2017 - ACM Fellow For contributions to end-user software engineering, understanding gender biases in software, and broadening participation in computing
2015 - ACM Distinguished Member
Her main research concerns End user, Software engineering, Human–computer interaction, Debugging and Programming language. Her End user research includes elements of Software, Correctness and Formative assessment. She has researched Software in several fields, including Web page and Knowledge management.
Her Software engineering research incorporates elements of Software maintenance, Software development, Interface, User interface design and Empirical research. Her Human–computer interaction study integrates concerns from other disciplines, such as Active learning, Machine learning and Artificial intelligence. The study incorporates disciplines such as Intelligent agent and Soundness in addition to Debugging.
Margaret Burnett mainly investigates End user, Software engineering, Programming language, Human–computer interaction and Software. The concepts of her End user study are interwoven with issues in Web application, Debugging, End user software engineering and Artificial intelligence. Her Debugging research is multidisciplinary, relying on both Correctness and Information foraging.
Her studies in Software engineering integrate themes in fields like Software maintenance and Software development. The various areas that Margaret Burnett examines in her Human–computer interaction study include User interface and Empirical research. Her study in Software is interdisciplinary in nature, drawing from both Knowledge management and Data science.
Her primary areas of study are Software, Data science, Empirical research, Human–computer interaction and Knowledge management. In general Software study, her work on Software walkthrough and Software development often relates to the realm of Work, thereby connecting several areas of interest. Margaret Burnett has included themes like Intelligent agent, Field, Information foraging, Debugging and Social software engineering in her Data science study.
Her studies deal with areas such as Active learning and Cluster as well as Debugging. Her Human–computer interaction research includes themes of Programming language, End user and Embedded system. Her work investigates the relationship between Visualization and topics such as Software engineering that intersect with problems in Time on task.
Margaret Burnett mainly focuses on Data science, Empirical research, Set, Software and Human–computer interaction. Her work deals with themes such as Information foraging, Personal software process, Formative assessment, Debugging and Focus, which intersect with Data science. Her research investigates the connection with Empirical research and areas like Management science which intersect with concerns in Time on task.
Her study on Software Engineering Process Group, Software walkthrough and Software development is often connected to Design modification as part of broader study in Software. Margaret Burnett interconnects Programming language, Active learning, Situated, Software design pattern and End user in the investigation of issues within Human–computer interaction. Her End user research is multidisciplinary, incorporating elements of Learning theory, Traditional learning, Real-time strategy, Error-driven learning and Machine learning.
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The state of the art in end-user software engineering
Amy J. Ko;Robin Abraham;Laura Beckwith;Alan Blackwell.
Principles of Explanatory Debugging to Personalize Interactive Machine Learning
Todd Kulesza;Margaret Burnett;Weng-Keen Wong;Simone Stumpf.
intelligent user interfaces (2015)
A methodology for testing spreadsheets
Gregg Rothermel;Margaret Burnett;Lixin Li;Christopher Dupuis.
ACM Transactions on Software Engineering and Methodology (2001)
Forms/3: A first-order visual language to explore the boundaries of the spreadsheet paradigm
Margaret Burnett;John Atwood;Rebecca Walpole Djang;James Reichwein.
Journal of Functional Programming (2001)
End-user software engineering
Margaret Burnett;Curtis Cook;Gregg Rothermel.
Communications of The ACM (2004)
Too much, too little, or just right? Ways explanations impact end users' mental models
Todd Kulesza;Simone Stumpf;Margaret Burnett;Sherry Yang.
symposium on visual languages and human-centric computing (2013)
A user-centred approach to functions in Excel
Simon Peyton Jones;Alan Blackwell;Margaret Burnett.
international conference on functional programming (2003)
Interacting meaningfully with machine learning systems: Three experiments
Simone Stumpf;Vidya Rajaram;Lida Li;Weng-Keen Wong.
International Journal of Human-computer Studies / International Journal of Man-machine Studies (2009)
A practical guide to controlled experiments of software engineering tools with human participants
Andrew J. Ko;Thomas D. Latoza;Margaret M. Burnett.
Empirical Software Engineering (2015)
Scaling up visual programming languages
M.M. Burnett;M.J. Baker;C. Bohus;P. Carlson.
IEEE Computer (1995)
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