liberact conference 2013 gnome surfer & moclo planner
TRANSCRIPT
Reality-based Interfaces for Collaborative Discovery
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How reality-based interaction can enhance collaborative learning and discovery?
Frameworks
& Tools
Interactive Systems
Evaluation
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Renaissance Team as Methodology
Outline G-nome Surfer Collaborative Exploration of Genomic Data
MoClo Planner A Collaborative Tool for Designing and specifying biological constructs
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A Tabletop Interface for Collaborative Exploration of Genomics
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Preliminary User Studies Position #
PIs 9
Postdocs 6
Industry Researchers 2
Student Researchers 12
Research Assistant 2
Master Student 1
Total 32
Goal Design requirements for synthetic biologists
Interview Procedure
1 hour interviews in laboratories
Interview Questions
Procedure walk-through Research goals Work practices Computational tools Future of the field
Data Collection
Video Voice recordings Screenshots Observations
Qualitative Methods
• Affinity diagrams • Iterative coding
Institutions
• Boston University • Harvard Medical School • MIT • Wellesley College • Wyss Institute
Heterogeneous Data
8
Design Goals
Locate
Learn Retrieve
Annotate
Compare
O. Shaer, M. Strait, C. Valdes, T. Feng, M. Lintz and H. Wang, Enhancing Genomic
Learning through Tabletop Interaction, Proc. ACM CHI 2011.
1. Microscopic: Usability of concrete interaction techniques
2. Macroscopic: Usefulness for real-world tasks
3. Holistic: Impact on collaborative learning
Evaluation
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Experimental task: Identify the molecular basis of an unclassified motor mutation in mice
Existing web-based bioinformatics tools G-nome Surfer with multi-mouse GUI G-nome Surfer
Macroscopic Evaluation: Comparative study with 48 students
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Holistic evaluation
Intermediate college-level Neuroscience laboratory Synthetic biology lab at BU
Evaluating Collaborative Problem Solving
• Quantitative measures
– Number and value of insights
– time per activity
– subjective workload
– attitude
– physical and verbal participation
– equality of participation
• Qualitative indicators
– collaboration style
– problem-solving strategy
– nature of discussion
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Findings • G-nome Surfer improves students performance,
reduces workload, and increases enjoyment (compare to current state-of-the-art bioinformatics tools)
• The tabletop prototype (compare to multi-mouse interface):
– Increases physical participation
– Encourages reflection
– Fosters effective collaboration
– Facilitates more intuitive interaction
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MoClo Planner A collaborative tool for Modular Cloning
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From Design to Synthesis
Clones multiple DNA fragments in a single reaction
Fusion sites – the cut and paste sites of Golden Gate cloning
Promoters
Fusion Site
Compatible Fusion Sites RBS
RBS Promoters
Modular Cloning
Requirements • Process
visualization
• Resource integration
• Efficiency
• Collaboration
Level 0: Basic Modules
Level 1: Transcriptional Units
Level 2: Multigene Constructs
Three tiers
Level 0: Choosing basic (L0) modules
Level 1: Building transcriptional units
Level 2: Building multigene constructs
S.Liu, K. Lu, N. Seifeselassie, C. Grote, N. Francisco, V. Lin, L. Ding, C. Valdes, R.
Kincaid, O. Shaer, MoClo Planner: Supporting Innovation in Bio-Design through
Multitouch Interaction , Demo abstract, ACM ITS 2012.
Research
Design
Build
Test
Evaluation
Position #
PIs 1
Postdocs 1
Student Researchers 22
Total 24
Institutions
• Boston University iGEM • MIT iGEM • Wellesley College
Goal Evaluate the usability of the program
Study Procedure
Use PixelSense in user’s lab environment
Usability Task
Select specific parts from Parts Registry
Build a Level 1 module Build a Level 2 module Create primers
Data Collection
Video recording Audio recording Post-task interview NASA TLX questionnaire Engagement questionnaire
User Study Task
General findings • Successful task completion
• User recommended
• Lowered complexity
• Quick and Efficient
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Going forward 1) Reality-based interaction offers unique opportunities for enhancing discovery and learning in data-intensive areas. 2) Designing interaction for problems in genomics can help move forwards the theory and practice of TEI. 3) Future research includes: How to visualize and engage data, activity, progress spanning many systems, people, places, timescales?
What representational forms, device ecologies, most appropriate for large, abstract data?
Facilitating engagement with big data in ways that highlight connections between multiple forms of evidence
Lessons learned and Going Forward RBI can facilitate immediate, visible, and easily reversible manipulations
• How to design TEI for open-ended creative inquiries?
Visual representations can facilitate multi-stage workflows
• Important for execution and tracking of complex analyses
• Need parametrized, annotatable representations of complex large datasets
RBI could facilitate collaboration for co-located teams
• Large interdisciplinary teams and distributed work are common in this area
• Users can jointly manipulate assumptions and see consequences
RBIs can support understanding and discovery
• Provide access to different pieces of the problem (data, reactions)
• Help users forms accurate mental models through tangible/embodied manipulation
Acknowledgements
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