Soldering on to connect #MakerEd plans

Preparing for the unknown:

Next week I’ll be facilitating an Ada Day with a group of students who’s activities will be centred around student voice and digital making.

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They’ll be challenged to creatively visualise and solve real world problems, which are linked to their school’s global citizenship curriculum.

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Following this first session, the students will be able to use their code with sensor nodes and link their environmental data and findings to the Connected Hull dashboard and coverage through The Things Network.

First things first, though.

  • Discover
  • Interpret
  • Design
  • Code
  • Test
  • Debug
  • Test again
  • Share

Soldering On

Through this approach we’ll explore the benefits, applications and considerations of big data, GPS metadata and privacy of personal data to add to future project builds.

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Planning for the unknown?

We’ve collated the start of a resource bank to equip the students to visualise their data and solutions.

Final outputs will only be discovered next week.

Exploring paper circuits before a live data feed

I’ve got an idea in mind to create a piece of artwork to visualise some live data, and wanted to see how quickly we could create a starter paper circuit.

Ordering Chibi Lights from the good folk at Pimoroni meant a first attempt notebook circuit within 24 hours and a whole lot of ideas to follow up.

A completely different context here, with a Spanish and dance theme explanation to follow 👠

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‘Quality’ decision making without peer pressure using Picap

Christmas came early last week.  Got to admit that we became embroiled in Quality Street-gate with forceful opinions expressed about which choc should have been replaced.

The trouble was that peer pressure swayed some, and anecdotes through rose tinted spectacles blurred others, into thinking that another choc should’ve been booted first.

Out came the first choc box of the season with a bit of tinkering with the Picap.

Soon we had a set up to give a truly anonymous and representative taste test and decision.

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Must be noted that we’d started with a healthier option for a blind taste test of tomatoes from a plant grown and sold by Ganton School in Hull, and another from a well known supermarket chain. The data confirmed our hunch – the school tomatoes were far more tasty 🙂

For both trials we used the simple touch Python script that allowed us to collect data showing which electrodes had been touched and released.

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And the verdict?

The data suggests that the orange creme should’ve been ditched before the toffee choc.  In our humble opinion of course.

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Strictly More Pi – Take Two

A year ago I asked the question, ‘Will I ever know what it’s like to dance like a dancer?’ It feels timely now to explain the non-stop questions that have followed and the resulting decision.

Initially rhetorical, I managed the answer on Monday this week. That was 24 hours after competing at the UKA Premier Medallist of the Year Festival at the Winter Gardens in Blackpool. Scroll and whizz to the bottom for the result, and you’ll see why it also took another 2 days to get back down to earth and be able to hold a conversation again.

Or read on to hear how the first iteration of ‘Dance Bot’ grew wider in so many ways; not least with the team of support which grew and with whom I have such deep respect for.

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Empress Ballroom 4th October 2015

Background:

Initially realising the significance to me of the meta learning approach from Tim Ferriss; deconstructing learning and concentrating on ‘material not method’, went hand in hand with the first Raspberry Pi-Cam and Google Glass project with my fab-u-lous teachers at North Leeds Dance Academy.

Using an AR perspective with Pi-Cam, gyro data for a performance analysis focus and reviewing a partner’s steps through Glass, the road to ‘More than steps in the ultimate dance algorithm‘ for me began.

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Lightbulb learning to learn moment

It was possible and if I pieced together a work-life balance that was about to significantly change again with the Jam Packed Computing Tour then I could actually learn substantially more through dance along the way.  That was always the fundamental aim.

Rationale:

As an educator the prospect of learning something new gave me opportunities to test ‘learning to learn’ strategies and explore my own preferred styles and retention.   To turn the blurred lines of opportunities from a range of tech interests from work, additional projects and social circles made sense when they became the tools to realise the ultimate dance algorithm.

Using data analysis with collection through physical computing and wearable tech projects was important to me to integrate performance analysis and data science techniques.  I wanted it to inform my progression of learning and lever next step questions.

So you think you can dance? Me, myself and Pi?

Step by step data approach

That alongside performance techniques that I knew I needed to incorporate into ‘Dance Bot’, including psychology and attitudes to successful learning approaches, was a tough gig for any teacher.

Not least, knowing that I wanted to question every step literally every step of the way as a learning tool and track impact of those personal gains.

Towards Outstanding through Outstanding Teaching:

To my teacher’s surprise early on, my confidence with dancing weaknesses was perhaps a little too strong. Flat refusals to learn using some strategies (knowing they wouldn’t make a difference to my understanding) were recognised from the start and luckily the somewhat hidden-before-then data geek in him emerged too.

I renamed the low benchmark as ‘towards outstanding’ and each lesson became more and more in awe of the range of successful teaching styles and visualisations used at the academy.

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Learning to Learn with NLDA

The tech and performance strategies were always tools in addition to the teaching styles delivered across the academy, so on the basis of a deconstruction approach using data, only the latter was bespoke.  And my preferred learning style with progression, of course.

It was my intention to use tech to enhance my own development which encompassed dance performance and activities relating to learning. Often directly linked to work and other projects.  For that I’m grateful to the team of teachers who supported me with the approach and gave me the opportunities to tinker through dance.

Using data to improve performance:

Realising the elements of the deconstructed dances which would impact most on specific and overall performance meant that I could explore projects with a range of tools:

  • Physical computing devices with an accelerometer and gyro to impact on parts of a dance such as the spin turn. I have a track record of over-thinking and ‘bottling it’.
  • Wearables to track, collect and analyse posture and body balance. My top line and frame were fundamentally flawed at the onset; now they’re ‘towards outstanding’ 🙂
  • Wearables collecting data with sleep patterns and general health and movement tracking.

And other tech tools:

  • Circuit tools and electric paint with dance shoes to act as a trigger to support me with heel and toe. Yes, really, it was very much needed!
  • Wearables to bling up the dress with LEDS – when the rules say no rules it makes you start to think!  In the end the dress didn’t hold any LEDs as it was still the accelerometer that held more impact with the turns.
  • Google Glass for partner perspective.  Again, back to the Four Hour Chef re-reads and experiences.
  • New Spotify Playlists – really, the roads to Hull and Salford this last year have paved the way to many a counting the music and hearing the beat sessions. El Tango de Roxanne became a firm favourite!

The wider team:

Spending more time at the dance school and touring with Jam Packed Tour gave more opportunities to engage with a range of people about their learning to impact on my own progression.  I’ve taken advice from dancers and non-dancers upwards of 3 years and perhaps the latter’s advice of ‘high on your toes and smile’ was one of the most significant for performance!

I asked some of the children at a recent exam about their learning focus, as a way to explore my own potential marginal learning gains, and got incredible insights that I’ve used at competition level.  As I’ve deconstructed particular dances, their pointers about performance, posture and reach have been powerful.

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Marginal Learning Gains

Through Jam Packed there was also the visualisation moment of truth when I learnt that the morning shower was the best time and place to run through my finest performance. One of many learning nuggets!

Sounds insignificant but we shared an empathy with the meta learning approach for like-minded individuals with a computational thinking focus.  The world of flamenco dance merged with Maker and added to my dance performance…..

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Visulalisation Techniques

I also met a number of fellow ballroom dancers, young and more mature, on the tour and swapped stories of learning gains and difficulties as I asked for tips.

Those additional variables to add to the steps in the algorithm became increasingly important as the significance of the overall performance itself became clear.

The thoughts, anecdotes and tips gleaned from others including contemporary dance teachers, computer scientists, a psychologist, a team of medics including a psychiatrist (yes – that became more useful towards the end), family and friends all fed into the design of the ultimate dance algorithm.

‘Hold your nerve’:

It was perhaps 3 weeks ago on one of my lonesome commutes to Hull that the enormity of that support team hit home.  As the year progressed the team increased and general conversations which had started with ‘Have I told you that I’m learning to dance?’ had shifted towards specific questions about my latest focus.

The realisation was pivotal because in that moment I dismissed everything I’d read and assimilated through reading The Chimp Paradox and momentarily resorted to Take That to clear my head.  A mistake that didn’t take long to remedy and which impacted highly last weekend.

As last minute doubts, uncertainties and fear of forgetting the routine set in I managed to counteract the negative thoughts. Probably a little too much as the final positive self-statements were closer in accent and confidence to a Jack Nicholson performance rather than my usual talking manner.  Must’ve been the dutch courage (gin).

Just one of the strategies used with the intention to meet the judge’s criteria on the day, and keeping my mind focused was tantamount to success. I never did find a tech support tool to help me keep my head left and attention on the dance straight and narrow!

Moment of clarity:

Ten minutes before I danced I asked a young dancer from the academy about her thoughts each time she steps onto the floor. With a look of puzzlement (why do I need to ask, it’s common sense?) she told me, and as a junior champion I hold her opinion highly:

‘Nothing, I don’t think anything.  You know your steps, you know your routine and you just do what you have to do.  There’s nothing else to do, is there?’

At which point The Chimp Paradox came back as a strategy and not as a voice.

Teaching. That’s been the crucial element for me with the biggest impact on my own performance and confidence in my abilities.  I knew that anyway and I’d been on a learning journey with data to support those decisions.

For that reason I will forever be in awe of the oustanding teaching, energy and motivations from Nicola, Mark and Ashleigh x

What happened, then?

In simple terms:

4 dances in 4 stages resulting in 4th place in the final.

#a-maz-ing 🙂

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Waltzing into the final

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Not an LED in sight!

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4th – eek!

Where do I need to be and how do I get there? I knew that as soon as I left Winter Gardens. Put simply, the deconstructed elements make it clear for me to understand after listening to exceptional teacher guidance.

Does more noise mean more collaboration at the Leeds’ Raspberry Jam?

Absolutely not?

But could it mean more Maker style Meet ups as we move forward?

When the team from York Hack Space joined us at this weekend’s Raspberry Jam our Maker Space got a tad more ambitious.

 

 
An increased range of activities and projects, incorporating Raspberry Pi and Arduino as the basis to hack with, gave way to more conversations, thoughts, ideas and inspiration towards next steps for everyone.

And actually, some new boards for some to consider too, but all to encourage collaboration and supporting ideas to share.

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Robotic Art – click for more info

What could happen next? Who helped who?

  • A year 8 student brought along a Raspberry Pi photo booth project that inspired a couple of teachers to consider projects with that theme for enrichment activities.
  • Another Year 8 student gave us an update about her Raspberry Pi robot project and what her future plans hold.  Extending her remote control hack?
  • Using Raspberry Pi with a 3D printer project to explore and stretch the Cannybot activity ideas developed during the day. Racing corner might appear at the next Jam!
  • The Water Color Bot from Super Awesome Sylvia gave another area to consider STEAM, different themes for projects and to launch numerous conversations about engaging inclusive and opportunities through computing. At it’s most basic level, from plug-in, design and print, to hack opportunities each idea shared an enjoyment whilst developing and extending skills.
  • Arduino-based pledges to explore and hack with electronics activities – lights, camera, action.
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Toolbox to launch a 1000 ideas

  • Wearable Tech plans using a range of tools as inspiration and stimulus.*  Time to say thank you for those #ProjectBlackpool ideas for me!

And what about the post title about noise?

Well we used the Raspberry Jam as a testbed for a data project and to explore more ideas for an upcoming community project in the city. Digital storytelling using data as a focus but with a creative output.

What will be that creative output?

I have no idea!

That’ll be decided by the group of young people who will build and hack their own project around the technology we provide, through a toolkit, and which they could add to.

The community had their own ideas at the Jam and it also gave more activities to explore after the Raspberry Pi workshops.  The Leeds’ Maker community will also be involved with this local project in September.

What we’re excited about most of all is the students adding their ideas stamp and creativity which they’ll share at a Leeds Jam. They’re Smart Citizens of West Leeds and one device they will use is the Smart Citizen kit:

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Smart Citizen

But will they build a project indoors or choose to create and make an external collaboration to tell their story?  Whilst I don’t think they’ll be showcasing though a spreadsheet, we’ll wait to see where they export their csv data and the resulting visualisations and models.

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Excel for a reason!

There were peaks in noise levels at the Raspberry Jam.  The data confirms that and also guides us as to when the device was internally mounted and when we hacked the deckchair outside, and planned a storytelling idea overlooking Leeds Dock.

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Click for more info about Space Hack

More noise through more conversations or challenges and shouts with Space Hack?  I like to think they’re both the same 🙂

More resources:

Codebug – interactive coding and wearable tech

Bare Conductive – electric paint and Touchboard

When cycling data becomes the input, not the output, with Raspberry Pi

Twelve months on from Le Grand Départ of the Tour de France in Yorkshire.

A year since the peloton passed through North Leeds on it’s way to the ceremonial start at Harewood House and was captured by a group of young children using their Raspberry Pi mini computers.

Planned, coded and created using window sills and trees along the route to create a time-lapse video to share as an output.

A data output of moving images as a digital storytelling piece and fitting creatively into the Computing curriculum.  Well, if it had formally been in place then.

So what can happen in a year if the TdF legacy conversation is explored but we consider Computing this time?

Time-wise some of us, particularly in Yorkshire, think back to those iconic images and forever lasting moments shared a year ago, particularly as the 2015 start approaches. Which made me think about using exactly those to look at project opportunities, activities, resources and more than anything perception and confidence with Computing from a work and social/community perspective.

We’ve had a Raspberry Jam in Leeds this year, another one scheduled for July and plans to introduce a regular diary date.  All very timely!


 
The Cote de Buttertubs Pass section of the race is the still image in my mind which encompasses the spirit of last year’s TdF in Yorkshire. So could we utilise Strava with cyclists on that particular section of the route and this year use their data as an input with Raspberry Pi? It’s an attempt to shift from the peloton as an output in a time-lapse to actually using data from the route as the input this year.  No pro-cyclists in 2015 as we move towards more open data and Strava with local riders : )

  • So how could we build contextual models to tell the story of one or two cyclists on that ascent?
  • Which tools could we use and whose experiences could we tap into?
  • How could the data be visualised and would one method create more understanding than another?
  • Would that depend on the creator and/or the viewer?
  • Is it possible at all to use the data from Buttertubs to share a rider’s experience?

Here’s a digital storytelling piece about one cyclist’s ascent of Cote de Buttertubs using their speed and cadence data. Through a sonification activity, Sonic Pi is used to blend three elements giving a different tone, output and ultimately a very different story of what the data would ordinarily infer during this ascent.

  1. Cadence data is used for the melody
  2. The small range of speed data (km/Hr) can be heard as notes using random selection from that range
  3. Listen out for the Queen ‘Bicycle Race’ undertones

For computer scientists, the Sonic Pi script below will show a very long winded approach to coding.  We talked a lot about possibilities, what we wanted to incorporate and how we wanted to use the techniques to display differences in the data and to try to create an atmospheric piece.  And we coded as we talked, and tried to understand the storytelling element through the data as we went along too.


 
As a bit of context, here are some thoughts and considerations discussed in planning:

  • Freddie Mercury was inspired to write ‘Bicycle Race’ after watching the 1978 Tour go past his hotel.  He was in France writing at the time, and as he was inspired and we recognise the local impact of legacy from TdF, then we wanted that piece of music incorporated.  It also gave us the impetus to collaborate and blend numerous elements and data sets into one piece whilst progressing our Sonic Pi experiences.
  • Conversations with music tech students at a recent Jam cemented planning thoughts after we considered the range of data.
  • Cadence was the chosen data to use as the melody due to it’s perfect fit with midi notes.
  • The small range of speed data, through km/hr and between 13 – 19, meant initial considerations to convert to integers and then into base 16 or base 8 to form chords.  Then we changed to learn more about using random numbers from a range in Sonic Pi.
  • Length of notes, amplitude and sleep were variables used to try to capture the storytelling element.
  • Above all else could the output ever tell the story and accentuate that from the rider’s perspective?  We thought about it and went in a completely different direction.  Abstract really.  We wanted to manipulate the data but the output would be melodic. Almost calm : )

Other resources and project ideas to build contextual models from the data?

High Speed Racing on Figure of Eight track from Cannybots on Vimeo.
 
Next month we’ll look to use the Cannybots racers at the Leeds’ Jam as we intend to race the data from two riders ‘on the flat’.  A sharp contrast to the ascent but one which fits with modelling using the sensors on the racers.  The speed data can be imported into this Python script – finish line report to follow. We’ll also take a peek at how the data could look as blocks in Minecraft.

  • How could and would heart rate data be visualised in a virtual world?
  • What if we added Buttertubs to the Minecraft World and built structures based on the data?

Maybe.  But then again our local Minecraft expert, who incidentally stood and watched the TdF at that very point, is working on the Leeds’ Minecraft map so perhaps we’ll explore that further in the Autumn term. 

Link to data & Sonic script on GitHub:

Song from the Earthquake Epicentre

Given the task to report on a natural disaster, to demonstrate learning from a mini topic, and using Sonic Pi is a decision made in a millisecond.

It’s a creative homework and that means the freedom to work on a fictional piece. All part of that creative decision making.

Explore a local example, consider appropriate ranges of data and ditch Minecraft to concentrate on more creative projects.

That final point sticks with me as a parent : )

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Creative coding?

Rope in your dad by installing the tools on his laptop and leaving him with a lasting Father’s Day gift.  An introduction to sonification and a flashback to the early 1980’s post-punk and electric dance music days!

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