CAUSE October 2022

cause@causeweb.org

7 participants
11 discussions

USCOTS 2023: Call for Proposals

by Taylor, Kati

The U.S. Conference on Teaching Statistics (USCOTS)<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…> will be held at the Penn Stater in State College, PA from Thursday, June 1st through Saturday June 3rd, 2023, with pre-conference workshops starting on Tuesday, May 30th. This conference provides a welcoming and engaging (perhaps even fun!) environment in which teachers can exchange ideas and motivate each other to improve their teaching of statistics. The conference features thought-provoking plenary sessions, interactive breakout sessions, informative posters-and-beyond sessions, and opening and closing sessions with inspiring and lively five-minute presentations. Other highlights include birds-of-a-feather discussions, a speed mentoring session, an awards ceremony, extensive pre-conference workshops, and exhibitor technology demonstrations. The USCOTS theme for 2023 is "Communicating with/about Data." Sessions will explore many aspects of this theme, including teaching students to present data-driven arguments through words, visualizations, and even code, and helping teachers effectively communicate with their students as they develop their understanding of key statistical ideas. USCOTS has been held in odd-numbered years since 2005. While USCOTS 2021 was held virtually due to COVID-19, all sessions of USCOTS 2023 will be held in–person. Please consider attending and even better, consider submitting a proposal<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…> for an interactive breakout session, pre-conference workshop, “posters and beyond” contribution, or “birds of a feather” discussion topic. Deadlines are: · November 30th, 2022 for proposing a pre-conference workshop · November 30th, 2022 for proposing an interactive breakout session · January 29th, 2023 for proposing a “posters and beyond” contribution, if you would like to receive formative feedback before your final submission · March 5th, 2023 for final submission of proposals for a “posters and beyond” contribution, whether or not you submitted a version earlier for feedback · May 6th, 2023 for proposing a “birds of a feather” discussion USCOTS 2023 will also feature a Research Satellite, to be held on May 31st and June 1st, that brings together researchers in statistics and data science education to promote and support projects of common interest. You can find more information about the conference and its theme, along with proposal submission links, here: https://www.CAUSEweb.org/cause/uscots/uscots23<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…> https://www.causeweb.org/cause/uscots/uscots23/about<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…> https://www.CAUSEweb.org/cause/uscots/uscots23/proposals<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…> Please address questions to program co-chairs Allan Rossman (arossman(a)calpoly.edu<mailto:arossman@calpoly.edu>) or Kelly McConville (kmcconville(a)fas.harvard.edu<mailto:kmcconville@fas.harvard.edu>), or to CAUSE director Dennis Pearl (dkp13(a)psu.edu<mailto:dkp13@psu.edu>).

1 year

eUSR Registration Final Reminder

by Taylor, Kati

A friendly reminder that registration for the Electronic Undergraduate Statistics Research Conference (https://www.causeweb.org/usproc/eusr/2022<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…>) is still open! The conference is free, and it will take place on Friday, November 4th. The conference is open to all students and faculty to attend. The keynote speaker is Susan Paddock (https://www.norc.org/Experts/Pages/susan-paddock.aspx<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.norc.…>). There will be sessions on statistics careers and graduate school. Winners of the Undergraduate Statistics Project Competition (https://www.causeweb.org/usproc<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…>) will give plenary talks. This email includes a poster as an attachment. You can feel free to use an electronic or print version of this poster to publicize the conference to your students. If you have any questions about eUSR, send an email to jihu(a)vassar.edu<mailto:jihu@vassar.edu>. We hope to see you there! Best, Co-Chairs of USPROC + eUSR Mine Dogucu (University College London and UC Irvine) Juanjuan Fan (San Diego State University) Jingchen Monika Hu (Vassar College) Maria Tackett (Duke University) Jennifer Ward (Clark College)

1 year, 1 month

Oct. 19th Cause Reading Group

by Mocko,Megan E

Dear all, CAUSE Research Reading Group meetings continue! Our next meeting is scheduled next Wednesday, October 19th, at 12:00-1:00pm ET. Please find the link for registration and the link to the article below. R. Gould, A. Bargagliotti, and T. Johnson, An analysis of secondary teachers' reasoning with participatory sensing data, Stat. Educ. Res. J. 16(2) (2017), 305-334 https://iase-web.org/ojs/SERJ/article/view/194Zoom: Register in advance for this meeting: https://ufl.zoom.us/meeting/register/tJwqduqqrTsqGNeF1niXmULW1_usC5oD4iUs After registering, you will receive a confirmation email containing information about joining the meeting. Our host for this session will be Valmiki Rama Krishna (thank you so much, Valmiki!).Look forward to having you join us next Wednesday, Megan & Shu-Min Megan Mocko (she/her/hers) Lecturer Information Systems and Operations Management WARRINGTON COLLEGE OF BUSINESS UNIVERSITY OF FLORIDA ____________________________ 352-392-9731 Megan.Mocko(a)warrington.ufl.edu<mailto:Megan.Mocko@warrington.ufl.edu> Stuzin Hall 351B PO Box 117169, Gainesville, FL 32611 WARRINGTON.ufl.edu [cid:image005.jpg@01D3D18E.A16AD250]

1 year, 1 month

STAT Faculty Positions at Illinois

by Findley, Kelly Patrick

The Department of Statistics at the University of Illinois--Urbana-Champaign invites applications for multiple specialized faculty positions (100% for 9 months) that support our growing statistics, statistics & computer science, and data science programs on campus. All areas of teaching expertise will be considered, but areas of priority include: * Introductory statistics * Machine learning * Data and software engineering * Statistical applications involving big data The department will consider applications for the following positions: Teaching Assistant Professor, Clinical Assistant Professor, Visiting Assistant Professor, Lecturer, and Instructor. * Teaching Assistant Professors teach 4 courses per year (typically 2 in fall and 2 in spring) while also contributing research and service in the areas of curriculum and instruction. * Clinical Assistant Professors teach 4 courses per year (typically 2 in fall and 2 in spring) while also contributing research and service that reflect their domain expertise. * Visiting Assistant Professors teach 3 courses per year while also maintaining a strong research program. * Lecturers teach 6 courses per year (typically 3 in fall and 3 in spring). * Instructors teach 6 courses per year (typically 3 in fall and 3 in spring). These are career-oriented positions with clear tracks for promotion and professional development. Visiting positions may be renewed for a maximum of 3 years. Applicants for Instructor must have a Master's degree by time of appointment, and applicants for Lecturer and Teaching/Clinical Assistant Professor must have a PhD by the time of appointment. These degrees should be in statistics or a related field (e.g., biostatistics, computer science, data science, engineering, math education, operations research). Candidates should have experience or demonstrate ability to teach effectively at the undergraduate level, and potentially at the graduate level. The anticipated starting date is January 1, 2023 or August 16, 2023. Salary is competitive. Review of applications will begin on November 1st, but the department may consider new applications after this date as well. For more information on how to apply, check out the announcement on our website: https://stat.illinois.edu/news/2022-09-28/department-statistics-seeks-appli… Kelly Findley Ph.D. Teaching Assistant Professor 703 S. Wright St., Office 23 Department of Statistics | The University of Illinois -- Urbana-Champaign

1 year, 1 month

CAUSE/JSDSE webinar (10/18/22): SCRATCH to R: Toward an Inclusive Pedagogy in Teaching Coding

by Taylor, Kati

This month, in the CAUSE (Consortium for the Advancement of Undergraduate Statistics Education) / JSDSE (Journal of Statistics and Data Science Education) webinar series, we highlight the research article, SCRATCH to R: Toward an Inclusive Pedagogy in Teaching Coding. In the webinar, Shu-Min Liao will introduce SCRATCH, a kid-friendly visual programming language developed by the Media Lab at MIT. SCRATCH was designed to introduce programming to children and teens in a “more thinkable, more meaningful, and more social” way. Although it was initially intended for K-12 students, educators have used it for higher education as well, and found it particularly helpful for those who haven’t had the privilege of learning coding before college. In this presentation, Dr. Liao will discuss using SCRATCH as a gateway to learning R in introductory or intermediate statistics courses. She will explain the design of her current project and share observations from a pilot study in a liberal arts college with 39 students who had diverse coding experiences. She found that the most disadvantaged students were not those with no coding experience, but those with poor prior coding experience or with low coding self-efficacy. This innovative SCRATCH-to-R approach also offers instructors a pathway toward an inclusive pedagogy in teaching coding. Article Link https: https://www.tandfonline.com/doi/full/10.1080/26939169.2022.2090467<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.tandf…> Presented By: Shu-Min Liao (Amherst College) Short bios: Shu-Min Liao is an Assistant Professor of Statistics at Amherst College. Her research interests include fully nonparametric theory and methodology, model-free multivariate dependence measures for categorical data, and STEM education research focused on DEIA (Diversity, Equity, Inclusion, and Accessibility) topics. The webinar will take place on October 18th, from 4:00-4:30 pm EDT. Registration is required but is free. Registration link is here: https://www.causeweb.org/cause/webinar/jsdse/2022-10<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cause…> We hope that you can join us. Sincerely, Leigh Johnson (Capital University) Moderator, CAUSE/JSDSE Webinar Series

1 year, 1 month

CAUSE Research Reading Group meeting on September 21

by Shu-Min Liao

Dear all, CAUSE Research Reading Group meetings continue! Our next meeting is scheduled next *Wednesday, September 21*, at *12:00-1:00pm ET*. Please find the link for registration and the link to the article below. *Article: **Wickham (2014): "Tidy Data", Journal of Statistical Software, 59(1): 1-23.* https://www.jstatsoft.org/article/view/v059i10 Zoom: Register in advance for this meeting: https://amherstcollege.zoom.us/meeting/register/tJwqdO2rpz8rHtE9I4vc-nC5G6g… After registering, you will receive a confirmation email containing information about joining the meeting. Our host for this session will be Tyler George (thank you so much, Tyler!). We are still looking for interested volunteers to host our sessions on October 6, October 19, and November 3. Please consider hosting one of those sessions and you can find our complete schedule in Fall 2022 via this link <https://docs.google.com/document/d/1JgQWdNAdRMsdVEHfpiAdppiWmaRFZul2NEUPO4h…>. Look forward to having you join us next Wednesday, Shu-Min

1 year, 2 months

CAUSE/JSDSE webinar (10/18/22): SCRATCH to R: Toward an Inclusive Pedagogy in Teaching Coding

by Taylor, Kati

This month, in the CAUSE (Consortium for the Advancement of Undergraduate Statistics Education) / JSDSE (Journal of Statistics and Data Science Education) webinar series, we highlight the research article, SCRATCH to R: Toward an Inclusive Pedagogy in Teaching Coding. In the webinar, Shu-Min Liao will introduce SCRATCH, a kid-friendly visual programming language developed by the Media Lab at MIT. SCRATCH was designed to introduce programming to children and teens in a “more thinkable, more meaningful, and more social” way. Although it was initially intended for K-12 students, educators have used it for higher education as well, and found it particularly helpful for those who haven’t had the privilege of learning coding before college. In this presentation, Dr. Liao will discuss using SCRATCH as a gateway to learning R in introductory or intermediate statistics courses. She will explain the design of her current project and share observations from a pilot study in a liberal arts college with 39 students who had diverse coding experiences. She found that the most disadvantaged students were not those with no coding experience, but those with poor prior coding experience or with low coding self-efficacy. This innovative SCRATCH-to-R approach also offers instructors a pathway toward an inclusive pedagogy in teaching coding. Article Link https: https://www.tandfonline.com/doi/full/10.1080/26939169.2022.2090467<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.tandf…> Presented By: Shu-Min Liao (Amherst College) Short bios: Shu-Min Liao is an Assistant Professor of Statistics at Amherst College. Her research interests include fully nonparametric theory and methodology, model-free multivariate dependence measures for categorical data, and STEM education research focused on DEIA (Diversity, Equity, Inclusion, and Accessibility) topics. The webinar will take place on October 18th, from 4:00-4:30 pm EDT. Registration is required but is free. https://www.causeweb.org/cause/webinar/jsdse/2022-10 We hope that you can join us. Sincerely, Leigh Johnson (Capital University) Moderator, CAUSE/JSDSE Webinar Series

1 year, 2 months

October caption contest correction

by Taylor, Kati

For those who find it difficult to travel backwards in time, entries in the October CAUSE cartoon caption contest are due by October 31 (not September 30).

1 year, 2 months

The CAUSE Cartoon Caption Contest for October is now taking entries!

by Taylor, Kati

The Consortium for the Advancement of Undergraduate Statistics Education is happy to announce our 77th Cartoon Caption Contest! Each month a cartoon, drawn by British cartoonist John Landers, is posted for you and your students to suggest statistical captions (cartoons are posted at the beginning of the month and submissions are due at the end of the month).   The caption contest is offered as a fun way to get your students thinking independently about statistical concepts. The next cartoon and the entry rules for the contest ending September 30 are at   https://www.causeweb.org/cause/caption-contest/october/2022/submissions The best submission will be posted on CAUSEweb and the winner(s) will receive their choice of a coffee mug or t-shirt imprinted with the final cartoon. Enjoy. [cid:bfa55d8f-a2d2-4d06-87a7-c4dde5b310f4] September Results:   The September caption contest cartoon is shown here. The judges found the winning caption to be “Ga-ga in ga-ga out," written by Jonathan Boucher, a student at Colorado University in Boulder. Jonathan’s caption can be a vehicle to discuss the old GIGO adage (Garbage In Garbage Out) indicating how poor data may well produce poor results. An honorable mention this month goes to Jim Alloway from EMSQ Associates for his caption, “It’s not a valid survey if your participants don’t understand the questions.” Jim’s caption aligns well with teaching about response errors such as when subjects misunderstand a question and how that may bias survey results. Thanks to everyone who submitted a caption and congratulations to our winners! If you’d like to try your hand at creating your own statistics cartoon or song or video or poem, or other fun item, you should enter CAUSE’s A-mu-sing contest (see https://www.causeweb.org/cause/a-mu-sing/2023/rules).

1 year, 2 months

Recruiting instructors and students for statistics and data science attitude research

by Douglas Whitaker

DO YOU TEACH STATISTICS OR DATA SCIENCE? ARE YOU WILLING TO PARTICIPATE IN RESEARCH TO UNDERSTAND THE IMPORTANCE OF ATTITUDES IN THESE DISCIPLINES? THEN READ ON... Dear Colleague, Folks on this list are invested in their students, so might be interested in this opportunity. We invite you to join us as we study the role that attitudes play in the learning process. We are working on a project<https://www.nsf.gov/awardsearch/showAward?AWD_ID=2013392&HistoricalAwards=f…> funded by the National Science Foundation (DUE-2013392) to develop validated instruments measuring student and instructor attitudes toward statistics and data science. We refer to this project as MASDER (Motivational Attitudes in Statistics and Data Science Education Research).These instruments will allow us to measure attitudes toward statistics or data science, which will create useful evidence in determining best-practices and impacts of interventions or teaching differences. We hope you will participate in this important work. There are a number of ways you could get involved this fall: * Do you TEACH STATISTICS at the introductory level? There are two ways to participate: o Participate in our INSTRUCTOR FOCUS GROUP<https://forms.gle/1JXrmc4WFA8z6J8o7>! We are offering $30 gift cards to participants in one of the Zoom sessions in early October. o Share YOUR attitudes<https://bit.ly/I-SOMAS> toward statistics via our pilot instructor attitudes instrument This should take about 15 minutes. (If you have already taken this survey, you do not need to take it again.) * Do you TEACH DATA SCIENCE at the introductory level? There are two ways to participate: o Sign-up<https://bit.ly/S-SOMADS> to administer our pilot student attitudes instrument to students in your data science course! o WHAT IS DATA SCIENCE? We won't try to answer this question for you, but we want to know what you teach in your introductory data science class. Please fill out our Introductory Data Science Topics Survey<https://bit.ly/DS_Topics>! This should only take about 15 minutes. Feel free to share these opportunities with other colleagues who teach statistics and data science. We all know the value of data! Please let us know if you have any questions. Thank you in advance for your help! Alana Unfried (PI), California State University - Monterey Bay (aunfried(a)csumb.edu<mailto:aunfried@csumb.edu>) Marjorie Bond, Penn State University April Kerby-Helm, Winona State University Michael Posner, Villanova University Douglas Whitaker, Mount Saint Vincent University Leyla Batakci, Elizabethtown College P.S. If you would like more detailed information about the project, keep reading: This project has been approved by our Institutional Review Board (IRB). The IRB has also set forth some guidelines that we must follow in conducting this research, which we describe herein. Please note that due to our IRB approval and scope of grant, we are only recruiting courses taught in the United States. The student survey should be assigned either for class credit or for extra credit in order to increase the response rates. We will share with you a list of students who completed the consent form, but we are unable to reveal additional student information or survey responses. Your involvement in this project improves the quality of the final survey which we will develop. Amalgamated, de-identified survey data will be publicly available at the end of the grant period, as well as additional material. If you would like to connect with your IRB before administering the survey, you may provide them with this folder<https://drive.google.com/drive/folders/1V4o0R0du_vPt6ZPWx8tlZx1HNcLp-Sd0?us…> that includes information they might need to determine your eligibility to administer the survey.

1 year, 2 months

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CAUSE October 2022