Group 7 met for the first time yesterday; 41 people attended, and three sent apologies, so it’s shaping up to be the largest cohort we’ve ever had. Notes are below (along with a warning about upcoming disruptions in the time-space continuum); the first exercise is to create some concept maps, and we’ll meet again in two weeks if Greg’s teaching schedule permits it.
Notes:
- Welcome
- Four things you need to know:
- A lot of smart people have spent decades studying learning and education, and we’ll be better teachers if we base our practices on what they’ve discovered
- Few university-level instructors know any of this.
- How Learning Works is an excellent summary
- Learning isn’t just about knowing more, it’s about thinking differently
- changing how people see the problem, “change behaviour”
- good/strong/varied connections between information
- learning how to learn
- Teaching is a performance art
- “Never hesitate to sacrifice truth for clarity”
- Make them want to care about what they are learning, and how they can use it
- personal motivation is of paramount importance for students’ learning — how to encourage that motivation?
- Software Carpentry focuses on what’s instantly usable by students.Two days isn’t much time to change behaviours.
- These curriculum items aren’t what might be most important in computing in a general sense.
- addendum: “It’s what the students are doing that counts” — E. Prather.
- Greg is still learning this stuff himself
- Feel free (and encouraged) to make corrections/additions to the material!
- A lot of smart people have spent decades studying learning and education, and we’ll be better teachers if we base our practices on what they’ve discovered
- Goals of the course
- Get you ready to improvise (because you’re going to have to)
- Every audience is different, therefore we need to be able to adapt to the audience and conditions
- diverse audience = variety of needs and backgrounds, need to adapt your materials to your audience, adapt to questions
- Familiarize you with what Software Carpentry teaches, how, and why
- sticky-notes, whiteboards, kinds of questions that work or not…
- Our GitHub repositories
- Build bonds with your fellow instructors
- pair/group activities
- observing each other, giving each other feedback: peer reviewing leads to better product and speeds things up
- interesting stat: In the US, teachers get 2/3 hours per year peer review. In Finland, 2/3 hours per week.
- Includes commenting on the work of others (constructively) on the blog
- teaching with others allows for critique, and ultimately improvement …
- “Great musicians will thank those who tear them to pieces” — taking & giving criticism are themselves hard skills
- Criticism must be constructive — tearing them to pieces gives the wrong message!
- Get you ready to improvise (because you’re going to have to)
- Learning is about building connections
- The real story is complicated (see Patricia Benner’s work on nursing), but for our purposes, there are three levels:
- Novice: “I don’t know what I don’t know”
- Frequently level of scientists who come to SWC workshops
- copy-paste/repeat exactly instructions…frequently those attending SCW
- Competent: “I can apply the right rules correctly under normal circumstances”
- Expert: “I know when to break the rules” — see the world differently
- Experts tend to be able to debug better than competents, because they can reason backwards
- But you forgot sohow to understand the thing (and explain simply): expert blind-spot
- Experts aren’t thinking faster, but are considering only the alternatives that are relevant
- getting to the point where your brain just recognises solutions, we are not aiming to create experts…we can get people from novices to competent (they can do normal things normally…).
- Two interesting experiments with chess novices and experts
- memorizing pieces position for setup coming from real games or from random placements -> experts outperformed by novices in the random case
- Want to get people from novice to competent (producing experts is not SWC’s goal)
- Takes less time
- They can get to expert themselves if needed
- The Tolstoy theory of learning: “people who understand, understand the same way; people who misunderstand misunderstand in original ways”. backed by research
- Easy to figure out student misconception if 1-on-1, but impossible for 40 or 400, this is where peer instuction can help (scales well!)
- Clear up their misconceptions, so they have the right framework to work from, and do more stuff
- Peer Instruction (best scalable instruction technique we have up to date)
- put a multiple choice question on the board — eg which option fixes this buggy code?
- ask people to vote for answers
- have people explain/discuss the answers in small groups (3-4)
- then vote again (another round of discussion and you get to talk to the people again: most of the learning takes place in the 2nd round of discussion)
- Could be a good combination of expert (teacher) and competent (peers) teaching
- Applying this to coding practices??
- MOOC don’t work very well for novices, but work well as review for concepts
- broadcast lecturing of any type (MOOC or sage on the stage) doesn’t work well for clearing up misconceptions.
- Difference (btw novice, competent, and expert) is partly volume of knowledge…
- …but strength and density of connections are actually more important
- James Burke’s Connections is a great illustration
- the better you understand the topic the more connections between the facts…so fewer hops
- We partly will give the facts, but also the connections, facts+connections=improved retention
- The more pointers to a fact in the brain, the more likely is is to be remembered (if no pointers, then purged) ; think about garbage collection
- Novice: “I don’t know what I don’t know”
- The real story is complicated (see Patricia Benner’s work on nursing), but for our purposes, there are three levels:
- Teaching is about making new facts and connections digestible
- How the brain learns under-constraints instructional design
- 7 plus or minus 2 (number of facts short-term memory can hold at one time — Don’t overload!)
- 45-90 minutes (brain gets tired at this point, murble murble murble)
- But really 5-10 minutes blocks of information we absorb
- The recovery period is about 5 minutes, get air/oxygen, need to move (Twitter doesn’t count as a reset activity)
- Underrepresented groups more likely to go into an activity if they go into it with at least a few other people that they identify as being like them
- group sign ups might bring up more interactivity and ease than individuals that never meet each other in the room…unless it’s a technique they have used before…
- scientists not use to peer review in teaching…give and accept correction…
- organization target bootcamps: share interest, even better if in the same disciplines, more material and higher retention: focus more narrower on what that particular crowd needs…
- follow-up after bootcamp: bring many people from a lab to a scw will translate in easier implementation of what they learned vs a single individual…
- And many other factors that we’ll discuss later
- People talk to each other more if they know each other.
- Round 1
- Read the first two chapters of How Learning Works and Mark Guzdial’s paper
- If you’re going to read one blog for this course, subscribe to http://teaching.software-carpentry.org
- But if you’re going to read a second, read Mark’s: http://computinged.wordpress.com/
- Pick a small topic related to what we teach here (something you think you could teach in 5 minutes) something a scientist with few computing skills would be interested in learning
- Create a concept map for it (“bubbles and arrows”)!
- Half a dozen bubbles and a dozen arcs — does not commit us to an order which a bullet list would. But we don’t think in order…we think in connections.
- Lists are linear, vs a concept map where you can put things down, link them, and then think about the order to put them in (for sketching out writing papers)
- A picture of the ideas and how they connect, not of the thing you’re teaching
- can be given to students before they’re being taught
- have students write them — as a feedback mechanism
- Low fidelity!
- no fancy software tools, draw it freehand and quickly (Post a picture)
- makes people be more honest, if you use a low fidelity drawing you will get more honest feedback…cause the reviewer see this can be done faster and therefore hurt less the feelings of the sketcher…prototypes: make them quickly, get honest feedback. Concept map: visual hook for those learnin about what they are learning: reinforces too (making the connections explicitly).
- Invert concept maps: ask the learners draw them about what they learned (quick concept map on a post-it) …you’ll be able to see if they got it or not. Not scalable though (numbers), use end of the day/just before lunch.
- See examples from past participants
- Post it by Thursday Oct 17 in the categories “Round 7.1″ and “Concept Map”
- We use categories rather than tags
- Comment on at least two other people’s concept maps
- Does it make sense?
- What’s missing?
- What’s there that shouldn’t be?
- Is it too large/too small?
- We’ll meet again on Thursday Oct 24th (if Greg’s teaching schedule permits)
- Read the first two chapters of How Learning Works and Mark Guzdial’s paper
- Q&A
- Coursera is good only if you’re already good at the subject (very bad for newcomers)
- 70-90% of successful “completers” have a background in the area
Attendees (morning):
- Greg Wilson (Mozilla, Toronto)
- Vijai Kumar (Tamilnadu, India)
- Aaron Garoutte (East Lansing, MI) (Hello, Aaron :))
- Sarah Sirin (Cambridge, MA)
- David Worth (STFC, UK)
- Fan Yang (Ames, IA, US) (hi Fan!)
- Erik Schnetter (Waterloo, ON, Canada)
- Richard Barnes (Minneapolis, MN)
- Luis Pedro Coelho (EMBL, Germany)
- Sam Thomson (Edinburgh, UK)
- Robert Flight (Lexington, KY, US)
- Joshua Adelman (Pittsburgh, PA, US) (Hi Josh — LPC)
- Don Brown (Indianapolis, IN, US)
- Pauline Barmby (London, ON, Canada)
- Melissa Santos (Portland, OR)
- Brian Brennan (Mozilla, Brooklyn, NY)
- Chris Greenough (STFC, UK)
- Christina Magkoufopoulou (TGAC, UK)
- Rémi Emonet (University of Saint Étienne, FR)
- Daniel Hocking (Durham, NH, USA)
- Ofer Bartal (Rehovot, Israel)
- David Kua (Toronto, ON, Canada)
- Asela Wijeratne (Wooster, OH, USA)
Attendees (evening):
- Greg Wilson (Mozilla Toronto)
- Naupaka Zimmerman (Woodside, CA, USA)
- Bill Mills (TRIUMF, Vancouver)
- Daniel Braithwaite (Chicago, IL, USA)
- Dave Jones (State College, PA, USA)
- Chris Waigl (Fairbanks, AK, USA)
- Alex Demarsh (Montreal, QC, Canada)
- David Rio (West Lafayette, IN, USA)
- Trevor Bekolay (Waterloo, ON, Canada)
- Ryan Williams (Ames, IA, USA)
- John Corless (Dallas, TX USA)
- Margaret Leibovic (San Francisco, CA, USA)
- Raymond Yee (Berkeley, CA USA)
- Shirley Sanchez(Boston, MA USA)
- Scott Chamberlain (San Francisco, CA, USA)
- Vicky Schneider-Gricar (TGAC, Norwich, UK)
- Denis Haine (Montreal, QC, Canada
- Michelle Hall (Cambridge, MA, USA)
- Sharon Benjamin (Falmouth, MA, USA)