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 shaped by the faculty, students, and teachers in the Center for Learning, Computing, and Imagination, our partner teachers, school leaders, and families, and generous external funding.

We publish primarily in Computing Education and Human-Computer Interaction. I also work to broaden research discourse as Editor-in-Chief of ACM TOCE and sustain peer review with Reciprocal Reviews. We share our discoveries by blogging, presenting, teaching, writing, and and connecting with community, including the CS for All Washington advocacy community and 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”—๏ธŽ

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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Programming languages can be designed to include everyone (2011 โ€” 2025)
Programming languages can embody values of justice, equity, and inclusion, but it requires careful design and attention to ability, culture, language, and more.

Amy J. Ko headshotCarlos Aldana Lira headshotIsabel Amaya headshotMegumi Kivuva headshotMichael J. Lee headshot

programming languagesjusticetools

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Learning to code with families can enable rich new forms of intergenerational learning (2018 โ€” 2025)
But it requires careful attention to the design of learning technologies to facilitate facile role switching.

Stefania Druga headshotAmy J. Ko headshotFee Christoph headshotRahul Banerjee headshotJason Yip headshot

familiesstudieslearning ย  ๐ŸŽฌ videoย 

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CS assessments aren't fair, but it's very hard to know how and why (2017 โ€” 2025)
Techniques from psychometrics can help, but they are far from usable by everyday CS teachers.

Amy J. Ko headshotBenjamin Zhou headshotMin Li headshotEman Sherif headshotJayne Everson headshotMegumi Kivuva headshotMara Kirdani-Ryan headshotBenjamin Xie headshotMatt Davidson headshotBrett Wortzman headshotGreg Nelson headshotHarshitha Akkaraju headshotWilliam Kwok headshotAmber Hu headshotAnnie Yan headshotMichael J. Lee headshotAda Kim headshot

assessmentstudiestools

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Justice-focused computing education requires trust, agency, respect, liberation, and courage (2020 โ€” 2025)
Making room for conversations about computing, society, and fairness demands deep respect for students' limiting situations, but also liberatory pedagogies.

Megumi Kivuva headshotAmy J. Ko headshotCarlos Aldana Lira headshotIsabel Amaya headshotJean Salac headshotLena Armstrong headshotJayne Everson headshotRotem Landesman headshotJared Lim headshotAlannah Oleson headshotAudrey Le Meur headshotStefania Druga headshotAnne Beitlers headshotBrett Wortzman headshotBenjamin Xie headshotMatt Davidson headshotMara Kirdani-Ryan headshotYim Register headshotMina Tari headshotDastyni Loksa headshotGreg Nelson headshot

justicestudies

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Understanding machine learning means understanding uncertainty (2005 โ€” 2025)
Tools can help, but even more so, using data and domains that people understand is even better.

Stefania Druga headshotAmy J. Ko headshotFee Christoph headshotChenglong Wang headshotYim Register headshotKayur Patel headshot

AI educationstudiestools

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People's interests in computing are intricately shaped by their social worlds (2009 โ€” 2025)
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.

Jayne Everson headshotMegumi Kivuva headshotEman Sherif headshotAlannah Oleson headshotAmy J. Ko headshotRotem Landesman headshotJean Salac headshotLena Armstrong headshotMara Kirdani-Ryan headshotChris Perdriau headshotMeron Solomon headshotAnael Kuperwajs Cohen headshotCamilo Montes de Haro headshotLeah Perlmutter headshotAnne Beitlers headshotBenjamin Xie headshotHarrison Kwik headshotRahul Banerjee headshotJason Yip headshotLeanne Hwa headshotKatie Davis headshotKyle Thayer headshot

intereststudies

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Text-based code editors can be richly interactive (2004 โ€” 2025)
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 headshotCarlos Aldana Lira headshotIsabel Amaya headshot

editorsprogrammingtools ย  ๐ŸŽฌ videoย 

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The tools and systems around programming languages are a primary source of learning difficulty (2000 โ€” 2025)
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 headshotBlaze Jayne Burg headshotThomas D. LaToza headshotMichael J. Lee headshot

programming systemsprogrammingstudies

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Teaching about diversity in CS is possible, but requires substantial professional development (2015 โ€” 2024)
The topic is largely ignored because of lack of teacher professional development, student resistance, and fear of failure, not disinterest.

Alannah Oleson headshotAmy J. Ko headshotMeron Solomon headshotChris Perdriau headshotBrett Wortzman headshotMatt Davidson headshotMara Kirdani-Ryan headshotStefania Druga headshotJayne Everson headshotSaba Kawas headshotLaura Vonessen headshotKristen Shinohara headshot

diversitystudies

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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.

Benjamin Xie headshotJared Lim headshotPaul Pham headshotMin Li headshotAmy J. Ko headshotThomas D. LaToza headshotJenny Liang headshotDastyni Loksa headshotHarrison Kwik headshotWilliam Kwok headshotJane Quichocho headshotHarshitha Akkaraju headshotGreg Nelson headshotMichael J. Lee headshotAlannah Oleson headshot

problem solvingstudies

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Studying programming requires human-centered methods (2006 โ€” 2023)
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.

Jenny Liang headshotAmy J. Ko headshotThomas D. LaToza headshotKyle Thayer headshotGreg Nelson headshotPaul Luo Li headshot

methods

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Equitable CS teaching requires equity and resources that CS culture resists (2019 โ€” 2022)
Teachers need time, resources, and community support to teach equitably, but CS culture often resists these needs in favor of individual achievement and technical prowess.

Jayne Everson headshotAmy J. Ko headshotSaba Kawas headshotLaura Vonessen headshot

teachingstudies

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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.

Stefania Druga headshotAmy J. Ko headshotAda Kim headshot

tutorialsstudies

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It is possible to mine, transform, and synthesize interfaces to serve new use cases and users (2015 โ€” 2021)
Reasoning about user interfaces in probabalistic and formal ways can enable new forms of accessibility and productivity.

Chenglong Wang headshotAmy J. Ko headshotAmanda Swearngin headshotAlannah Oleson headshotBlaze Jayne Burg headshot

UI miningtools ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย 

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Software engineering depends on information (2006 โ€” 2021)
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.

Kyle Thayer headshotAmy J. Ko headshot

teamsstudies

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Accessible computing can be taught as part of CS education (2016 โ€” 2019)

Saba Kawas headshotLaura Vonessen headshotAmy J. Ko headshotKristen Shinohara headshot

accessibilitystudiesteaching

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Teaching program reading before writing can promote more robust learning (2011 โ€” 2019)
This is because writing skills are dependent on reading skills. Unfortunately, learning to read code correctly can be boring.

Benjamin Xie headshotDastyni Loksa headshotGreg Nelson headshotMatt Davidson headshotHarrison Kwik headshotAlex Tan headshotLeanne Hwa headshotMin Li headshotAmy J. Ko headshotMichael J. Lee headshotPolina Charters headshotFanny Luor headshotMichael Beswetherick headshot

program readingpedagogytools

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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 headshotAmy J. Ko headshot

expertisestudies

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Some defects can be found by operationalizing principles of human communication (2005 โ€” 2018)
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 headshotBryan Dosono headshotNeeraja Duriseti headshotParmit K. Chilana headshotXing Zhang headshotPaul Luo Li headshot

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

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Finding help with software can be as simple as pointing (2006 โ€” 2015)
Pointing to user interface elements can be a powerfully discrminating input into help retrieval algorithms.

Parmit K. Chilana headshotAmy J. Ko headshot

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

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Programs can answer questions about their behavior (2004 โ€” 2013)
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.

Blaze Jayne Burg headshotAmy J. Ko headshot

debuggingtools ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย ย  ๐ŸŽฌ videoย  ย {}ย code

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Bug reports are where developers and users engage in conflict around what software is for (2003 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 headshotParmit K. Chilana headshotMichael J. Lee headshotValentina Ferrari headshotStephen Ip headshotCharlie Tran headshot

issue trackingstudies

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Design skills depend greatly on domain expertise (2006 โ€” 2012)
We found through several studies that designers' productivity and careers are often limited by their lack of domain expertise.

Parmit K. Chilana headshotAmy J. Ko headshot

designstudies

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Framing compilers as fallible, prosocial collaborators can facilitate learning (2011)
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.

Michael J. Lee headshotAmy J. Ko headshot

feedbackstudiestools ย ๐Ÿ–ฅ๏ธ demo

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Defects emerge from the interaction of satisficing and state space complexity (2002 โ€” 2005)
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


CC0 Last updated 12/18/2025. 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.