Michael D. Swartz, PhD – Department of Biostatistics and Data Science at the University of Texas Health Science Center at Houston
Friday, June 11, 2021 - 2:00pm
The idea of developing a rubric for assessments or flipping lectures in an Applied Biostatistics (or even Applied Statistics) classroom can be overwhelming, but it does not have to be. I will lead a discussion introducing several ideas for building a rubric for statistics assignments and exams, and flipping parts of a lecture to combine traditional lecture with interactive components to fully engage students to enhance their learning in the classroom or live synchronous sessions (like teaching through Webex or Zoom) using polling software like PollEverywhere. The polling software strategy I introduce will also provide instructors real-time feedback regarding students’ current comprehension of the material. One of the techniques can also be modified to increase engagement for an online only format (pre-recorded lectures). Attendees who consider themselves beginners with respect to rubrics or flipped classrooms as well as those who consider themselves more experienced are welcome to this webinar.
Subha Nair (HHMSPB NSS College for Women); Satheesh Kumar (University of Kerala); Asha Gopalakrishnan (Cochin University of Science and Technology); Mousumi Banerjee (UMICH); Kevin Wilson (Newcastle University); Sahir Bhatnagar (McGill University)
Tuesday, March 30, 2021 - 10:00am
A new form of pedagogical approach was thrust upon us by the pandemic – online classrooms; a concept that was never experienced or experimented to the extent that was witnessed in the past few months. The challenges involved in online teaching are many, especially for a discipline like statistics which is essential for students undergoing courses in science, health science as well as social sciences. The challenges can be anything, including difficulty in comprehending foundational concepts through virtual classrooms, lack of availability of technical tools such as electronic gadgets or internet coverage, lack of online teaching tools and resources, absence of appropriate technical knowhow which can hinder the ease of communication between the facilitators and students, and lack of appropriate evaluation of student performances. The extent of these challenges may vary from region to region and would depend upon socio-economic profiles of the places. However, the global academic fraternity in the statistics community is committed to effective dissemination of statistics content and knowledge to students from multiple disciplines amid these changed circumstances. In such a scenario, it will be both important as well as informative to have a platform for experience sharing of experts from around the world. This will not only help us exchange information regarding multiple academic approaches and evaluation aids successfully implemented by the statistics fraternity, but also provide significant insights into the availability of shared resources and identify what worked well in different geographical regions.
Douglas Landsittel (University of Pittsburgh)
Thursday, November 12, 2020 - 2:00pm
Many areas of clinical research, such as comparative effectiveness research and patient-centered outcomes research, strongly depend on making causal inferences from observational data. Further, these topic areas also utilize pragmatic trials and quasi-experimental designs, where consistent estimation of causal effects is also more challenging than traditional randomized controlled trials, and/or involves distinct approaches for intention-to-treat versus as-treated or per-protocol effects. While substantial literature exists on associated designs and analysis strategy, the corresponding methods are complex and not always taught in formal training, even within graduate statistics or biostatistics programs. Therefore, a critical need exists for accessible educational resources and the expansion of relevant courses and training programs. Regarding that goal, however, significant debate exists on whether these advanced methods should even be taught at all to non-statisticians, and/or researchers with more limited statistical training (e.g. a fundamental course and some background in regression). This talk proposes some possible perspectives to effectively address these concerns, while still avoiding the result of "knowing enough to be dangerous". The presenter has some related links at www.landsittellab.pitt.edu. This work was supported by AHRQ grant R25HS023185, PCORI contract R-IMC-1306-03827, and supplemental funding from the NIH/NLM grant 5 T15 LM007059-32.
Amy Nowacki (Cleveland Clinic) & Carol Bigelow (University of Massachusetts)
Wednesday, July 29, 2020 - 1:00pm
The TSHS Resources Portal (www.causeweb.org/tshs) contains datasets from 13 real health sciences research studies. Each dataset is accompanied by a study description and a data dictionary. Most are linked to a published paper as well. These datasets, plus some extra teaching tools, are peer reviewed and ready for use with your learners. In this webinar, Amy and Carol will walk through what is available and how to get the most out of this resource.
Ann Brearley, PhD (University of Minnesota)
Thursday, April 23, 2020 - 2:00pm
Over the past 10 years we have adopted a variety of new teaching methods to make both our in-person and our online introductory biostatistics courses more active, relevant and effective. These include the flipped classroom approach, active learning, collaborative answer keys, and group projects using “The Islands”. The virtual world of The Islands, created by Michael Bulmer at the University of Queensland, allows students to actually do research (and statistics) from start to finish by designing, executing, analyzing and reporting the results of a “real” study on virtual people. We have collaborated with Dr. Bulmer to add features to The Islands (such as clinics and hospitals) to facilitate health-related research studies, both experimental and observational. Carrying out an Island study provides students with sometimes painful but nevertheless invaluable experience in many aspects of research, including study design, data collection, teamwork, data analysis, and communicating research results to others. This webinar will describe The Islands and how we use them for student projects and will discuss the benefits and challenges of these projects, both for students and for instructors.
Thomas M. Braun, PhD (University of Michigan)
Thursday, January 30, 2020 - 2:00pm
The idea of a "flipped classroom" has been integrated for two years into the introductory biostatistics course required of all Masters of Public Health (MPH) students at the University of Michigan. The course was divided into eight modules, with each module consisting of one or more video lectures and three modes of assessment: a quiz and two in-class projects. The in-class projects consisted of (1) data analysis of contemporary public health data sets using Excel and (2) review of statistical methods and results in manuscripts published recently in the American Journal of Public Health. This talk will review my experiences with the development of the course, with the implementation of the course, and student input received from anonymous end-of-semester evaluations.
Please use the following form to register: https://redcap.hfhs.org/redcap/surveys/?s=4WH8JJ9KYH. The webinar link will be sent to you ahead of the session, and a link to the webinar recording will be sent to you about a week after the session.
Adam Sullivan (Brown University)
Thursday, May 30, 2019 - 2:00pm
Flipped classrooms have appeared in all levels of education. One of the major benefits is that the passive learning (lecture) is completed at home and the active learning (activities and problem solving) are done in class with the instructor. However, the issues with flipped classrooms are the cost to make high quality video content and the time. Due to the cost and time many classes are created and then not updated. This talk will discuss common ways for creating and updating flipped classrooms, considering a case study of PHP 2560: Statistical Programming in R at Brown University. We will discuss the first flipped version of this course, in terms of content and creation time. Then we will discuss how subsequent iterations have been adapted and updated to maintain relevance.