Katherine Deibel: Research

For any assistive technology to truly be helpful and beneficial, the technology itself must be adopted into regular use. However, a third to one half of all assistive technologies are abandoned after purchase. This results not only in a waste of time, money, and resources, but can also lead to disillusionment about the potential helpfulness of assistive technologies.

My dissertation is about understanding and supporting the adoption of assistive technologies for adults with reading disabilities. Using Value Sensitive Design, I am investigating the complex interactions between users, technologies, and sociocultural contexts. Through this approach, I am developing insights into the important values that assistive technologies need to respect in order to both meet the needs of the users and ensure that the technologies are adoptable.

Further Reading

• K. Deibel. Current Issues and Research in Digital Literacies and Disabilities (asynchronous sakai discussion). Online Portion of Computers and Writing 2009, February 2009. [Abstract (pdf)]
• K. Deibel. Access Technology for Reading Disabilities & Access Technology Acceptance. Invited lecture in CSEP 590B Accessibility, University of Washington, Seattle, WA, USA, October 2008. [ppt]
• K. Deibel. Sociocultural Factors of Assistive Technology Adoption among Individuals with Reading Disabilities. New Scholarship at the Intersections: Care, Work, and Diversity, Graduate Research Conference, School of Social Work, University of Washington, Seattle, WA, USA, April 2008. [pdf] [ppt]
• K. Deibel. Adoption of Assistive Technologies for Reading Disabilities: Cultural, Literacy, and Technological Aspects. Generals Examination, Department of Computer Science & Engineering, University of Washington, Seattle, WA, USA, November 2007. [pdf] [ppt]
• K. Deibel. Adoption and Configuration of Assistive Technologies: A Semiotic Engineering Perspective. Proceedings of the 9th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), p 237-238, 2007. [pdf] [ppt]
• K. Deibel. Understanding and Supporting the Use of Accommodating Technologies by Adult Learners with Reading Disabilities. ACM SIGACCESS Accessibility and Computing, 86, p. 32-35, September 2006. [pdf]

Experiences of Students with Disabilities in Computing Courses

Working from my interests involving disability and education, I conducted a series of interviews with students with disabilities about their experiences in computer science courses. I had two goals with these studies. First, I wanted to identify challenges in doing studies of university students with disabilities and then determine appropriate research methodologies. The second goal was to get an understanding of how the students' disabilities impacted their course experiences and how the courses could be adjusted (if necessary) to be more inclusive.

I have also begun to use this study and its findings as a means for teaching faculty and staff about inclusive education practices.

Further Reading

• K. Deibel. Inclusive Teaching Practices for Supporting Students with Disabilities. Practical Pedagogy Roundtable, University of Washington, Seattle, WA, USA, February 2009. [ppt]
• K. Deibel. Inclusive Practices for [Computer Science] Education. Invited lecture, Faculty Development Workshop, Digipen Institute of Technology, Redmond, WA, USA, August 2008. [ppt]
• K. Deibel. Course Experiences of Computing Students with Disabilities: Four Case Studies. Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education, p. 454-458, 2008. [pdf] [ppt]
• K. Deibel. Studying Our Inclusive Practices: Course Experiences of Students with Disabilities. Proceedings of the 12th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), p. 266-270, 2007. [pdf] [ppt]

Teaching Cyber-Savvy: Website Evaluation Skills

In collaboration with fellow UW graduate students, Tim Wright and Sarah Read from Practical Pedagogy Research, we have been exploring how to teach students to be better consumers of information from the World Wide Web. Through a multidisciplinary effort, we have developed the Q6C process to support both students and instructors in learning how to effectively evaluate the reliability and usefulness of web-based sources.

Further Reading

• S. Read, K. Deibel, and T. Wright. Teaching sustainable online research practices across the curriculum: The Q6C Solution (panel). Computers and Writing 2009, Davis, CA, USA, June 2009. [Abstract (pdf)]
• S. Read, T. Wright, and K. Deibel. Q6C: A Transdisciplinary Process for Teaching Online Research Practices (poster). 2009 University of Washington Teaching and Learning Symposium, Seattle, WA, USA, 2009. [ppt] [Handout (pdf)]
• K. Deibel, S. Read, and T. Wright. Q6C: A Multidisciplinary Approach for Teaching Online Research Practice (poster). 40th SIGCSE Technical Symposium on Computer Science Education, Chattanooga, TN, USA, 2009. [Abstract (pdf)] [Poster (ppt)]
• T. Wright, K. Deibel, and S. Read. Across the Disciplines: Strategies for Teaching Cyber-Savvy. 2008 CIDR Teaching and Learning Symposium, Center for Instructional Development and Research, University of Washington, Seattle, WA, USA, May 2008. [ppt]

Analyzing Card Sorts Through Edit Distance Clustering

This was a continuation of work with Richard Anderson and Ruth Anderson on the Bootstrapping Project. As part of our analysis of the card sorting data from this project, we developed a method for determining the relative distance between card s orts using a defined edit metric. Using this new analysis technique, we identified clusters of closely-related sorts and examined the descriptions the sorters gave to these sorts.

Further Reading

• K. Deibel, R. Anderson, and R. Anderson. Using Edit Distance to Analyze Card Sorts. Expert Systems, 22(3), p. 129-138, July 2005. [abstract] [pdf]

Software

• UW Card Sort Analyzer (intermittently supported)

Facilitating Group Work

From personal experience as both a student and an instructor (teaching assistant), the benefit of in-class group work for students is mixed. As part of my TA work, I became interested in forming student groups to promote participation from all students. I developed two team formation techniques: one using the Felder-Silverman styles and a variation on the classic jigsaw method—the latent jigsaw.

Further Reading

• E.F. Gehringer, K. Deibel, K. J. Whittington, and J. Hamer. Cooperative Learning—Beyond Pair Programming and Team Projects (panel). Proceedings of the 37th SIGCSE Technical Symposium on Computer Science Education, p. 458-459, 2006. [pdf] [ppt]
• K. Deibel. Team Formation Methods for Increasing Interaction During In-Class Group Work. Proceedings of the 10th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), p. 291-295, 2005. [pdf] [ppt]

At the Center for Engineering Learning and Teaching, I work on projects related to understanding the design processes of engineering students and professionals. In particular, I develop tools to support the analysis of verbal protocol data with a specific interest in visualization of that information. One such example are timeline representations of coded, segmented transcripts (example to the right).

Software

• CELT Analysis Tools (coming eventually)

Assisted Cognition Research

The Assisted Cognition project led by Henry Kautz is an effort to develop computing technologies to increase independence for adults with mild to moderate Alzheimer's disease and dementia by providing support for activites for daily living. For my Master's work / qualifying exam, I worked on a system for recognizing human activities within a sensored environment.

In order to recognize human activities from a large plan library, a probabilistic inference engine requires not only efficiency and scalability, but also flexibility in terms of configurability and end-user programming by non-experts. My solution to these challenges was contrail filtering. Contrail filtering extends the notion of particle filtering by incorporating memory management into the structure of the inference engine and thereby allows the underlying dynamic Bayesian network structure to change as necessary.

Further Reading

• K. Deibel. Contrail Filtering: A Mechanism for Efficient and Robust Activity Recognition. Qualifying Examination Document. Department of Computer Science and Engineering, University of Washington,Seattle, WA, May 2003. [pdf]
• K. Deibel. Contrail Filtering: A Mechanism for Structured Flexibility in Activity Recognition. Qualifying Exam Presentation. Department of Computer Science and Engineering, University of Washington,Seattle, WA, May 2003. [ppt]