast.2011.10240

Cited by 19 publications

(24 citation statements)

References 5 publications

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“…Integrative capstone experiences are an excellent place to integrate (but not to introduce!) these skills, see Lazar, Reeves & Franklin (2011). In addition, cocurricular events can help to provide opportunities for our students to refine their ability to "wrangle" data.…”

Section: Data-related Skillsmentioning

confidence: 99%

Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward

Horton¹

2015

The American Statistician

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The 175th anniversary of the ASA provides an opportunity to look back into the past and peer into the future. What led our forebears to found the association? What commonalities do we still see? What insights might we glean from their experiences and observations? I will use the anniversary as a chance to reflect on where we are now and where we are headed in terms of statistical education amidst the growth of data science. Statistics is the science of learning from data. By fostering more multivariable thinking, building data-related skills, and developing simulation-based problem solving, we can help to ensure that statisticians are fully engaged in data science and the analysis of the abundance of data now available to us.

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Section: Data-related Skillsmentioning

confidence: 99%

Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward

Horton¹

2015

The American Statistician

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“…Megaclasses in introductory statistics seem to emerge around the globe simultaneously, while others have existed for many years in universities that offer the single service course in statistics to all undergraduate students, regardless of their discipline. Several case studies describing experiences and quality improvement lessons learned by teams involved in teaching introductory statistics courses have been published, see, eg, Lazar et al or Petocz . A current list of MOOCs in statistics offered via Coursera appears at https://www.mooc-list.com/tags/statistics .…”

Section: The (Statistics) Megaclass As a Complex Service Production Smentioning

confidence: 99%

The megaclass as a service production system and the challenge of facilitating its continuous quality improvement: Towards a research agenda in a complex domain

Ograjenšek

Gal

2018

Quality & Reliability Eng

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This paper aims to fill a gap in the literature on continuous quality improvement in higher education, regarding factors that may contribute to the effectiveness of megaclasses. We argue for the need to view megaclasses as a complex service production system, using introductory statistics classes as an example. Given the multiple virtual and tangible factors and processes and diverse learning communities involved in the megaclass, we believe that there is a need to better understand both its academic learning outcomes (ie, formation of knowledge, attitudes, and beliefs) and outcomes of service processes (ie, satisfaction levels of stakeholders and service metrics). We propose directions for a research agenda in this rapidly developing arena, using a model of 6 research areas influencing the above outcomes: (1) teaching methods; (2) cognition, learning, and assessment; (3) emotions, attitudes, and beliefs; (4) self‐management and metacognition; (5) social interaction and inquiry patterns; and (6) technology‐based interactions. We examine 7 traditional and emerging research methods that may jointly contribute to a better understanding of outcomes in megaclasses and Massive Open Online Classes and discuss their implications.

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“…The course culminated in a final project where students brought together all the tools they had learned to analyze a dataset of their choosing. This project acted as a kind of capstone, along the lines discussed in [24]. I will discuss how I assessed the efficacy of my approach towards achieving the desired student learning outcomes in Section 5.…”

Section: Introductionmentioning

confidence: 99%

A Project-Based Approach to Statistics and Data Science

White¹

2019

PRIMUS

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In an increasingly data-driven world, facility with statistics is more important than ever for our students. At institutions without a statistician, it often falls to the mathematics faculty to teach statistics courses. This paper presents a model that a mathematician asked to teach statistics can follow. This model entails connecting with faculty from numerous departments on campus to develop a list of topics, building a repository of real-world datasets from these faculty, and creating projects where students interface with these datasets to write lab reports aimed at consumers of statistics in other disciplines. The end result is students who are well prepared for interdisciplinary research, who are accustomed to coping with the idiosyncrasies of real data, and who have sharpened their technical writing and speaking skills.

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A Capstone Course for Undergraduate Statistics Majors

Cited by 19 publications

References 5 publications

Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward

Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward

The megaclass as a service production system and the challenge of facilitating its continuous quality improvement: Towards a research agenda in a complex domain

A Project-Based Approach to Statistics and Data Science

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