Presentations

Breaking down classroom walls and setting learning free, at Lecture Breakers Virtual Summer Conference, Tuesday, June 4, 2024

The rapid transition to online teaching necessitated by the coronavirus pandemic has been a good opportunity to rethink my approach to teaching. Moving online laid bare the restrictions imposed by both traditional classrooms and online teaching, and demonstrated that many activities that have traditionally been synchronous and instructor-paced, can be improved by making them asynchronous and self-paced in any teaching modality. What may have...

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Designing questions for student-centered learning (I), at AMISA 2024 Educators' Conference, American School of Asuncion, Asuncion, Paraguay, Thursday, March 21, 2024

Questions are the heart of evaluating and engaging students. In this workshop, we will work individually and in pairs on a case study to learn best practices for developing effective questions.

After participating in this workshop, participants will be able to
  • Evaluate questions and classify them according the levels of Bloom’s taxonomy
  • Revise questions to increase the level of Bloom’s taxonomy at which they engage students
  • Develop questions that more effectively engage students in a flipped-learning environment
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Student-centered learning with Perusall, at AMISA 2024 Educators' Conference, American School of Asuncion, Asuncion, Paraguay, Wednesday, March 20, 2024

Learning is a social experience — it requires interactivity. Most students learn best by engaging with content, reflecting on it, and engaging with their peers. Moving pre-class reading assignments to an asynchronous and self-paced environment improves completion rates of these assignments. Perusall, a free social learning platform, permits one to move online the information-transfer that normally takes place in a lecture and make this information transfer interactive. In addition, the platform promotes intrinsic and extrinsic motivation to learn. In this workshop we will demonstrate the...

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Anton Strezhnev presents "A Guide to Dynamic Difference-in-Differences Regressions for Political Scientists" Wednesday, March 20, 2024

Abstract: Difference-in-differences (DiD) designs for estimating causal effects have grown in popularity throughout political science. Many DiD papers present their central results through an "event study" plot - a visualization that combines estimated dynamic average treatment effects for multiple post-treatment time periods alongside placebo tests of the main identifying assumption: parallel trends. Despite their ubiquity, the methods used in practice for the creation of these plots are not standardized and in many cases the approaches adopted by researchers can result in misleading...

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Innovating education to educate innovators, at AMISA 2024 Educators' Conference, American School of Asuncion, Asuncion, Paraguay, Wednesday, March 20, 2024
Can we teach innovation? Innovation requires whole-brain thinking — right-brain thinking for creativity and imagination, and left-brain thinking for planning and execution. Our current approach to education in science and technology, focuses on the transfer of information, developing mostly right-brain thinking by stressing copying and reproducing existing ideas rather than generating new ones. I will show how shifting the focus in lectures from delivering information to team work and creative thinking greatly improves the learning that takes place in the classroom and help develop problem-... Read more about Innovating education to educate innovators
Connecting the dots and setting learning free, at 14th Reinventing Higher Education Conference, University of Miami, Miami, FL, Thursday, March 7, 2024:
In my journey as educator, I have been connecting dots for several decades in response to various disruptions. Reflecting back on this journey, I realize the learning environment I have created in the last few years, is a world apart from the way I started my teaching career. Some of the keypoints that have emerged are the importance of pedagogy and assessment (not technology), the importance of optimizing the valuable face-to-face time we have with students, and the need to reimagine our learning spaces.
Amanda Coston presents "Addressing confounding in decision-making algorithms." Wednesday, March 6, 2024
Abstract: 

Machine learning algorithms are used for decision-making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. These algorithms are often intended to predict outcomes under a proposed decision. It is challenging to evaluate how well these algorithms perform because we only observe the relevant outcome under a biased sample of the population. In this talk, we explore how to use techniques from causal inference to estimate performance on the full population. We will consider several strategies to account for...

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Phillip Heiler presents "Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization" Wednesday, February 28, 2024

Abstract: We propose a method for estimation and inference for bounds for heterogeneous causal effect parameters in general sample selection models where the treatment can affect whether an outcome is observed and no exclusion restrictions are available. The method provides conditional effect bounds as functions of policy relevant pre-treatment variables. It allows for conducting valid statistical inference on the unidentified conditional effects. We use a flexible debiased/double machine learning approach that can accommodate non-linear functional forms and high-dimensional confounders...

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Ross Mattheis presents "Spurious Mobility in Imperfectly Linked Data Trials" (joint with Jiafeng Chen). Wednesday, February 21, 2024

Abstract: Estimating intergenerational mobility often requires linking data across multiple sources. However, mistakes in record linkage can introduce biases in subsequent estimates. This paper re-examines the history of intergenerational mobility in the United States with emphasis on bias from  imperfectly linked data. In particular, data corrupted by incorrect links will typically attenuate estimates of linear estimands towards zero. When the estimand is the intergenerational elasticity of status, this bias will tend to exaggerate levels of mobility. We propose two...

Read more about Ross Mattheis presents "Spurious Mobility in Imperfectly Linked Data Trials" (joint with Jiafeng Chen).

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