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Seminar: HCII Post Doctoral Fellows

4 Guest Speakers from the HCII
Post Doctoral Fellows


Seminar will be presented via Zoom

Video link


Cynthia Bennett

"The Care Work of Access"

ABSTRACT: Current approaches to AI and Assistive Technology (AT) often foreground task completion over other encounters such as expressions of care. Our paper challenges and complements such task-completion approaches by attending to the care work of access—the continual affective and emotional adjustments that people make by noticing and attending to one another. We explore how this work impacts encounters among people with and without vision impairments who complete tasks together. We find that bound up in attempts to get things done are concerns for one another and how well people are doing together. Reading this work through emerging disability studies and feminist STS scholarship, we account for two important forms of work that give rise to access: (1) mundane attunements and (2) non-innocent authorizations. Together these processes work as sensitizing concepts to help HCI scholars account for the ways that intelligent ATs both produce access while sometimes subverting people with disabilities.

BIO: Cynthia Bennett is a postdoctoral researcher at Carnegie Mellon University’s Human-Computer Interaction Institute and a researcher at Apple, Inc. Her research concerns the intersection of disability, design, and accessibility. She positions the lived experiences and creativity of people with disabilities as starting points for developing more accessible design and research methods and for designing new, accessible interactions with emerging technology. Her research has been funded by the National Science Foundation and Microsoft Research. She has published at top-tier ACM venues including CHI and the ASSETS Conference on Computers and Accessibility, and three of her ASSETS collaborations received best paper or best student paper awards. You can follow her on Twitter (@clb5590) and read more from her website at


Lu Lawrence

"Exploring the Design Process and Use of a Teacher Orchestration Tool"

ABSTRACT: Design-based research is an iterative, non-linear process used to collaboratively design and implement educational artifacts in authentic contexts (Wang & Hannfi, 2005; Ormel et al., 2012). Responding from calls from the field for researchers to disseminate this process, I will describe findings from a fine-grain analysis of a full design-based research iteration. I investigated how an interdisciplinary team designed a collaborative orchestration tool and analyzed how it was used in the classroom by engineering instructors. Using a traditional design method called linkography (Goldschmitd, 2014), I describe the design process and outline specific interactions that led to innovative ideas about the orchestration tool. Then, I will share conclusions from the classroom implementation to illustrate how real-time prompts supported instructors and how their differences influenced their engagement with the tool. This work broadens our understanding of how design-based research processes are enacted to explore this form of learning among researchers and align designs with classroom outcomes.

BIO: LuEttaMae Lawrence is a Postdoc Fellow at Carnegie Mellon at the Human-Computer Interaction Institute. She received her PhD in Curriculum and Instruction from the University of Illinois at Urbana-Champaign and her BFA in Graphic Design from Iowa State University. As a learning scientist and design researcher, Lu studies co-design processes to build educational technology and investigates how designs are embedded in authentic learning contexts. To do this work, she integrates methods from design, human-computer interaction, and education to understand how collaborative discourse and learning occur. Learn more on her website:

HOST: Vincent Aleven


Michael Mogessie

"Building Scalable Software Infrastructure for Educational Technology Research"

ABSTRACT: Developing educational technology requires robust technical knowledge and must be informed by best practices in software engineering. Software technologies have evolved at a much faster pace in the past decade together with significant advances in computing capabilities. This had led to the transition of some educational software developed in recent years into legacy systems. When it comes to academia and educational technology research in particular, I believe robustness, scalability and decoupling of software components has not been given the attention it deserves. In this seminar, I will talk about work that has been done to port legacy educational software to current standards and efforts to decouple front- and backend components of systems as we seek to leverage cloud computing infrastructures to continuously develop and deploy scalable and client-agnostic services.
BIO: Michael Mogessie is a postdoctoral fellow at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University. He received his PhD in Information Technology from the University of Trento, Italy in 2017, his MSc in Computer Science in 2012 from the same university and his BSc in Information Systems from Addis Ababa University in 2006. Before transitioning back to research in 2018, he worked as a software engineer where he used cutting edge technologies to develop software including human resource management and scheduling systems deployed across a wide variety of sectors in the healthcare, aviation, transportation, banking, food service and retail industries. His graduate training focused on the development and testing of a web-based peer-assessment educational technology and how student log data from such technology can be used to build machine learning models that can predict student performance reliably and can serve as tools of early intervention. During his time at HCII, he has contributed to efforts to develop machine learning models
that detect student affective states and co-led projects to develop real-time student activity visualization on Augmented Reality (AR) headsets, cloud-based services to aid educational
technology research and web-based cognitive tutor interfaces in accordance with best industry practices.

HOST: Bruce McLaren


Amy Pavel

"Describing Videos"

ABSTRACT: For decades, text was a primary source for information online including mediums like tutorials, instructions, reviews, and blogs. Recently, online videos hosted on platforms like YouTube, and Vimeo, have become primary information sources for many users, in parallel forms of explainer videos, how-to tutorials, unboxings, and vlog. But, online videos often use visual content to convey core information creating potentially serious access barriers for people who can not see it. One approach to making videos more accessible is to create audio descriptions — or narrated descriptions of the visual content in videos — but such descriptions are typically only created by audio description professionals. Creating audio descriptions is challenging, largely due to the synchronous nature of the audio description that must fit into gaps of other video content. In this talk, I’ll introduce a tool, Rescribe, that helps authors create and refine their audio descriptions. Using Rescribe, authors first create a draft of all the content they would like to include in the audio description. Rescribe then optimizes between the length of the audio description, available automatic shortening approaches (automated paraphrasing and extractive summarization), and source track lengthening approaches. I present the results of two user studies: one with novice audio description creators using Rescribe and one with blind and visually impaired audio description users evaluating the results of Rescribe. I will conclude with additional challenges and potential solutions for creating informative descriptions at scale.

BIO: Amy Pavel is a postdoc in the HCII at CMU and the Accessibility/ML research group at Apple. Her research considers how interactive tools, augmented with natural language understanding and generation, can help people with expertise to create useful representations of their recorded data such as videos, feedback sessions, and conversations. Her work has been published in conferences such as UIST, CHI, and ASSETS. She was previously a graduate student in the EECS department at UC Berkeley, where her work was supported by an NDSEG fellowship. Read more at her website: