Statistical Education in the 21<sup>st</sup> Century: A Review of Challenges, Teaching Innovations and Strategies for Reform

Tishkovskaya, Svetlana; Lancaster, Gillian

doi:10.1080/10691898.2012.11889641

Cited by 159 publications

(150 citation statements)

References 70 publications

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“…Flipped and blended classrooms have been associated with some documented benefits over traditional and online approaches, such as higher grades, more evidence of learning, greater motivation and engagement, stronger sense of community, better attitudes, more opportunities to integrate active learning methods, and more frequent classroom attendance (Rovai and Jordan 2004;Babb, Stewart, and Johnson 2010;Deslauriers, Schelew, and Weiman 2011;Pearl et al 2012;Tishkovskaya and Lancaster 2012;McLaughlin et al 2014). Flipped classes may also include superior "external connections with the material by reference to a variety of experiences and perspectives," and opportunities for both stronger and weaker students to strengthen their skills and knowledge (Giraud 1997, p. 2).…”

Section: Research Comparing Course Delivery Methodsmentioning

confidence: 99%

“…However, previous researchers note that there is a shortage of high-quality, standardized assessments for measuring statistical literacy (Garfield and Gal 1999;Watson 1997;Gal 2002;Pearl et al 2012;Tishkovskaya and Lancaster 2012), possibly because low-level statistical literacy classes are not as common as the typical introductory statistics courses, which also emphasize data analysis.…”

Section: Statistical Reasoningmentioning

confidence: 99%

“…Unfortunately, statistics courses do not always have a positive reputation among students who are not majoring in science, technology, engineering, and mathematics (STEM) disciplines. Non-STEM students often have a significant amount of anxiety related to statistics courses, which can negatively affect their performance (Baloglu 2003;Finney and Schraw 2003;Onwuegbuzie and Wilson 2003;Verhoeven 2006;Dempster and McCorry 2009;Vanhoof et al 2011;Tishkovskaya and Lancaster 2012). As statistics educators, we should be interested in the attitudes our students have about statistics as a field, statistics as a class, and their own confidence in their ability to learn statistics.…”

Section: Student Attitudes Toward Statisticsmentioning

confidence: 99%

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A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Web-Augmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class

Gundlach

Richards

Nelson

et al. 2015

Journal of Statistics Education

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Web-augmented traditional lecture, fully online, and flipped sections, all taught by the same instructor with the same course schedule, assignments, and exams in the same semester, were compared with regards to student attitudes; statistical reasoning; performance on common exams, homework, and projects; and perceptions of the course and instructor. The Survey of Attitudes Toward Statistics-36 (SATS-36) instrument and eight questions from the Statistical Reasoning Assessment (SRA) were given both at the beginning and end of the semester to measure change. The students selected their own sections, but the students in the sections were similar demographically, with similar pre-course college grade point averages. The SATS-36 showed increases in affect, cognitive competence, and perceived easiness and decreases in value, interest, and effort from beginning to end of the semester for all sections. Only affect and Journal of Statistics Education, Volume 23, Number 1 (2015) 2 perceived easiness showed any differences for section, with traditional higher than online on average for both. Results from the SRA questions showed an increase in correct statistical reasoning skills and decrease in misconceptions for all sections over the semester. Traditional students scored higher on average on all three exams, but there were no significant differences between sections on homework, the project, or on university evaluations of the course or instructor. Results are contextualized with prior educational research on course modalities, and proposals for future research are provided.

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Section: Research Comparing Course Delivery Methodsmentioning

confidence: 99%

Section: Statistical Reasoningmentioning

confidence: 99%

Section: Student Attitudes Toward Statisticsmentioning

confidence: 99%

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A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Web-Augmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class

Gundlach

Richards

Nelson

et al. 2015

Journal of Statistics Education

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“…There has been increased attention recently to teaching and learning aspects of statistics education (Tishkovskaya & Lancaster, 2012). Traditional education in statistics has focused on developing knowledge and skills whereby students learnt by absorbing information.…”

Section: 1traditional Theoriesmentioning

confidence: 99%

Adjusted Pedagogy for Teaching Statistics

Stojanovski

2017

Pijss

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“…In the statistical education literature, there is consensus that integrating software programming in statistics and probability courses is imperative [20] . However, the specific methodology to incorporate programming into a statistics course depends on the students' major and their level of prior exposure and engagement with programming software.…”

Section: Students' Programming Experiencementioning

confidence: 99%

Using Case Studies to Enhance the Critical Thinking Skills of IE Students

Alexandra

Cross

King

et al.

2016 ASEE Annual Conference &Amp; Exposition Proceedings

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The most challenging aspects of teaching probability and statistics to engineering students are the theoretical nature of the topic and the disconnection of the material taught with real-world engineering problems. Although the engineering curriculum in most cases has been updated and expanded to incorporate group work and project-based learning, most of the mathematical oriented courses are still taught in a passive manner.Our goal is to enhance students' critical thinking by integrating case studies to our introductory course in probability and statistics. This is typically a sophomore-level core course in the industrial engineering curriculum. Students who complete this course, should be able to understand the role of uncertainty in engineering models, apply critical probability concepts (e.g. independence, expectation, variance), identify and analyze discrete and continuous random variables, and formulate and conduct statistical analyses of observed data.One key innovation that we implemented is the introduction of real-world data-driven case studies. We wish to expose our students to engineering problems that will help them relate the material taught in class with their own major. The primary enabling technology is statistical programming with Python. The case studies are introduced as group assignments and are motivated in class or discussion sessions. Students select their own groups and in the end of each case study, they do a peer-evaluation in order to assess the degree of in-group collaboration. In this way, students build valuable competencies, such as problem solving, critical thinking, and collaboration. We have also updated the way the students are being evaluated; therefore, case studies are graded based on rubrics that clearly communicate our expectations to the students. Finally, to track the progress and evaluate the success of the above innovations, we have created an attitudes survey (beginning/end of the semester) and an informal early feedback survey (middle of the semester).

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Statistical Education in the 21^st Century: A Review of Challenges, Teaching Innovations and Strategies for Reform

Cited by 159 publications

References 70 publications

A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Web-Augmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class

A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Web-Augmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class

Adjusted Pedagogy for Teaching Statistics

Using Case Studies to Enhance the Critical Thinking Skills of IE Students

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Statistical Education in the 21st Century: A Review of Challenges, Teaching Innovations and Strategies for Reform

Cited by 159 publications

References 70 publications

A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Web-Augmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class

A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Web-Augmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class

Adjusted Pedagogy for Teaching Statistics

Using Case Studies to Enhance the Critical Thinking Skills of IE Students

Contact Info

Product

Resources

About

Statistical Education in the 21^st Century: A Review of Challenges, Teaching Innovations and Strategies for Reform