Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Learning action strategies for planning domains
Artificial Intelligence
ACM Computing Surveys (CSUR)
Automatic personalization based on Web usage mining
Communications of the ACM
Extracting usability information from user interface events
ACM Computing Surveys (CSUR)
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Women go with the (optical) flow
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Knowledge Discovery from Telecommunication Network Alarm Databases
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Modeling User Behavior by Integrating AQ Learning with a Database: Initial Results
Proceedings of the IIS'2002 Symposium on Intelligent Information Systems
From run-time behavior to usage scenarios: an interaction-pattern mining approach
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Sequential PAttern mining using a bitmap representation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
A divisive information theoretic feature clustering algorithm for text classification
The Journal of Machine Learning Research
Forms/3: A first-order visual language to explore the boundaries of the spreadsheet paradigm
Journal of Functional Programming
The fuzzy felt ethnography—understanding the programming patterns of domestic appliances
Personal and Ubiquitous Computing
Communications of the ACM - End-user development: tools that empower users to create their own software solutions
Gender: An Important Factor in End-User Programming Environments?
VLHCC '04 Proceedings of the 2004 IEEE Symposium on Visual Languages - Human Centric Computing
Effectiveness of end-user debugging software features: are there gender issues?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Summarizing itemset patterns: a profile-based approach
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Mining compressed frequent-pattern sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Tinkering and gender in end-user programmers' debugging
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The influence of task and gender on search and evaluation behavior using Google
Information Processing and Management: an International Journal
Generating semantic annotations for frequent patterns with context analysis
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting redundancy-aware top-k patterns
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing itemset patterns using probabilistic models
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Gender HCI: What About the Software?
Computer
Storytelling alice motivates middle school girls to learn computer programming
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
On to the Real World: Gender and Self-Efficacy in Excel
VLHCC '07 Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing
Design Planning in End-User Web Development
VLHCC '07 Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing
Testing vs. code inspection vs. what else?: male and female end users' debugging strategies
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An ethnographic examination of the relationship of gender & end-user programming
An ethnographic examination of the relationship of gender & end-user programming
The last mile: parallel programming and usability
Proceedings of the FSE/SDP workshop on Future of software engineering research
Instrumenting the crowd: using implicit behavioral measures to predict task performance
Proceedings of the 24th annual ACM symposium on User interface software and technology
ACM Transactions on Computer-Human Interaction (TOCHI)
End-user debugging strategies: A sensemaking perspective
ACM Transactions on Computer-Human Interaction (TOCHI)
Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design
Machine learning based analysis of gender differences in visual inspection decision making
Information Sciences: an International Journal
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Can we learn about users' problem-solving strategies by observing their actions? This article introduces a data mining system that extracts complex behavioral patterns from logged user actions to discover users' high-level strategies. Our application domain is an HCI study aimed at revealing users' strategies in an end-user debugging task and understanding how the strategies relate to gender and to success. We cast this problem as a sequential pattern discovery problem, where user strategies are manifested as sequential behavior patterns. Problematically, we found that the patterns discovered by standard data mining algorithms were difficult to interpret and provided limited information about high-level strategies. To help interpret the patterns as strategies, we examined multiple ways of clustering the patterns into meaningful groups. This collectively led to interesting findings about users' behavior in terms of both gender differences and debugging success. These common behavioral patterns were novel HCI findings about differences in males' and females' behavior with software, and were verified by a parallel study with an independent data set on strategies. As a research endeavor into the interpretability issues faced by data mining techniques, our work also highlights important research directions for making data mining more accessible to non-data-mining experts.