Computer science taught as an art

I've been involved with learning, teaching and creating for all my life. During my formative years (in-utero to shortly after high-school graduation) I was focused on getting what I needed to finish. I was also involved in a lot of art (music, graphic design, crafts, dance, theatre) but my socially encouraged (my parenting) focus was on math and science. Needless to say, I have had my feet firmly planted in both art and science my whole life. I guess most people are this way, with different ratios of art to science. I really feel I continue to straddle both these areas as I pass my 1/2 century mark. What this has given me is a deep appreciation and engagement in both art and science. This is why I am more broad than I am deep. And this is why I have learned art as much as I have learned math and science.

Now I am an enterprise architect, educational technologist, computer scientist, teacher, visual arts performer and all around nice guy (well I hope). I still draw and paint, play music (the best I can) and dance in the open. I encourage my kids to engage in art more than science. Surprisingly, my kids math and science skills are good. I do think there is a connection.

I also think computer science can be taught very well as an art. Particularly, in the early stages of learning computer science. Why? Because, it needs to be done with reckless abandon and with the freedom to make a mess. You need to be able to stop half-way and throw it away. You need to be able to change it into something never planned. You need to be able to break something, and then fix it. You also need restraints through assignments (or learning themes), focused subjects, a palette, skills and abilities, uncertainty and little preparation, it all needs to be inspired and interpretive. I also see taking risks and "feeling stupid" is safer with art than science. Doing a scientific experiment seems more serious than dancing like no-one is watching or painting for yourself. Art seems more reckless than science. It is this recklessness that makes art more accessible to learn than science. I also think there is a lower barrier to entry for art than science, though I don't think it needs to be this way.

How I perceive creating and learning art.
My participation in the arts comes in two themes; the visual make things (graphics, painting, architecture, woodworking, and building) and in folk music and dance. How do I learn new things within these realms; by doing, with a whole lot of reading, research and seeking out those who have done it before. How do I believe it best assist to others learn; by involving them, and pointing them toward understanding how they themselves learn and encouraging their own research practices. Together we do things, I've built and created many things with others and the conversation and collaboration is a beautiful thing. Bringing together music and dance is an amazing collaborative effort. Best done with a willingness to fail, and the patience to persist. One of our best dances is tri-martal-o (it took two years to develop), is hauntingly beautiful, the music is inspired and the piece is way fun to dance. The important aspect of learning art is to dive in, create and participate as soon as you can. And remember, make a mess.

How I perceive creating and learning computer science.
Immediate feedback is the way! Being able to get something working by using the tools and techniques immediately is paramount to learning computer science. Programming something and then seeing it run, render, compute... is preferred for learner engagement. Once this immediate feedback has been experienced, the opportunity to create has been fulfilled, and a good number of computing science tasks have been completed then the deepening and complexity can begin. And this deepening and complexity needs to grow iteratively with continued immediate feedback and fulfillment. It should almost be like playing an instrument or creating art; repetition, creation and fun.

I believe it is also important to understand computing science as a creative and where it fits within the big scheme of things (historically, culturally, epistemogically, and algorithmically). This helps to put computing science into life context. Where it fits with being a human being, and this is where it gets interesting. The ability to take working ideas out of your brain and use them (in other ways and experiments) within a device outside of your head. This is computing science, and it is unique in history. For thousands of years we have taken ideas out of our heads and created things; first, wall paintings, then tools and writing, then machines and engines... but now, we can re-incarnate a working idea in another device that can process the idea, and use it with other peoples ideas, or more of our own ideas. And we can process these ideas as experiments and run a collection of ideas for days with different inputs which influence further ideas.

How do I see teaching computer science as an art? 
Create, make a mess, work with others, make... this is why I see the maker movement so positive. And why the webmaking initiatives currently underway as the right way toward teaching computer science. It creates a low barrier to entry and encourages learning with reckless abandon while on a journey of skills and knowledge development. Webmaking also takes learning computer science into the realm of social learning, which I consider more closely aligned with learning the arts than the sciences.

But how would this work for the more complicated computer science topics? The solution is in how more complicated art projects are created. They are more collaborative efforts, where the more experienced are given the complicated tasks and have to be sure their direct collaborators are also engaged. And there is a whole bunch of healthy collaborative critique going on. Look at how a performance art piece is created, learned and performed. What can be taken from this process and applied to teaching the more complicated aspects of computer science.

In my opinion one of the best books when considering the creation of computer software is written by Russell Shackelford and titled "Computing and Algorithms", I've used this book a number of times when teaching entry level computer science. What I fond strongest in this book is how it connects the creation of computer algorithms (software) with art from the scientific perspective. Or at least that is how I read it...

So in the end when teaching computer science as an art it also comes down to practice, practice, practice... if you want to be a good artist, that includes a lot of practice. If you want to be a good computer scientist, that also takes a lot of practice. The key is to find fun, creative and collaborative ways to stay engaged, and treating the learning of computer science as an art will keep it more engaging. Regardless of age. And as the projects and learning become more complicated, increasingly engage others who are peers and mentors. Find the fun individually and as a group.

Big Data; Similarities and Differences

Compare and contrast; VLDB and Big Data.

I've been a data guy for over 25 years. My undergrad degree is in Technology with specialty in Database Management Systems (DBMS). The focus of my whole career has been on the data... I believe if the data is wrong (even just a small amount of it), most of the other related IT is pretty much useless and any reporting or analytics should be taken with more than a little skepticism. In my opinion, its all about the data, and it's correctness or accuracy. This has been a cornerstone to my career, all I do has elements of advocating for data quality.

I continue to be entrenched in data related projects. My current project is focused upon opening up Machine-to-Machine (M2M) data exchange using satellite networks and RESTful API's. Very cool and very relevant to open data / big data. I continue to work with and read about data (big and small)... but, I don't see that much has changed from the Very Large Database (VLDB) discussions of the past 40 years. Don't get me wrong; the amount of data has never been so big, the ability to process data has never been greater, the algorithms and models have matured, and the technologies to support big data have never been better. I see more similarities than differences when talking about big data when including references to VLDB and past data analytics.

This blog post sets out to describe the technologies and processes that support big data and how these are more similar than different to big data processing of the past and present. This post describes the accompanying image from its top to bottom; with descriptions provided for how I see the real world as related to data and the purpose of each step (or grey box) in the big data realm. I do believe that many of these boxes (or process) have remained the same in relation to the processing of data (big and large).

Real world

Sources of data

Data comes from many sources! It is good to keep in mind that every small amount of data can be collected when considering the entirety of data creation vs. data collection. As an example; data is created in massive quantities as every person moves through their day. Heart rate, body temperature, calories burned, eye movements, blood sugar levels, foods eaten, decisions made, walking pace, etc, etc... And all these data attributes change throughout each persons day. All of this and an massive number of other data attributes is what make up data creation in the real world. When you consider all this data is created by every person, every second of every day it becomes a massive amount of data creation. This example only includes people as the sample, data creation is even greater when every object on the planet could be considered as a data creator.
The point I am wanting to make is that in the real world there is a lot of data being created all the time, and only a small amount of it is actually being collected. What is being collected is already considerable and comes from a plethora of sources (and to consider this is only the beginning of data collection in an internet of everything world). This is a high level list in what I see as the current set of data creators / collectors;

• log and event data - server logs, click-through events, page views, API's called, etc...
• transactional data - traditional data processing systems across all industries / organizations / institutions.
• multimedia data - movies, images, photographs, music, etc.
• geolocation - latitude, longitude and other relevant location / movement data
• unstructured data - unorganized or having no data model or pre-defined structure.
• device data - data made available through small or handheld devices
• sensor data - data coming from sensors attached to objects (remote or otherwise) - in time, this is where the greatest amount of data will originate.
• streamed data - audio, video, astronomical, etc.
• human data - data about people, in its broadest sense.

Collection
The methods of data collection have remained similar over the last 40 years (well, much longer, but...). I see data collection as capturing the details of a real world event and making it digital by recording the event using an electronic device. This capture occurs in many ways as described in the previous list of creators / collectors. The important part of collection is in consolidation, where the relevant data sources and attributes are identified and brought together (either physically or virtually) for processing. I do agree the greatest change for the current big data is the three V's of big data; volume, variety, and velocity. I do believe the collection methods are more similar than different over the past 40 years, they are just happening at greater volume, with more variety of sources, and coming into systems with a greater velocity.

Processing (ECTL)

Preparing the data

Processing is about getting the data from many different sources into a state and place where it can be analysed. I cut my data processing teeth with Extract, Transform and Load (ETL) work. I consider ETL as the harvester of data. I see processing as the consolidation of many a data sources by Extracting the data from the data collection systems, Transforming the data from these different sources so it will fit together, and then be Loaded it into a system (usually a data cube type technology) for analysis and reporting. As time progressed I began to include a data Cleanse into the traditional ETL process. Cleansing is about preparing the data for a greater transformation rate. Not all data can be transformed into a common data store, cleansing increases the success of the transformation. And once the processing is complete the raw (or originating) data may be discarded for results have been calculated or the meta-data determined. This discarding does not occur in all processing situations, but keep in mind the end result of processing may be cleansed and transformed raw data or some amount of calculated or meta-data. Again, I don't see this has changed much over the last 40 years, except for the increase in volume, variety, and velocity. The methods and approaches remain the same...

Storage
Storage is where the data resides after it has been captured and processed. This may occur in real-time and reside in an in-memory storage rather than physically stored on a disk or other solid-state device. The data may also reside in an Operational Data Store (ODS), in a Data Warehouse (DWHS), in files, or as raw data. The storage may be long-term or short-term, there does need to be a place for the data to be stored so it can be analysed and used for calculating results or developing insights. I do see storage as being one of the areas creating differences in the way big or very large data is stored, processed, and analysed. In the past, data needed to be stored to a physical device, like disk. But now virtual memory is large enough, at a reasonable cost, where storage approaches are allowing the database (storage) to be entirely in-memory. This can fundamentally change how large volumes of data can be processed, and how database technology is implemented. The traditional row-locking database is no longer required as the latency created by disk input / output (IO) no longer exists when the whole data store can be in-memory. The approach to database technology design can fundamentally change without needing to manage the issues of on-disk storage as a part of the traditional database.

Exploratory Data Analysis
Once you have your data all in one place (or as you are bringing the data together in one place, Storage) you can start with Exploratory Data Analysis (EDA). I think of this as play; laying all the data out on the table and looking at it from different perspectives, flipping it around, stacking it in different ways, molding it into the shapes that it can stay in. Using tools and techniques designed and developed to begin sense-making with the data collected. Remember, its exploratory. And other than the wonderful new technologies (or tools) that have emerged recently, the approaches to EDA haven't changed that much over the last 40 years.

Data Cubes / Multi-dimensional Cubes
I like cubes, particularly multi-dimensional cubes. Always have, even as merged data sets. There is something that makes sense to me in regards to loading related data sets into a technology that builds insight into the data relationships. Online Analytical Processing (OLAP) is a multidimensional analysis approach that has been around also for 40 years.

I do see EDA and OLAP as similar, but I believe the tools and techniques available to (or developed for) EDA as broader and deeper than the tools and techniques associated with OLAP.

Bringing intelligence to the data

Business Intelligence / Data Analysis
The term business intelligence always fascinates me for historical reasons; it is well described how the term was first articulated over 150 years ago. The idea of bringing together disparate sources of "large" data for competitive business advantage isn't new. What is relatively new (last 60 years or so) is the use of computers and digital data storage for the processing and analysis. I do consider business intelligence and data analysis was born out of the data warehousing stream of big data and a lot of the algorithms and statistical models will find there data processing roots in traditional large data initiatives. I consider machine learning the new comer in the big data realm, for it is only until recently that the volume of data and the commodity priced hardware, software capacity, etc. has created the thinking / need behind machine learning.

Machine Learning, Algorithms, Statistical Models
I see the troika of machine learning, algorithms, statistical model as the intelligence side of "big data". Collectively the three hyper-links in the previous sentence give great descriptions of these three parts of deriving intelligence and knowledge from data. The big part of these three is that they automate the creation of the "intelligence", they allow data to be consumed and then "knowledge" created so decisions can be made in real-time (by the computer, or network; depending how you look at it) to impact the way further information is presented.

It is important to note that machine learning, algorithms, statistical models (as indicated by the data flow arrows) often get data directly from storage (real-time or otherwise) and don't include the EDA step. This is often due to once data and its sources are understood no more exploration is required and the data can be accessed directly for intelligent processing.

Data Product
A data product is information (precise or otherwise) that has been derived from Business Intelligence, Data Analysis, Machine Learning, Algorithms, or Statistical Models. These products can be added to the attributes of another product or be used to focus a decision or alter a user experience to better suit the specific viewer. In its simplest terms; a data product is what is harvested from your Google search terms to display focused and specific adds on your views of subsequent (and seemingly unrelated) web pages.

http://selection.datavisualization.ch/

Reporting, Dashboards, Visualizations, and Communications
One of the areas where I continue to be amazed is the growth and innovation within the graphical representation approaches to displaying data. A look into some of the open source frameworks will amaze - a look at the D3.js library is an excellent example. I believe their are four main aspects to rendering data, these are;

• Reporting - I consider reporting to be text or graphical documents (printed or otherwise), spreadsheets, emails, etc. that report on information or knowledge derived from the processing of data. 
• Dashboards - I consider dashboards as the digital single page rendering of current an important decisions for the day-to-day activities of a business, enterprise, organization, etc...
• Visualizations - the graphical visualizations of processed data 
• Communications - outbound communications derived from data processing can be in many different forms. Using rich media and emerging technologies to increase variety, frequency and management of communication channels can assist with big data efforts.

Decisions
Decision differ from data products as they are cognitive / intelligent activities done by people. They use the reports, dashboards, visualizations and communications with provide the knowledge to make informed decisions. All of the steps in gathering, processing, and analyzing the data down the right side of the image leads to supporting the human activity of decision making. Even though the process are similar within big data and traditional large data the end product in the traditional is most often as input to people, where the big data side creates data products used by machines / computers.

Similarities and Differences
I dislike using percentages to indicate differences, but; I would say that the tools, techniques, and approaches to big data compared to traditional large data is > 80%, where there is an 80% similarity between the two. Over the last 40 years big data has been present (under different names) and used in decision making, research, science, etc... The tools, techniques, and approaches are a trajectory that has build upon what has happened in the past; So what we have today with big data has built upon many technologies and techniques developed over the past 40 or more years.

Shepparding multi-stakeholder architectural decisions

What fun. I recently moved with my Family from an island off the west coast of Canada to as far east as you can get in North America; St. John's, Newfoundland. One of the benefits of this is I can become more involved in the technology community. My previous island life made it prohibitive to participate in social and technology events in the city. Now that I can participate, I will.

St. John's has a number of technology conferences (or events) in the fall. And one of these is aligned with the bsides security conference. I decided to participate by proposing a lightning talk, fortunately my talk was selected... what fun. The title and abstract of my talk is as follows; and will allow me to discuss my experience with shepparding multi-stakeholder architectural decisions to agreement.

Title: Defence in Depth: Approaches and Importance of Enterprise Architecture Security Decisions
Abstract: In this lightning talk we will explore one approach to getting multi-stakeholder agreement on Enterprise Architecture decisions focused on a defence in depth security model. Corporate enterprise technology environments can be large and complicated. And when it comes to making changes to the internet facing security environment both rigorousness and resistance to change increase. These increased challenges can be overcome with good project / process management, solid end-to-end architecture, and a comprehensive decision making template. In a nutshell, this talk explores the enterprise architecture decision.

Defence in depth is an age old practice.

Fortunately, over the last 15 years many of the projects I have worked on were internet facing and had security and privacy issues baked into the project. The bigger the project the more technical stakeholders were involved in designing, building and deploying the solution(s). utilizing all these technical people can make for a stronger and more comprehensive and well engineered solution. Coming to agreement across all the stakeholders can be difficult, for they sometimes have opposing tasks and responsibilities that are counter to another. With good process and a strong engineering mindset it is possible to find the common ground and build a solution where all stakeholders technical constraints can be met. This talk explores this process in the context of altering an existing network infrastructure and related governance groups to deepen defence in depth approaches to enterprise security.

Book Review: Buccaneer Scholar

This book hit a home run for me in many ways;

1. it chose a buccaneer (sailing) theme
2. it told a good story with good imagery
3. it challenged the status quo in education with personal evidence
4. it provided a map to the self-directed learner
5. it recognized the importance of organizing your learning goals
6. it offers the adult learner an alternative
7. it shows a life can be great, with amazing achievements, without a formal education
8. it is inspiring to think what James has achieved through self-education

What Buccaneer Scholar did best is got to the root of it all by driving home the point that scholarship is about learning, personal learning. True scholarship is not about the certificates and institutional recognition but about learning new things, deepening your own knowledge, and being able to take on new challenges due to your ability to learn, with little or no guidance. In the end learning is about personal fulfilment, personal commitment, finding a satisfactory way to make a living, and honouring your life's journey!

Thanks James!

Course Design Sprint

Outstanding!!! Early last year I wrote a post playing with the idea of a course design sprint. The main idea being the development of a full online course in a reduced amount of time. less than five days, or some low number of days like that. In my post I dreamt of having the time to execute on the idea to see if it would work.

Agile Instructional Design Sprint

Well it turns out my friend Billy Meinke ran a course sprint this past weekend.  The course was developed as a launch course for the School of Open during Open Education Week (Mar 11-15). I really don't want to take the wind out of their sails... so you can read about all there great work yourself. I'm just so flipped out they proved this idea out! Kudos to everyone involved, particularly Billy!

• http://billymeinke.wordpress.com/2013/02/11/open-science-course-sprint-an-education-hackathon-for-open-data-day/
• http://creativecommons.org/weblog/entry/36600
• http://blogs.plos.org/scied/2013/02/21/guest-post-open-data-day-sprint-courses-and-hackathons/
• http://onlinelearninginsights.wordpress.com/2013/02/26/a-course-design-sprint-my-experience-in-an-education-hackathon/

The Solution Architect

This concept map is a compliment to the previously posted "Educational Technologist" post. These two concept maps together provide the visuals for my identified domain of study as I work through the P2Pu challenge to declare my OnPhD candidacy. This concept map contains the two related concepts of Solution Architect and Information Technology (IT) Architect. Many of the skills and knowledge for the solution architect are a part of the overarching role of IT Architect. It is my intention to seek a research domain that occurs within the intersection of Education Technologist and Solution Architect. I believe bringing greater architectural discipline to the educational technologist role will assist greatly in growing this important role within the rapidly innovating educational space.

Teach people to teach themselves

What stands out for me most is that we need to teach people to teach themselves. Everyone needs to design and develop their own learning methodology and implement for the rest of their lives. This methodology needs to include and recognize other people as places where your knowledge resides. People also need to alter the methodology through time, but it is still their own learning design methodology customized and upgraded for them and by them. I believe people can begin to get meta-cognitive during their teens. I think this timing would be different with everyone. But when a person is ready they need to develop (with rigor) their own learning approach.

The Educational Technologist

Gears of my childhood

I am involved in the current running of Learning Creative Learning with MIT and P2Pu. A fantastic online course which is prompting much reflection and confirming much of what I am doing with inspiring adult learners. I am definately on the right road!

This weeks activity is to;
Read Seymour Papert’s essay on the “Gears of My Childhood” and write about an object from your childhood that interested and influenced you.

I struggled with this. I didn't have an object like Papert had, something that I grew my learning around, something I would use to visualize or conceptualize my learning. Something I did have, and still have... is the bicycle. I rode my bicycle everywhere, to school, from school, to the park, just up and down our dead-end road. My social life was around the bicycle for many years, we had a bike club on our street. Every day and every weekend we would meet-up and do things, the bicycle was a constant.   I didn't think about the bicycle in direct relationship with my learning. It never was a gear to my learning. I would rather see is as a foundation to most of what I did, and played a big part of forming who I am today.

• The bicycle provided a freedom to travel great distances, unsupervised. Today, I love to travel.
• The bicycle provided me access to a number of different social circles and friendships. Today, I know many people and socialize across social and economic domains.
• The bicycle provided me travel to many different events. Today, my interests and studies are broad.
• The bicycle allowed me to escape the restraints of what was expected of me. Today, I seek (with confidence) alternate routes to desired outcomes.
• The bicycle was easy to take apart and put back together. Today, I am constantly taking things apart and putting them back together, often improving them along the way.
• The bicycle caused me injury, but I always made it home. Today, I pick myself up on bad days and have persistence to keep going.
• The bicycle took me places I could not have otherwise gone. Today, I am still curious and follow thoughts, ideas and inspirations to places I would not have otherwise gone.

I know that the bicycle isn't the same as the gear as described by Papert. I never used the bicycle as an analogy or image to base my learning. The bicycle provided me a freedom to become an autodidactic.

Badge Clustering

As my digital badges seminar series came to an end I was doing a lot of thinking about badge clustering and what I meant by the term. With a little creative thinking, and some fun, I borrowed and edited three clustering terms and applied them to badges.

Badge Cluster

noun, epistemology:
A bunch of badges (ranging in number from a few to hundreds) which are bound to each other by their mutual knowledge domain as defined by the badge earner.

Open Cluster
noun, epistemology.
a comparatively young, irregularly shaped group of badges, often numbering up to ten to one hundred, and held together by and active learning journey; usually found associated with people who are gaining new knowledge where new ideas are forming on a regular basis. As the open cluster grows domain mastery increases.

Globular Cluster
noun, epistemology.
a comparatively older, spherically symmetrical, compact group of up to a few hundred badges, held together by a shared knowledge domain, that are located in the earners digital badge repository. Globular clusters are often stable with few new badges being added. In general, they show a mastery of a subject domain.

What is a Badge Cluster?
Badge clustering happens as a badge earner groups their badges into knowledge clusters as defined by themselves (the badge earner). This provides an approach for people to deepen their learning through grouping knowledge in ways that make the most sense to them. It also provides visual queues or information organization to identify gaps or holes in their self-directed study. Badge clusters can be compared to personal curriculum maps to identify the gaps in their learning.

Mozilla digital backpack as a badge repository.

Why badge clustering will be important?
As learners gather more badges into their digital badge repositories they will organize the badges into groups for a variety of purposes. The groupings will be for;

• display purposes
• setting public and private display
• identifying personal knowledge domains
• achievement towards a learning goal
• inspiring others toward similar (yet personalized) learning journeys
• organizing badges into micro and macro badges

With the correct number of badge endorsements, badge assertions, verified badge criteria, confirmed evidence, and the ability to analyze a cluster of badges against a known knowledge domain we could get to a persons completed learning efforts being assessed towards the mastery of an identified knowledge domain. I dream!

1/2 finished posts have been chosen

A month back I was musing about my > 20 half-finished blog posts, I decided to put it out to vote. After three weeks the poll was closed and my next few posts have been chosen. The immediate blogging with cover the following six posts; with injected posts from my work with open badges, building online learning communities, popcorn.js, and other pedagogical subjects I am inspired to write about. The poll results can be found within the original post, and my next few posts will include;

1. Computer Science taught as an art (33% voters)
2. Learning is Knowledge Management (33% voters)
3. Traditionalists, Reformers and Outliers (28% voters)
4. Not everyone is social (28% voters)
5. Learning Platforms for People (28% voters)
6. Using smart phones within a connectivist approach (28% voters)

As of the poll closing day, 21 of 204 viewers voted. And the final results were different than those a week after the poll had opened.

Help me complete my half-finished blog posts

After reading a couple of posts on Boris Mann's blog, in particular; "The Posts That You Don't Write". I got thinking about all the half written blog posts I have. My blogging style is to write down ideas for blog posts as unpublished blog posts. As the ideas pop into my head I create the post, add notes and references, loop around, and often finish them off. This can take months, sometimes over a year... most of the time they get finished (or deleted). Currently, I have over 20 blog posts like this, some are almost finished some are not. So I wondered, what would happen if I put this out to vote.

 Which of these half-finished blog posts should I complete?
 

Agile Instructional Design in Practice

A few weeks back I was engaged in an email conversation about Agile Instructional Design and where it fits with the institutional learner and the individual learner. I believe this was a very important conversation about my views on Agile Instructional Design. here is the Transcript;

Peter: Great to connect with you. I followed you on twitter and here is an email. Please reply to confirm receipt. Be Well...

Other: Thanks, Peter! I started looking for rapid or agile instructional development (ID), because we've got a lot of programs here that need to go online, and I'd like to find a methodology to assist with the development process. I'd also like to find a model of agile or rapid ID that would support leadership in understanding their sponsorship role. I've done these ID projects for over a decade, but usually have had the luxury of more resources. Times have changed and we've got limited resources and departments are likely to increasingly do things on their own, or even hiring 3rd party companies because they think we don't have the internal resources. It looks like you're focus is more toward exploring the personal side of ID. Is that what you're focusing on now with progressive video?

http://www.flickr.com/photos/helico/404640681/

Peter: It all sounds so familiar to me. A while back I was inspired by Rapid... but it still fell into the waterfall of ADDIE as far as I was concerned, so I started applying Agile techniques and so far they seem to be working on a number of projects. I have every intention of keeping my AID exploration as a methodology for larger institutions, medium sized communities of practice and the individual learner. I have a couple of sites (traditional institutions) where I am gathering further information of how they are applying Agile techniques to ID. I keep focused on the individual for it is where I believe all ID needs to come from. I honestly believe the best instructional designer is the learner themselves. And if we can build the learning into the actual course development this is optimal, saves money and deepens learning. Each round of the course just builds more content. One of the troubles I see when people go outside of the "institutions" Instructional Design Office is there are so many lost opportunities for reuse and the money spent when things aren't a shared service from a platform perspective... Anyhow, I hope I answered your question about my focus. I focus on the individual (myself being the example) for it is where all learning has to begin... but each individual becomes a part of the learning collective and should collaborate in building understanding by iteratively building and sharing learning resources with the guidance of teachers and instructional designers... That is kind of where I am going with AID.
Love to continue this discussion... I think I may turn this email into a blog post. It was a very important question. Thank-you! Be Well...

Other: What if your designing new programs. And it's only the exceptional learner who understands their own learning, right? It's rare to have students who've been taught about metacognition? For many students, control of their own learning is completely foreign and they've spent a lifetime having it stripped away from them.

Peter: Exactly!!!! that is why my blog has the theme, "Setting out to inspire adult learners. Pedagogy, technology and life-long learning from outside the institutions." and why I have the inspired learner series of posts;

• http://criticaltechnology.blogspot.com/2011/03/inspired-learners-series.html
• http://criticaltechnology.blogspot.com/search/label/inspired

I believe inspiring learners to claim back their own learning is one of the issues of our time... and the dialogue has only just begun.

What to do when the individual doesn't yet exist... set out to engage them during the first lesson or online module. Murder Madness and Mayhem is an excellent example. AID at its best! I spoke of it in this post; http://criticaltechnology.blogspot.com/2012/01/implementation-of-aid.html Look at what they did here http://en.wikipedia.org/wiki/Wikipedia:WikiProject_Murder_Madness_and_Mayhem In a way this is the easiest time for the ID or teacher for they just begin with the theme or outcomes of the course. It gets harder when there already is a body of content created by previous running's of the course. Introduce the topic, engage the learners, build the approach, a couple of rubrics, create some tension, inspire... what teachers should be doing anyway ;) This is an awesome conversation! Thank-you!

Inspired Ableton Teacher

Drew Vespers came to my attention over a year ago as I began my Ableton Live journey. I signed up for our local Ableton group on facebook and started reading and listening. Vespers bubbled to the top as someone very engaged in using and teaching with Ableton Live. Yesterday I received an email from Vespers asking if I wanted to write a track with him? You bet I do, only my challenge is time. I still had a good look around his site and I realized just what an inspired learner (and teacher) he is. Drew is definitely what Curtis Bonk considers a supermentor.



What I consider particularly inspiring is how Drew uses the technology and publishing platforms to promote his work and engage learners. These are a few of the particular activities that push into supermentor.

• Use of livestreaming with later download for personal review. This kind of video learning is very strong pedagogically.
• Use of social media (facebook, g+, myspace, soundcloud, youtube, twitter). 
• Use of blogging to share wisdom. 
• Engagement with local communities. 
• Teaching in traditional institutions. 
• A practitioner of what he is teaching. 

And to think all these services are done a very little to no cost. Drew Vespers is an inspired learner (and teacher).

An end for education

Last week I was reading a post from my friend Brad. In his post he asked the question what is the end of education. Not the kind of end meaning over/finished, but the kind of end meaning purpose. For me the answer to this important question is;

to be a positive and loving contributor to the local and global community as a whole.

This pretty much means, do what you are good at, do what you enjoy, find a place for yourself where you help the local community and the world be a better place. In other words the end of education is to help people to know who they are and where they fit, and then provide them the skills and knowledge to support this self-understanding.

Simple Concepts well Supported

As many of you know I have been a big follower of progressive inquiry for quite a while. I was first introduced to the approach back in 2006 when I was building some faculty development workshops out at Memorial University of Newfoundland. I needed a framework / approach to legitimize the use of social media for learning. Academics really need a peer-reviewed and academic approach before they will even start listening. So I found progressive inquiry; and when you think about the success of the Finnish education system, I think the Finns must be onto something...

So when my friend Dan Pontefract posted about what he considered a jaw dropping image used by Mitchel Resnick in a talk at the Future of Learning Conference and Festival I was pleasantly surprised by the similarity of the images. It reinforced my belief that progressive inquiry is a model for learning that works well online and off. And at its core learning is a creative endeavour that begins with a persons imaginative initiation to create, to share with others, to reflect, and to keep imagining.

So if you find yourself wanting to learn something new or begin a creative project, begin it! Imagine and create with reckless abandon, play at what you are doing, share with others, reflect and keep imagining and creating. And be rigorous about it, take HUGE risks, play with the humility of it all, engage those who can provide feedback and deepen you understanding, iterate!

Narcissism and Presentism

This is an important video when describing curriculum development and how it could offer a journey out of the current culture of narcissism and presentism. I wanted to watch this video as reference to my post on "Personal Curriculum Mapping". It supported well my belief that it is important every individual be engaged in curriculum development. And from my perspective, the development of their own curriculum. I have embedded the video and included the main points that meant the most to me and my idea of personal curriculum mapping.


William Pinar "Allegories of the Present: Curriculum Development in a Culture of Narcissism and Presentism" from Tallinna Ülikool on Vimeo.

• Curriculum is mostly focused upon economy and society. In general, it is not localized to community needs. Most curriculum development is procedural and assessment focused.
• Curriculum development should encourage ongoing forms of intellectual engagement.
• Advanced capitalism has created an environment of narcissism and presentism. People have retreated from public life. People no longer engage with the past or future.
• Allegory (storytelling) provokes reflection and engagement to the past and future. It also is an internal and external journey as one will reflect internally to the history. Allegory stretches in many directions and allows individuals to find personal relation to the story. Study of history is important, it fits very well to allegory.
• Curriculum guidelines should be no more than guidelines. Teachers should have freedom to explore wherever their imaginations take them.
• Intellectual labor is also an emotional undertaking. Allegory allows for intellectual depth mediated by the learner.
• Allegory and analogy both connect the individual internally to external objects, events and other people. They connect people to the world. Contributing to curriculum development connects us to others, the past, present and future.
• Self-reflective understanding transforms the present.
• Move from curriculum standardization to curriculum differentiation. Working through the legacies of the past enables finding the future.
• Presentism. All that we have is now. One task follows another task. It erodes the lived links among originality, creativity, spontaneity, anger, risk-taking, excitement, pleasure, discomfort, anxiety, all of humanity.
• I don't want teachers to be the same, a good mix of people. We need teachers to be individuals. We need an intellectual differentiation.
• The tests that only make sense are those that are devised by the teachers for the particular class.
• Outcomes based curriculum are manipulative and too limiting, we want to keep the future open. It is the excitement of becoming educated.

My take away; distinctiveness of continents, nations, states, provinces, cities, municipalities, neighborhoods, families and individuals is good for humanity. Diversity will keep our knowledge base broadening. Curriculum development  needs to include the learner. It would connect the learner to the past, present and future of the subject domain when they have greater responsibility in creating the curriculum.

Harmony House Super Mentor

If you follow this blog you are aware of my inspired learner series of posts. The idea being that there are already many people learning online and using social media as a part of their learning. I also believe that the role of the super mentor will become increasingly important for self-directed learners.

Sandi Melody is a super mentor who has created something very special. She has created a school where youth can come for music and live performance training. What she provides goes far beyond the regular music teaching, she provides mentorship to many aspects of being a musician, not just the chops of playing your chosen instrument. What Sandi does is well described by Curtis Bonk in his book "The World is Open";

This will be a person to consult with at critical junctures in your learning process. Such individuals will be critical in helping sort out the myriad ways you can learn today as well as the interesting routes you might take to reach new learning milestones. As learning becomes increasingly essential in our lives, super mentors will continually provide the breath of life by leading us to relevant and meaningful learning paths.

What I also believe is done very well with Harmony House, Sandi and her students is their use of social media to promote their activities. Being public with your learning increases its depth and quality. And by engaging your social network during your learning increases opportunity for reflection, peer engagement and mentorship.



I believe Sandi Melody is an inspired super-mentor who uses many of the available social media technologies to deepen peoples learning by engaging others and provide opportunities for reflection and public support. Sandi is an Inspired Super-mentor and her students are Inspired Learners.

The days first task

http://www.flickr.com/photos/naotakem/

Seth Godin often prompts me to think different. And this morning was no different, he essentially asked the question "what do you do when you start your working day?" Do you consume online media or do you create. I believe the morning sets the tone for the day so how you start is important, and most days I start by consuming online media. This has got to change for me. I consider myself a creative and I need to seize this important and productive time to create something. This is how I intend to flip my mornings around, I will start my daily online activity with an act of creation. Depending on the time available it will either be;

• with a short time, I will reflect upon my learning and my professional life and post a tweet that I believe would have value to those who follow me.
• with a longer time, I will use a pomodoro to add to my blog.

I will consume online media through-out the day using my netbook or smartphone. This is what I do already, so... I hope this new way of starting the day will add to the collective intelligence of everyone's day rather than my just lurking within the collective stream.

Emersive Learning

What is it about emersion that works so well? A couple of months back I wrote about how progressive inquiry and tranformative learning are a great way to learn. During my recent family adventure I was presented the opportunity to spend 24 hours in Wat San Goo. I was excited by spending time in a traditional Thailand Wat and was looking forward to what I would also learn. I really had no idea what was going to unfold and as the time to emerse myself neared I became increasingly hesitant. Throwing myself into a world I had never experienced and being surrounded by a language I was only just beginning to hear was creating a little fear. Needless to say I was pushing a few boundaries.

What emerged from the 24 hours became the subject of a rather detailed blog post. And what stands out for me was the amount I learned during the 24 hours. I would almost say I created a transformative learning experience for myself. Could it be that my hesitancy and mild fear pushed me into a heightened awareness that enabled me to assimilate more information and the unfamiliar surroundings increased my ability to learn about these surroundings?