My research imagines and enables equitable, joyous, liberatory learning about computing and information, in schools and beyond.

I work with outstanding postdocs, doctoral students, undergraduates, teachers and communities on this vision. My current projects within this goal are largely shaped by the faculty, students, and teachers in the Center for Learning, Computing, and Imagination, our partner teachers, school leaders, and families, and to a lesser extent, my active grants.

We publish primarily in Computing Education and Human-Computer Interaction and I work to broaden scholarly discourse as Editor-in-Chief of ACM TOCE and facilitating Reciprocal Reviews. More importantly, we share our discoveries broadly by blogging, presenting, teaching, writing, and and connecting with community, including the CS for All Washington advocacy community, the PNW CS Teach consortium of teacher educators.

Want to do research with me? Read about my lab, and join us in creating a more equitable future of computing that includes everyone.

Discoveries ๐Ÿ”—

My lab and I have discovered many things since I started doing research in 1999. Here are some of the highlights from our work. How I describe these is always evolving as we learn more.

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Justice-focused CS education is empowering but requires student trust and agency (2021 โ€” 2024)
Making room for conversations about computing, society, and fairness demands deep respect for students' limiting situations.

Jayne Everson headshot Amy J. Ko headshot Megumi Kivuva headshot Brett Wortzman headshot Matt Davidson headshot Alannah Oleson headshot Mara Kirdani-Ryan headshot Stefania Druga headshot Anne Beitlers headshot Jean Salac headshot Lena Armstrong headshot Audrey Le Meur headshot Rotem Landesman headshot Camilo Montes de Haro headshot

justicestudies ย ๐Ÿ“„papers

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CS assessments aren't fair, but it's very hard to know how and why (2019 โ€” 2023)
Techniques from psychometrics can help, but they are far from usable by everyday CS teachers.

Matt Davidson headshot Amy J. Ko headshot Brett Wortzman headshot Benjamin Xie headshot Alannah Oleson headshot Jayne Everson headshot Min Li headshot Greg Nelson headshot Anne Drew Hu headshot Lena Armstrong headshot

assessmentstudiestools ย ๐Ÿ“„papers

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Programming problem solving can benefit greatly from guided, step-by-step scaffolding (2015 โ€” 2023)
Most learners don't want to be that deliberate about their process, favoring less effective trial and error strategies. But framing it as aunthetic practice can help.

Michael J. Lee headshot Amy J. Ko headshot Dastyni Loksa headshot Alannah Oleson headshot Thomas D. LaToza headshot William Kwok headshot Jane Quichocho headshot Harshitha Akkaraju headshot Benjamin Xie headshot Harrison Kwik headshot Jenny Liang headshot

problem solvingstudies ย ๐Ÿ“„papers

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People's interests in computing are intricately shaped by their social worlds (2009 โ€” 2023)
We found across a series of reflective studies that people and events in people's lives come to shape their interest and disinterest in computing.

Amy J. Ko headshot Katie Davis headshot Leanne Hwa headshot Jason Yip headshot Harrison Kwik headshot Benjamin Xie headshot Leah Perlmutter headshot Jean Salac headshot Megumi Kivuva headshot Mara Kirdani-Ryan headshot

intereststudies ย ๐Ÿ“„papers

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Learning to code with families can enable rich new forms of intergenerational learning (2018 โ€” 2022)
But it requires careful attention to the design of learning technologies to facilitate facile role switching.

Rahul Banerjee headshot Jason Yip headshot Amy J. Ko headshot Stefania Druga headshot Fee Christoph headshot

familiesstudieslearning ย  ๐ŸŽฌ videoย  ย ๐Ÿ“„papers

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Teaching about diversity in CS is possible, but requires substantial professional development (2018 โ€” 2022)
The topic is largely ignored because of lack of teacher professional development, student resistance, and fear of failure, not disinterest.

Kristen Shinohara headshot Saba Kawas headshot Amy J. Ko headshot Alannah Oleson headshot Laura Vonessen headshot Meron Solomon headshot Mara Kirdani-Ryan headshot Yim Register headshot Benjamin Xie headshot Mina Tari headshot Matt Davidson headshot Stefania Druga headshot Dastyni Loksa headshot Greg Nelson headshot Brett Wortzman headshot Jayne Everson headshot

diversitystudies ย ๐Ÿ“„papers

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Materials for learning CS online largely ignore pedagogical best practices (2017 โ€” 2022)
They fail to provide feedback, scaffold effectively, grow self-efficacy, or develop mastery, often because learners struggle to effectively deploy their agency.

Ada Kim headshot Amy J. Ko headshot Kyle Thayer headshot Benjamin Xie headshot Greg Nelson headshot Harshitha Akkaraju headshot William Kwok headshot Stefania Druga headshot

tutorialsstudies ย ๐Ÿ“„papers

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Studying programming requires human-centered methods (2000 โ€” 2022)
Studying programming is hard. We invent new methods for studying programming, and reflect on the science of studying programming, to help accelerate progress on improving it.

Amy J. Ko headshot Thomas D. LaToza headshot Greg Nelson headshot Alannah Oleson headshot Benjamin Xie headshot Jean Salac headshot Jayne Everson headshot Megumi Kivuva headshot

methods ย ๐Ÿ“„papers

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It is possible to mine, transform, and synthesize interfaces to serve new use cases and users (2017 โ€” 2021)
Reasoning about user interfaces in probabalistic and formal ways can enable new forms of accessibility and productivity.

Amanda Swearngin headshot Amy J. Ko headshot Alannah Oleson headshot Chenglong Wang headshot

UI miningtools ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย  ย ๐Ÿ“„papers

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Understanding machine learning means understanding uncertainty (2009 โ€” 2021)
Tools can help, but even more so, using data and domains that people understand is even better.

Amy J. Ko headshot Kayur Patel headshot Yim Register headshot Stefania Druga headshot

AI educationstudiestools ย ๐Ÿ“„papers

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The tools and systems around programming languages are a primary source of learning difficulty (2000 โ€” 2021)
Programming is hard for many reasons, but my work showed that it is also hard because tools, APIs, and IDEs make information about program behavior particulary difficulty to find.

Amy J. Ko headshot Kyle Thayer headshot

programming systemsprogrammingstudies ย ๐Ÿ“„papers

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Teaching program reading before writing can promote more robust learning (2017 โ€” 2019)
This is because writing skills are dependent on reading skills. Unfortunately, learning to read code correctly can be boring.

Greg Nelson headshot Benjamin Xie headshot Amy J. Ko headshot Dastyni Loksa headshot Matt Davidson headshot Harrison Kwik headshot Alex Tan headshot Leanne Hwa headshot Min Li headshot

program readingpedagogytools ย ๐Ÿ“„papers

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Software engineering expertise is technical, but also social, organizational, and political (2015 โ€” 2019)
Across thousands of surveys and interviews, we found that expertise is far more than just knowing how to architect and build software.

Paul Luo Li headshot Amy J. Ko headshot

expertisestudies ย ๐Ÿ“„papers

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Framing compilers as fallible, prosocial collaborators can facilitate learning (2011 โ€” 2017)
Compiler feedback is usually impersonal and mean; we found that being nicer has powerful impacts on learners' attention, compelling them to pay attention to valuable direct instruction.

Amy J. Ko headshot Michael J. Lee headshot Polina Charters headshot Fanny Luor headshot Michael Beswetherick headshot Dastyni Loksa headshot Annie Yan headshot

feedbackstudiestools ย ๐Ÿ–ฅ๏ธ demo ย ๐Ÿ“„papers

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Software engineering depends on information (2007 โ€” 2017)
Through a series of studies, I unconvered the many ways that developers depend on information from people and systems to make engineering decisions, and how some of the most crucial information is hard or impossible to find.

Amy J. Ko headshot Paul Luo Li headshot

teamsstudies ย ๐Ÿ“„papers

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Design skills depend greatly on domain expertise (2009 โ€” 2015)
We found through several studies that designers' productivity and careers are often limited by their lack of domain expertise.

Parmit K. Chilana headshot Amy J. Ko headshot

designstudies ย ๐Ÿ“„papers

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Programs can answer questions about their behavior (2004 โ€” 2015)
I invented tools and algorithms for deriving 'why' and 'why not' questions from programs and automatically answering those questions, helping people efficiently and interactively debug the root causes of program failures.

Amy J. Ko headshot BJ Burg headshot

debuggingtools ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย  ย {}ย code ย ๐Ÿ“„papers

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Some defects can be found by operationalizing principles of human communication (2010 โ€” 2014)
Many defects in dynamically typed programs can be found by operationalizing simple observations about how people write code, often forgetting to close the loop that statically typed programs can easily point out.

Amy J. Ko headshot Xing Zhang headshot Bryan Dosono headshot Neeraja Duriseti headshot

verificationtools ย ๐Ÿ–ฅ๏ธ demo ย {}ย code ย ๐Ÿ“„papers

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Finding help with software can be as simple as pointing (2006 โ€” 2013)
Pointing to user interface elements can be a powerfully discrminating input into help retrieval algorithms.

Parmit K. Chilana headshot Amy J. Ko headshot

helptools ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย  ย ๐Ÿ–ฅ๏ธ demo ย {}ย code ย ๐Ÿ“„papers

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Bug reports are where developers and users engage in conflict around what software is for (2010 โ€” 2012)
The seeminly technical context of bug reports are where large communities of users and small teams of developers engage in power struggles about what software should and shouldn't do.

Amy J. Ko headshot Parmit K. Chilana headshot Michael J. Lee headshot Valentina Ferrari headshot Stephen Ip headshot Charlie Tran headshot Paul Luo Li headshot

issue trackingstudies ย ๐Ÿ“„papers

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Text-based code editors can be richly interactive (2005 โ€” 2006)
The structured editors of the 1980's were hard to build and use; I invented ways of making both easier by viewing programs as user interfaces, not documents.

Amy J. Ko headshot

editorsprogrammingtools ย  ๐ŸŽฌ videoย  ย ๐Ÿ“„papers

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Defects emerge from the interaction of satisficing and state space complexity (2003 โ€” 2006)
Much of my work during my dissertation examined where software failures come from; cognitive slips interact with the large state space that people create when programming to generate defects that are hard to localize.

Amy J. Ko headshot

errorsstudies ย ๐Ÿ“„papers


CC0 Last updated 10/7/2024. To the extent possible under law, Amy J. Ko has waived all copyright and related or neighboring rights to the design and implementation of Amy's faculty site. This work is published from the United States. See this site's GitHub repository to view source and provide feedback.