Browsing by Author "Wu, Leanne"

Now showing 1 - 6 of 6
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    Demographically Diverse Anthropographics: Exploring Equitable Visual Representations of Diversity
    (2023-07) Dhawka, Priyadarshinee; Willett, Wesley; Wu, Leanne; Messier, Geoffrey; Henry, Ryan
    In this thesis, we explore the design of demographically diverse anthropographics from demographic data. Anthropographics are visualizations that often use generic human-shaped symbols as abstract representations of humans. These visualizations are frequently used to convey the human importance of data related to people’s experiences, usually focusing on demographic data such as age, gender, race among others. However, most current anthropographics employ generic human shapes to represent data about distinct demographic groups, which can hide important demographic and physical differences between these groups. The use of generic human shapes in current anthropographics highlights the lack of inclusive approaches for representing human physical diversity in data visualizations. In response,we explore the creation of demographically diverse anthropographics that communicate the visible physical diversity of demographically-distinct populations. Our contributions stem from a set of critical design explorations for visualizing demographic data with a focus on representing human physical diversity and a study exploring how viewers perceive visual representations of diversity in anthropographics. We make three contributions in this work. First, we describe critical design explorations from two prototypes for representing racial demographic data as physical characteristics of diversity (such as skin tones) in diverse anthropographics. Second, we explore how viewers may perceive visual representations of demographic diversity in anthropographics through an interview study on contemporary examples of homogeneous anthropographics from popular news media and our own set of diverse anthropographics. Finally, we identify a set of social and technical challenges in the creation of anthropographics and contribute a collection of forward-looking opportunities for advancing this line of research on equitable visual representations of diversity through demographically diverse anthropographics.
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    Earn your Shakespeare Badge
    (2015-05-12) Ullyot, Michael; Kenney, Theresa; Wu, Leanne; Beaulieu, Braydon
    There are multiple outlets for students’ creative and critical engagement in our introductory course on Shakespeare, each linked to an explicit learning outcome: annotating texts, live-tweeting classes, reviewing performances, blogging sonnets. Like others at our institution (Kim: 2014), we are implementing a micro-credentialling system of digital badges to reward this engagement. Our goal is to gamify participation with a system of recognition that would be responsive to student initiative. We give students multiple options under each of our ten badges. For instance, the Genres and Modes Badge invites them to signify genres by designing movie posters; or to capture the arbitrariness of outcomes through a text-adventure video game. (“If Romeo commits suicide, click here; if he hesitates long enough for Juliet to wake up, click here.”) Digital badges recognize students’ skills that extend beyond a particular course into new environments: analyzing texts is a skill for other courses, and for the workplace (Alliance: 2013). They also recognize peer achievement and build a class community (Ferdig and Pytash: 2014).
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    Exploring Context for Privacy Protection in North American Higher Education and Beyond
    (2020-01) Wu, Leanne; Barker, Ken E.; Denzinger, Jörg; Oehlberg, Lora A.; Lock, Jennifer V.; Veletsianos, George
    Undergraduate students in North American post-secondary institutions are subject to a wide range of data collection. It includes data generated in the course of teaching and learning, but also can include a wide range of other aspects of modern life, such as closed-circuit security cameras, internet and wireless network use, and what students buy and consume. This makes the post-secondary institution an ideal model for understanding the privacy impact of modern and future technologies, as a single organization which collects and potentially uses wide-ranging amounts and kinds of data about our daily lives. This thesis proposes a framework which separates context into three interrelated layers so that systems can be designed which more fully protect the privacy of individuals, examines the ways in which we collect and use data about undergraduate students, and makes a quantitative study of undergraduate privacy behaviours and attitudes. Thus we present the case that context is a core concept for privacy protections which better protect undergraduate students and their privacy.
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    Iterative Open Area Detection in Feature Spaces Using World Constraints
    (2024-07-03) Douglas, Nathan Josiah; Denzinger, Joerg; Jacob, Christian; Wu, Leanne
    Improving data quality is a very valuable step of any data-driven process. One method of evaluating data quality that is understudied is the detection of Open Areas. An Open Area indicates a discrepancy between what information exists in a dataset, and what information should exist in that dataset as determined by world constraints (i.e. constraints informed by the dataset’s domain). We propose the Iterative Open Area Detection (IOAD) approach as a method to detect these problematic areas. IOAD is an iterative process which successively finds Open Areas in a worst-first fashion. Each iterative step first searches the feature space for the least represented point, and then finds the largest surrounding area such that the entire sphere does not meet some criteria for reasonable representation. We evaluate this approach on a variation of an existing dataset which we extend to ensure compatibility with the relevant world constraints, and also on a series of synthetic datasets of varying dimensionality. First, we show that the areas we find are both interesting and appropriate by analyzing both the candidate points and the surrounding areas in the context of the world constraints. Then, to further validate the areas reported by IOAD we artificially introduce Open Areas by removing some cluster of points, and then measure the number of iterations needed to detect the removed area. Our results show that our approach is always successful, but the efficiency may be bound by the Curse of Dimensionality.
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    Privacy-based retention
    (2010) Wu, Leanne; Barker, Kenneth E.
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    Teaching Assistant in Residence: A Novel Peer Mentorship Program for Less Experienced Teaching Assistants
    (2015-05-12) Stephenson, Ben; Wu, Leanne; Kendon, Tyson
    Each semester approximately 80 graduate teaching assistants (TAs) support the delivery of the undergraduate computer science program at The University of Calgary. While these teaching assistants provide an essential service to the undergraduate program, in past years the department has invested little effort in ensuring that teaching assistants have the opportunity to develop the skills necessary to tackle these duties effectively. During the 2012-2013 academic year, a novel TA mentorship program was initiated. An experienced teaching assistant with a demonstrated record of excellence in teaching was hired to serve as the TA in Residence. This graduate student provided training and advice to new teaching assistants, including classroom visits where the TA in Residence observed TAs in action. TAs that participated in the program generally reported that the advice provided by the TA in Residence was helpful, and all of the TAs that responded to the survey question believed that it would be worthwhile to continue the mentorship program in the future. As a result, we continued the TA in Residence program in subsequent years. This poster provides an overview of the TA in Residence program, its benefits, and the challenges that the TAs in residence have faced and overcome. The revisions that we have made to the program since its inception are also described, which will allow other departments interested in developing a TA in Residence program to avoid some of the pitfalls that we initially encountered.