Hello everyone! My name is Mannu Lambrichts
and together with my collegues Raf Ramakers and Sven Coppers from Hasselt University
and Steve Hodges and James Devine from Microsoft Research
we would like to introduce our paper: a survey and taxonomy
of interactive and ubiquitous device prototyping.
Over the past two decades, many toolkits for prototyping electronic devices have appeared,
both as research project and commercial products.
These toolkits have a wide range of technical specifications,
such as for example processor speed and amount of memory.
But in addition, these toolkits also differ in terms of features, design and target audience.
For example: SoftMod and littleBits consist of magnetic modules,
while .NET Gadgeteer and mBot are built around modules with connectors.
This results in very different user experiences, strengths and weaknesses,
which mostly depend on the intended application.
As a result, it can be very challenging for those new to the area
to understand the range of user experiences offered by electronics toolkits.
In this paper we present a literature study and product summary
of the broad range of electronics prototyping toolkits.
We have created a taxonomy as a framework that goes beyond
the technical specifications, providing a more holistic view.
Secondly, we decided to make our dataset publicly available
and created an interactive online tool to browse all data.
Our database is hosted at Github
and we invite the community to complete and extend our dataset.
Lastly, we also report on the results of a formative online survey which indicates the relevance
of the characteristics in our taxonomy and highlights some common prototyping practices.
So first: Review and Taxonomy.
After our literature study and a lot of reflecting, our taxonomy now includes
13 objective characteristics divided over 4 groups, listed here.
In this video I would like to highlight one, namely “Type of electronics”.
Based on previous research we identified three types of electronics.
First, the first type of electronics are based on discrete components.
They are quick and easy to prototype with, but require significant knowledge of electronics.
The second type of electronics defines MCU development boards and breakout boards.
These integrate all necessary components for the correct operation of an a particular chip,
like an MCU or a sensor.
Prototyping is simplified,
but as you need to interface multiple not necessarily compatible modules,
you still require a good understanding of electronics.
Lastly, the third type of electronics covers toolkits that consist
of a complete ecosystem of modules specifically designed to work together.
This simplifies prototyping a lot,
but adding discrete components or custom modules to an ecosystem
is often very hard and not supported.
The second part of our work is the Online Dataset.
A table visualizes all 13 characteristics we captured across all 56 toolkits we reviewed.
You can find it at "etclassification.com" together with an online interactive tool to browse all data.
Let me take you there now.
Here you can see all our characteristics represented as the columns of the table.
Each row in the table is a different toolkit.
You can sort
and filter each row,
and you can click the “hints” button to see all possible interactions.
In the navigation bar you can also hide columns
and find links to the paper and GitHub page.
Besides the objective characteristics, there are also important holistic attributes of toolkits.
As they are somewhat subjective, we tried to assess them
by combining relevant objective characteristics by assigning weights to their labels.
Let me show you this.
We have created 4 holistic characteristics, such as expertise in programming,
which you can see in the dropdowns and columns.
According to the weights, each toolkit gets calculated a score
which is visualized in the table.
The score is between 0 and 1, and 1 is always “better”:
so “least experience required” or “easiest”.
Here you can see that Arduino Feather requires quite some experience in programming,
and littleBits none.
Changing the weights is very easy, just open the dropdown and change the values.
Let’s get back to the presentation and cover the last part: our Formative Study.
During our research, we were curious to evaluate if the needs of electronics engineers and makers
are addressed by the current electronics toolkits, so we conducted an online survey.
The survey was aimed at people who have built at least one electronic device prototype
and consisted of both multiple-choice and free-form responses for a total of 75 questions.
Over the course of the study 122 people participated.
We asked respondents to rate 26 characteristics on a Likert scale,
based on how important they are when selecting a prototyping platform.
This graph shows the outcome of the ranking
for electronics engineers versus other disciplines.
Here you can see the top 3,
and the characteristics where there is a significant difference.
We also asked respondents about their experience with scaling up to multiple copies.
To our surprise, 94% of all electronics engineers
and 73% of all other disciplines
reported making multiple copies.
53% of all respondents often start with an integrated microcontroller development board.
To conclude this presentation, I would like to notice that programming and electronics
expertise requirements are not a significant barrier, according to most respondents.
Respondent 1 indicates that current modular kits are missing fundamentals,
making users struggle with debugging.
Respondent 2 complements this by indicating the need of a new toolkit
speeding up prototyping, but without constraining the artifact that can be build.
So what do we like you to remember from this video?
First, please read our paper, it contains much more in-depth information than described here.
Secondly, please feel free to contribute to our online dataset,
both by adding toolkits or characteristics.
You can simply do this by creating a pull request in GitHub.
And lastly, go out and create some new interesting toolkits or systems
accommodating the preferences indicated by the respondents.
With that I would like to conclude this video, thank you very much for your attention!