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Welcome!
Basic question
What should we teach biologists about
computing and data?
How can we motivate it?
(My ideas go here)
But I’m making lots of assumptions –
• Molecular biologist
• Sequencing data analyst
Improve thyself
• Virtually everyone who cares thinks they’re a
good teacher.
• (We’re probably mostly wrong, in terms of
actual knowledge transfer.)
• Assessment and evaluation is key, and core, to
the mission of teaching.
• Assessment must be done in context of
subject, not by outside “experts.”
Pulling back…
• BIO Centers meeting on “Cyberinfrastructure
issues in BIO” here at SESYNC, ~1 year ago
• Everyone’s secondary concern was education:
– Inexpert users
– No clear training path for grads, postdocs
– But always secondary to their mission.
• Funding opportunity: $200k/1 yr => ???
This grant, v1
Software Carpentry + Bio
1. Coordination meetings (us)
2. 2-day workshops at centers (me +)
3. Assessment (Julie)
4. Material development (me + ??)
Topics: Compute + Data
Level: grad student and beyond
This grant, v2
Added NESCent, +3 workshops/+$70k
• “Workflow meeting” – Galaxy, Taverna, iPlant,
etc to present & cross-train.
• “Workflow hackathon” – install, configure,
execute each other’s workflow engines.
• “Train the trainers” – hands-on workshop on
teaching people to teach workflow engines.
My background for this
• Two-week workshop on Analyzing NGS
– 4th year
– NIH funded
– Starts from scratch
• Software Carpentry 2-day workshops
• Grad course (3 years)
– Programming!?
• Research-focused workshops
BIO + Software Carpentry
• Biologists trend towards the “intro” side on
the spectrum of computing expertise.
• Virtually no undergrad training, no culture of
computing, little math or computing.
• Ultimately this stuff will need to be integrated
into introductory biology courses.
• For now focused on grad student education.
Why are you here?
• Many varied reasons
• Most of you, one way or another, are actively
engaged in teaching or thinking about
teaching computing to scientists.
• And/or Greg gave me your name.
What are we here to do?
• Brainstorm on what to teach about compute
and data.
• Figure out what teachers should know.
• ???

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2013 bio-sesync-intro

  • 2. Basic question What should we teach biologists about computing and data? How can we motivate it?
  • 3. (My ideas go here) But I’m making lots of assumptions – • Molecular biologist • Sequencing data analyst
  • 4. Improve thyself • Virtually everyone who cares thinks they’re a good teacher. • (We’re probably mostly wrong, in terms of actual knowledge transfer.) • Assessment and evaluation is key, and core, to the mission of teaching. • Assessment must be done in context of subject, not by outside “experts.”
  • 5. Pulling back… • BIO Centers meeting on “Cyberinfrastructure issues in BIO” here at SESYNC, ~1 year ago • Everyone’s secondary concern was education: – Inexpert users – No clear training path for grads, postdocs – But always secondary to their mission. • Funding opportunity: $200k/1 yr => ???
  • 6. This grant, v1 Software Carpentry + Bio 1. Coordination meetings (us) 2. 2-day workshops at centers (me +) 3. Assessment (Julie) 4. Material development (me + ??) Topics: Compute + Data Level: grad student and beyond
  • 7. This grant, v2 Added NESCent, +3 workshops/+$70k • “Workflow meeting” – Galaxy, Taverna, iPlant, etc to present & cross-train. • “Workflow hackathon” – install, configure, execute each other’s workflow engines. • “Train the trainers” – hands-on workshop on teaching people to teach workflow engines.
  • 8. My background for this • Two-week workshop on Analyzing NGS – 4th year – NIH funded – Starts from scratch • Software Carpentry 2-day workshops • Grad course (3 years) – Programming!? • Research-focused workshops
  • 9. BIO + Software Carpentry • Biologists trend towards the “intro” side on the spectrum of computing expertise. • Virtually no undergrad training, no culture of computing, little math or computing. • Ultimately this stuff will need to be integrated into introductory biology courses. • For now focused on grad student education.
  • 10. Why are you here? • Many varied reasons • Most of you, one way or another, are actively engaged in teaching or thinking about teaching computing to scientists. • And/or Greg gave me your name.
  • 11. What are we here to do? • Brainstorm on what to teach about compute and data. • Figure out what teachers should know. • ???