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Proceedings Article•DOI•

MIRTO: an Open-Source Robotic Platform for Education

Kelly Androutsopoulos1, L. Aristodemou1, Jaap Boender1, Michele Bottone1, Edward Currie1, I. El-Aroussi1, Bob Fields1, L. Gheri1, Nikos Gorogiannis1, M. Heeney1, Matteo Micheletti1, Martin J. Loomes1, Michael Margolis1, Miltos Petridis1, A. Piermarteri1, Giuseppe Primiero1, Franco Raimondi1, Nick Weldin1 •
Middlesex University1
14 Jun 2018-pp 55-62
TL;DR: A detailed description of the Middlesex RoboTic platfOrm platform is provided, whose hardware specifications and software libraries are all released open source; a number of teaching usages of the platform are described, and some of its aspects in terms of effectiveness, usability, and maintenance are evaluated.
Abstract: This paper introduces the Middlesex RoboTic platfOrm (MIRTO), an open-source platform that has been used for teaching First Year Computer Science students since the academic year 2013/2014, with the aim of providing a physical manifestation of Software Engineering concepts that are often delivered using only abstract or synthetic case studies. In this paper we provide a detailed description of the platform, whose hardware specifications and software libraries are all released open source; we describe a number of teaching usages of the platform, report students' projects, and evaluate some of its aspects in terms of effectiveness, usability, and maintenance.

Summary (4 min read)

Jump to: [1 Introduction] – [2 Hardware details] – [3 Software Details] – [4.1 Teaching applications] – [4.1.1 Continuous integration and delivery] – [4.1.2 Test-driven development] – [4.1.3 Reasoning about system architectures] – [4.2 Student projects] – [4.2.1 Voice recognition.] – [4.2.2 Using Twitter and Image Capturing.] – [4.2.3 Swarm robotics] – [5 Evaluation] – [5.1 Qualitative and Quantitative Considerations] – [5.2 Comparison with other platforms] – [5.3 Lessons learnt] and [6 Conclusion]

1 Introduction

  • The teaching team decided to place particular emphasis on physical manifestations of computing through the use of hardware resources, in an attempt to create a syntonic environment (in the sense of [14]), in which students could “establish a firm connection between personal activity and the creation of formal knowledge”.
  • This approach is particularly useful for code comprehension, but also to cover with practical and concrete projects some of the topics typical of Software Engineering, such as agile development in a team, continuous integration, and test-driven development.

2 Hardware details

  • The main components are: A pair of 5 V 1:34 geared motors with encoders connected to 1/10 scale car wheels.
  • The wheels and the off-the-shelf components are connected to the Teensy micro-controller by means of a bespoke printed circuit board (PCB) that has been designed at Middlesex ; the design files of the PCB are released open source (see links below) and several companies are available to print them.
  • A Raspberry Pi version 3 with 1.4GHz 64-bit quad-core processor, 1 Gbyte RAM, built-in WiFi, 4 USB ports, HDMI, composite audio output and 40-pin GPIO header.
  • The frame of the robot is made using 3 mm acrylic sheets cut using a laser cutter, locked using threaded nuts and bolts.
  • The design files for the frame in DXF format, the design files for the PCB, a full list of parts, and hardware instructions are available at https://github.com/michaelmargolis/MirtoDesignFiles.

3 Software Details

  • The core software component (and main difference between MIRTO and other robotic platforms) is a bespoke firmware running on the Teensy that allows for the interaction of the micro-controller with separate clients over a streaming connection (typically a serial connection).
  • Racket [9] is a LISP-like programming language used since 2013 to teach foundations of programming to First Year Computer Science students at Middlesex University.
  • Figure 5 shows an example of how the robot can be controlled over TCP.

4.1 Teaching applications

  • The robot enables us to cover several knowledge areas of the ACM Computer Science Curriculum [10].
  • In addition to Software Development Fundamentals such as conditional structures, iterative control structures, recursion, and abstract types such as Stacks and Priority Queues, MIRTO exposes students to a physical manifestation of concepts such as unit testing and programming using APIs.
  • Moreover, MIRTO can be used to cover specific Software Engineering topics, some of which are exemplified in the following subsections.

4.1.1 Continuous integration and delivery

  • The Raspberry Pi layer of MIRTO runs a standard Debian-based Linux distribution.
  • As a result, all the development tools available on a standard Linux distribution are also available on MIRTO.
  • The key features of continuous integration and delivery can be covered by installing git on the Raspberry Pi and by defining a “bare” git repository2 on it.
  • A typical exercise for this scenario is the following: “Develop a line following algorithm for MIRTO using the infra-red sensors to detect the presence of a black line.
  • Students are given a Bash script containing the basic instructions to build the software on the Raspberry Pi, to stop a running process (the line following algorithm in this case), and to re-start the process.

4.1.2 Test-driven development

  • Students are required to reason about functional requirements, describing how system data is exchanged using UML.
  • Figure 6 shows an example UML sequence diagram showing how a message travels from the student laptop to the actual wheel through a TCP/Serial bridge on the Raspberry Pi and ASIP messages.
  • Students are requested to draw these diagrams for all components, thus modelling the bi-directional flow of information and reasoning about the overall architecture (see next section).
  • Students are requested to design unit tests for all the components modelled with UML diagrams.
  • Given the black-box nature of system tests, when working in groups students can test other groups’ systems and thus also appreciate with concrete instances the notion of acceptance testing, thus covering all the steps: unit testing, integration testing, system testing and acceptance testing.

4.1.3 Reasoning about system architectures

  • The robot is inherently more complex than software-only systems that can be used in a teaching environment.
  • At the very least, the robot is composed of multiple and independent sensors and actuators that are coordinated by a microcontroller.
  • There are two options in this case: in the first option, the code can run on the Raspberry Pi itself (all the client libraries are supported, including Racket).
  • All these options allow students to reason about configuration and release management for the several projects that can be implemented.
  • First year students typically implement this task using Racket and its built-in web server to drive a robot using key presses on a browser.

4.2 Student projects

  • The authors encourage students to work autonomously at projects of their choice throughout the course of their studies, encouraging them to build a portfolio of projects using a code repository such as GitHub and Bitbucket.
  • The authors allocate teaching time for these activities, in particular: in the last four teaching weeks of the First Year, students have the option of working at the “First Year Challenge in Computer Science”.
  • This is a challenge funded by an external industrial sponsor that provides a prize of 500 GBP for the “best” student project.
  • For this challenge, students typically work in groups and projects are assessed for their originality, for the Software Engineering approaches used, and for the complexity of the tasks.
  • The authors report below two submissions received in previous years and a third year project that led to a publication.

4.2.1 Voice recognition.

  • This project by a first year student involved the use of Carnegie Mellon PocketSphinx4, a lightweight continuous speech recognition engine written in C.
  • The student compiled the code on the Raspberry Pi and modified it so that it could output only specific command such as “move forward”.
  • The commands were then streamed to a Racket application that moved the robot accordingly.
  • The only additional component required for this project was a USB microphone connected to the Raspberry Pi.

4.2.2 Using Twitter and Image Capturing.

  • This project by a group of first year students involved the use of the Twitter streaming API5.
  • By connecting MIRTO to the internet, students were able to filter tweets containing the keyword MIRTOBOT.
  • Then, they could parse specific messages such as movement instructions, but also instructions to take pictures using a USB webcam added to the Raspberry Pi.
  • All the images captured in this way have been made available through a web server running on the robot and written in Racket.

4.2.3 Swarm robotics

  • The student first developed and simulated algorithms for decision making using NetLogo [17].
  • These algorithms have then been implemented in Java and deployed on Mirto.
  • This project shows that MIRTO can be used not only for teaching, but also to introduce students to research activities.

5 Evaluation

  • In this section the authors evaluate the MIRTO platform and compare it to other existing solutions.
  • The authors also discuss their experience since 2013 and report lessons learnt that, they hope, may be useful to other educators who plan to use a robotic platform in their classes.

5.1 Qualitative and Quantitative Considerations

  • In terms of a qualitative financial evaluation, the overall cost per robot for parts only is approximately 100 GBP; the most expensive components are the Raspberry Pi (approx 30 GBP) and the Teensy 3.2 (approx 20 GBP).
  • Given that the robots are pre-assembled and that students are provided with high-level libraries and detailed handouts, the authors have observed that students are able to start working at specific tasks such as “move forward for 1 second” in less than 30 minutes when they are first exposed to the platform.
  • The most energy-hungry task is wheel movement at maximum torque (i.e., uphill or on a “soft” surface).
  • In particular, after introducing the material for a SOB, the authors have observed how many students were observed on subsequent days, for a total of 144 students in the academic year 2017/18.
  • Only 4 other SOBs are observed (on average) earlier than the SOB on the robot: 2 of them are related to an in-class programming test which is normally observed within a week, as students are required to take the test in specific dates.

5.2 Comparison with other platforms

  • The number of robotic platforms used in teaching is vast, and a detailed review of the options is beyond the scope of this article.
  • Micro-controllers are also commonly found in classrooms, including Arduino boards and the UK-specific BBC micro:bit (http://microbit.org/) targeted at Year-7 students and including both blockbased and textual coding environments.
  • The main difference with respect to their solution is that the authors release both hardware and software as open source.
  • In general, the adoption of robots in the classroom is by no means new, see for instance [4] for a systematic literature review and for references to options beyond Lego EV3.
  • The authors argue that, in the case of MIRTO, the provision of highlevel libraries in Java and other programming languages enables students to by-pass low-level technical issues.

5.3 Lessons learnt

  • Over the years, the authors have made a number of changes that allowed us to: Simplify assembly and reduce maintenance: starting in 2015, they have designed their own printed circuit board, resulting in a very small number of wires required.
  • There is a total of approximately 180 students in the First Year of Computer Science; students are split in groups of approximately 30 students and therefore the same lab sessions are repeated six times every week.
  • For the robotic sessions the authors normally employ between 7 and 10 robots per class, corresponding to approximately 3 students per robot.

6 Conclusion

  • An open source robotic platform employed at Middlesex University to teach Software Engineering knowledge areas from the ACM curriculum [10].the authors.
  • The authors have described both the hardware and the software architecture of the robot and they have provided example activities for the classroom and reported projects developed by students in the past 5 academic years.
  • In addition to its usage in the classroom, the authors have used MIRTO for outreach activities with audiences ranging from primary school children to science festivals with adults.
  • Given the level of maturity and stability of the platform, the authors are now beginning to start using the platform for research purposes to study energy consumption in wireless sensor networks and genetic algorithms for strategy selection in a multi-robot environment.
  • ASIP firmware for the Teensy layer: https://github.com/mdxmase/asip Java ASIP client library: https://github.com/fraimondi/java-asip.

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Middlesex University Research Repository
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Androutsopoulos, Kelly ORCID logoORCID: https://orcid.org/0000-0001-8257-1867,
Aristodemou, Leonidas, Boender, Jaap, Bottone, Michele, Currie, Edward ORCID logoORCID:
https://orcid.org/0000-0003-1186-5547, El-Aroussi, Inas, Fields, Bob ORCID logoORCID:
https://orcid.org/0000-0003-1117-1844, Gheri, Lorenzo, Gorogiannis, Nikos ORCID
logoORCID: https://orcid.org/0000-0001-8660-6609, Heeney, Michael, Micheletti, Matteo,
Loomes, Martin J., Margolis, Michael, Petridis, Miltos, Piermarteri, Andrea, Primiero, Giuseppe,
Raimondi, Franco ORCID logoORCID: https://orcid.org/0000-0002-9508-7713 and Weldin, Nick
(2018) MIRTO: an open-source robotic platform for education. ECSEE’18: Proceedings of the
3rd European Conference of Software Engineering Education. In: 3rd European Conference on
Software Engineering Education, 14-15 June 2018, Seeon, Germany. ISBN 9781450363839.
[Conference or Workshop Item] (doi:10.1145/3209087.3209106)
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2
MIRTO: an Open-Source Robotic Platform for
Education
K. Androutsopoulos L. Aristodemou J. Boender
M. Bottone E. Currie I. El-Aroussi B. Fields
L. Gheri N. Gorogiannis M. Heeney M. Micheletti
M. Loomes M. Margolis M. Petridis A. Piermarteri
G. Primiero F. Raimondi N. Weldin
June 14, 2018
Abstract
This paper introduces the MIddlesex RoboTic platfOrm (MIRTO), an
open-source platform that has been used for teaching First Year Computer
Science students since the academic year 2013/2014, with the aim of pro-
viding a physical manifestation of Software Engineering concepts that are
often delivered using only abstract or synthetic case studies. In this paper
we provide a detailed description of the platform, whose hardware spec-
ifications and software libraries are all released open source; we describe
a number of teaching usages of the platform, report students’ projects,
and evaluate some of its aspects in terms of effectiveness, usability, and
maintenance.
1 Introduction
In 2013 the Department of Computer Science at Middlesex University took the
decision of re-designing the first year of the Computer Science degree, with the
aim of addressing some of the issues with the previous course format: progressive
disengagement, negative feedback about course content in terms of employabil-
ity and “practical” experience, low attendance rate, etc. Due to the diverse
range of academic backgrounds of first year students at Middlesex University,
another problem to be addressed was the definition of a course format that could
accommodate a non-uniform class of students.
The teaching team decided to adopt a problem-based approach to teach-
ing, with a focus on the so-called inverted curriculum where students learn
theory whilst they are doing practical exercises [11] and project-centered de-
livery, providing detailed material that students could use in workshops un-
der the supervision of members of staff. Assessment is performed on a daily
basis through so-called Student Observable Behaviours (SOBs), which can be
1
Figure 1: MIRTO fully assembled (front and rear views)
thought of as fine-grained learning outcomes, or capabilities, such as “Build
and test simple combinatorial logic circuits using at least two different gates
in hardware” or “Write a simple recursive function to carry out a well-defined
task over lists or integers, test the function and explain how it works”. Ob-
servation of behaviours is supported by a bespoke assessment tool available at
https://bitbucket.org/mdxmase/sobmonitor, with the aim of addressing the
known limitations of self-paced learning and constructivist approaches [16, 12]:
indeed, while students can work in a very flexible way, we are nevertheless able
to track their progress both in terms of attendance and progress.
The teaching team decided to place particular emphasis on physical mani-
festations of computing through the use of hardware resources, in an attempt
to create a syntonic environment (in the sense of [14]), in which students could
“establish a firm connection between personal activity and the creation of for-
mal knowledge”. This approach is particularly useful for code comprehension,
but also to cover with practical and concrete projects some of the topics typical
of Software Engineering, such as agile development in a team, continuous in-
tegration, and test-driven development. More specifically, physical computing
provides an opportunity for conceptual blending [8]: by asking students to work
in both abstract and physical spaces, they create blends that enable rich con-
versations — the behaviour of their code blends with the behaviour of a robot
(or device), and the latter is observable in explicit ways.
In this paper we present MIRTO, the MIddlesex RoboTic platfOrm, show-
ing how it can be used to cover several of the Knowledge Areas in the ACM
Computer Science curriculum [10], with a particular focus on the Software Engi-
neering knowledge area. In particular, we provide hardware details in Section 2
and software details in Section 3; example applications for teaching and students
projects are reported in Section 4, while an evaluation and a comparison with
other existing platforms are provided in Section 5. We conclude in Section 6.
2 Hardware details
Mirto is a two-wheel robot of circular shape, with a diameter of approximately
20 cm and height 10 cm, see Figure 1. The main components are:
2
Figure 2: MIRTO PCB
• A pair of 5 V 1:34 geared motors with encoders connected to 1/10 scale
car wheels.
• Off-the-shelf components: bump contact sensors, infra-red sensors, poten-
tiometer, digital switch, piezo buzzer, 5-line LCD screen.
• A Teensy 3.2 micro-controller: this is an Arduino-compatible ARM micro-
controller running at 72 MHz, 256 Kbytes of flash memory, 64 Kbytes of
RAM, 33 usable PINs, USB and serial communication ports.
• The wheels and the off-the-shelf components are connected to the Teensy
micro-controller by means of a bespoke printed circuit board (PCB) that
has been designed at Middlesex (see Figure 2); the design files of the
PCB are released open source (see links below) and several companies are
available to print them.
• A Raspberry Pi version 3 with 1.4GHz 64-bit quad-core processor, 1 Gbyte
RAM, built-in WiFi, 4 USB ports, HDMI, composite audio output and
40-pin GPIO header. The PCB plugs into the Raspberry Pi GPIO pins
and communicates with the Teensy over a serial channel. Software details
are reported in the next section.
3
Citations
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Agoric computation: trust and cyber-physical systems

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Michele Bottone
28 Nov 2018
TL;DR: This thesis reviews the logical and mathematical basis of stateless abstractions and takes steps towards the software implementation of agoric modelling as a framework for simulation and verification of the reliability of increasingly complex systems, and reports on experimental results related to a few select applications.
Abstract: In the past two decades advances in miniaturisation and economies of scale have led to the emergence of billions of connected components that have provided both a spur and a blueprint for the development of smart products acting in specialised environments which are uniquely identifiable, localisable, and capable of autonomy. Adopting the computational perspective of multi-agent systems (MAS) as a technological abstraction married with the engineering perspective of cyber-physical systems (CPS) has provided fertile ground for designing, developing and deploying software applications in smart automated context such as manufacturing, power grids, avionics, healthcare and logistics, capable of being decentralised, intelligent, reconfigurable, modular, flexible, robust, adaptive and responsive. Current agent technologies are, however, ill suited for information-based environments, making it difficult to formalise and implement multiagent systems based on inherently dynamical functional concepts such as trust and reliability, which present special challenges when scaling from small to large systems of agents. To overcome such challenges, it is useful to adopt a unified approach which we term agoric computation, integrating logical, mathematical and programming concepts towards the development of agent-based solutions based on recursive, compositional principles, where smaller systems feed via directed information flows into larger hierarchical systems that define their global environment. Considering information as an integral part of the environment naturally defines a web of operations where components of a systems are wired in some way and each set of inputs and outputs are allowed to carry some value. These operations are stateless abstractions and procedures that act on some stateful cells that cumulate partial information, and it is possible to compose such abstractions into higher-level ones, using a publish-and-subscribe interaction model that keeps track of update messages between abstractions and values in the data. In this thesis we review the logical and mathematical basis of such abstractions and take steps towards the software implementation of agoric modelling as a framework for simulation and verification of the reliability of increasingly complex systems, and report on experimental results related to a few select applications, such as stigmergic interaction in mobile robotics, integrating raw data into agent perceptions, trust and trustworthiness in orchestrated open systems, computing the epistemic cost of trust when reasoning in networks of agents seeded with contradictory information, and trust models for distributed ledgers in the Internet of Things (IoT); and provide a roadmap for future developments of our research.

8 citations

Cites background from "MIRTO: an Open-Source Robotic Platf..."

  • ...4; and a second, more limited live experiment consisting of four robots incorporating the MIRTO robotic platform [Androutsopoulos et al. 2018], moving on a scaled down 5×5 square enclosure where each position in the grid contains exactly one robot and robots change positions by following black lines arranged in a triangular Petersen mesh, shown in Figure 6....

    [...]

Book Chapter•DOI•
Embedding creativity in the university computing curriculum

[...]

Edward Currie1, Carl James-Reynolds1•
Middlesex University1
11 Sep 2017
TL;DR: The need for embedding creativity in the UK higher education computing curriculum and some of the challenges associated with this are explored and a number of recommendations are made.
Abstract: We explore the need for embedding creativity in the UK higher education computing curriculum and some of the challenges associated with this We identify some of the initiatives and movements in this area and discuss some of the work that has been carried out We then describe some of the ways we have tried to meet these challenges and reflect on our degree of success with respect to the goal of producing graduates who are fit for the myriad of job opportunities they will come across in a rapidly changing technology landscape Finally, we make a number of recommendations

2 citations

Cites background from "MIRTO: an Open-Source Robotic Platf..."

  • ...They extend this work to projects that involve programming bespoke robots with on board Raspberry Pi computers [20], infrared and bump sensors etc....

    [...]

References
More filters
Book•
Mindstorms: Children, Computers, And Powerful Ideas

[...]

Seymour Papert
01 Jan 1980
TL;DR: The gears of my childhood as discussed by the authors were a source of inspiration for many of the ideas we use in our own work, such as the notion of assimilation of knowledge into a new model.
Abstract: The Gears of My Childhood Before I was two years old I had developed an intense involvement with automobiles. The names of car parts made up a very substantial portion of my vocabulary: I was particularly proud of knowing about the parts of the transmission system, the gearbox, and most especially the differential. It was, of course, many years later before I understood how gears work; but once I did, playing with gears became a favorite pastime. I loved rotating circular objects against one another in gearlike motions and, naturally, my first "erector set" project was a crude gear system. I became adept at turning wheels in my head and at making chains of cause and effect: "This one turns this way so that must turn that way so . . . " I found particular pleasure in such systems as the differential gear, which does not follow a simple linear chain of causality since the motion in the transmission shaft can be distributed in many different ways to the two wheels depending on what resistance they encounter. I remember quite vividly my excitement at discovering that a system could be lawful and completely comprehensible without being rigidly deterministic. I believe that working with differentials did more for my mathematical development than anything I was taught in elementary school. Gears, serving as models, carried many otherwise abstract ideas into my head. I clearly remember two examples from school math. I saw multiplication tables as gears, and my first brush with equations in two variables (e.g., 3x + 4y = 10) immediately evoked the differential. By the time I had made a mental gear model of the relation between x and y, figuring how many teeth each gear needed, the equation had become a comfortable friend. Many years later when I read Piaget this incident served me as a model for his notion of assimilation, except I was immediately struck by the fact that his discussion does not do full justice to his own idea. He talks almost entirely about cognitive aspects of assimilation. But there is also an affective component. Assimilating equations to gears certainly is a powerful way to bring old knowledge to bear on a new object. But it does more as well. I am sure that such assimilations helped to endow mathematics, for me, with a positive affective tone that can be traced back to my infantile experiences with cars. I believe Piaget really agrees. As I came to know him personally I understood that his neglect of the affective comes more from a modest sense that little is known about it than from an arrogant sense of its irrelevance. But let me return to my childhood. One day I was surprised to discover that some adults---even most adults---did not understand or even care about the magic of the gears. I no longer think much about gears, but I have never turned away from the questions that started with that discovery: How could what was so simple for me be incomprehensible to other people? My proud father suggested "being clever" as an explanation. But I was painfully aware that some people who could not understand the differential could easily do things I found much more difficult. Slowly I began to formulate what I still consider the fundamental fact about learning: Anything is easy if you can assimilate it to your collection of models. If you can't, anything can be painfully difficult. Here too I was developing a way of thinking that would be resonant with Piaget's. The understanding of learning must be genetic. It must refer to the genesis of knowledge. What an individual can learn, and how he learns it, depends on what models he has available. This raises, recursively, the question of how he learned these models. Thus the "laws of learning" must be about how intellectual structures grow out of one another and about how, in the process, they acquire both logical and emotional form. This book is an exercise in an applied genetic epistemology expanded beyond Piaget's cognitive emphasis to include a concern with the affective. It develops a new perspective for education research focused on creating the conditions under which intellectual models will take root. For the last two decades this is what I have been trying to do. And in doing so I find myself frequently reminded of several aspects of my encounter with the differential gear. First, I remember that no one told me to learn about differential gears. Second, I remember that there was feeling, love, as well as understanding in my relationship with gears. Third, I remember that my first encounter with them was in my second year. If any "scientific" educational psychologist had tried to "measure" the effects of this encounter, he would probably have failed. It had profound consequences but, I conjecture, only very many years later. A "pre- and post-" test at age two would have missed them. Piaget's work gave me a new framework for looking at the gears of my childhood. The gear can be used to illustrate many powerful "advanced" mathematical ideas, such as groups or relative motion. But it does more than this. As well as connecting with the formal knowledge of mathematics, it also connects with the "body knowledge," the sensorimotor schemata of a child. You can be the gear, you can understand how it turns by projecting yourself into its place and turning with it. It is this double relationship---both abstract and sensory---that gives the gear the power to carry powerful mathematics into the mind. In a terminology I shall develop in later chapters, the gear acts here as a transitional object. A modern-day Montessori might propose, if convinced by my story, to create a gear set for children. Thus every child might have the experience I had. But to hope for this would be to miss the essence of the story. I fell in love with the gears. This is something that cannot be reduced to purely "cognitive" terms. Something very personal happened, and one cannot assume that it would be repeated for other children in exactly the same form. My thesis could be summarized as: What the gears cannot do the computer might. The computer is the Proteus of machines. Its essence is its universality, its power to simulate. Because it can take on a thousand forms and can serve a thousand functions, it can appeal to a thousand tastes. This book is the result of my own attempts over the past decade to turn computers into instruments flexible enough so that many children can each create for themselves something like what the gears were for me.

6,780 citations

Running head: WHY MINIMALLY GUIDED INSTRUCTION DOES NOT WORK Why Minimal Guidance during Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching

[...]

Paul A. Kirschner, John Sweller
01 Jan 2006

5,243 citations

Journal Article•DOI•
Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching

[...]

Paul A. Kirschner1, John Sweller2, Richard E. Clark3•
Open University1, University of New South Wales2, University of Southern California3
01 Jun 2006-Educational Psychologist
TL;DR: In this article, the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert-novice differences, and cognitive load, and it is shown that the advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide "internal" guidance.
Abstract: Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide "internal" guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.

5,199 citations

Journal Article•DOI•
Scratch: programming for all

[...]

Mitchel Resnick1, John Maloney1, Andrés Monroy-Hernández1, Natalie Rusk1, Evelyn Eastmond1, Karen Brennan1, Amon Millner1, Eric Rosenbaum1, Jay Silver1, Brian Silverman, Yasmin B. Kafai2 •
Massachusetts Institute of Technology1, University of Pennsylvania2
01 Nov 2009-Communications of The ACM
TL;DR: "Digital fluency" should mean designing, creating, and remixing, not just browsing, chatting, and interacting.
Abstract: "Digital fluency" should mean designing, creating, and remixing, not just browsing, chatting, and interacting.

2,823 citations

"MIRTO: an Open-Source Robotic Platf..." refers methods in this paper

  • ...The robots are also used for outreach activities with children using Scratch [15]: a Scratch-MIRTO bridge is available at https://github....

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  • ...The robots are also used for outreach activities with children using Scratch [15]: a Scratch-MIRTO bridge is available at https://github. com/fraimondi/java-asip....

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  • ...For Scratch activities, the robot creates a wireless access point and children can employ blocks that we have designed to perform simple tasks, such as moving inside an area delimited by black tape to simulate a Roomba robot: an example program for this task is reported in Figure 10....

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Book•
The Way We Think: Conceptual Blending And The Mind's Hidden Complexities

[...]

Gilles Fauconnier, Mark Turner1•
University of Maryland, College Park1
03 Apr 2002
TL;DR: Fauconnier and Turner as discussed by the authors show that conceptual blending is the root of the cognitively modern human mind, and that conceptual blends themselves are continually combined and reblended to create the rich mental fabric in which we live.
Abstract: A long-awaited synthesis that marks a major turning point in cognitive science. . Until recently, cognitive science focused on such mental functions as problem solving, grammar, and pattern-the functions in which the human mind most closely resembles a computer. But humans are more than computers: we invent new meanings, imagine wildly, and even have ideas that have never existed before. Today the cutting edge of cognitive science addresses precisely these mysterious, creative aspects of the mind. The Way We Think is a landmark analysis of the imaginative nature of the mind. Conceptual blending is already widely known in research laboratories throughout the world; this book, written to be accessible to both lay readers and interested scientists, is its definitive statement. Gilles Fauconnier and Mark Turner show that conceptual blending is the root of the cognitively modern human mind, and that conceptual blends themselves are continually combined and reblended to create the rich mental fabric in which we live. The Way We Think shows how this blending operates; how it is affected by (and gives rise to) language, identity, culture, and invention; and how we imagine what could be and what might have been. The result is a bold and exciting new view of how the mind works.

2,475 citations

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Frequently Asked Questions (2)
Q1. What are the contributions in "Mirto: an open-source robotic platform for education" ?

This paper introduces the MIddlesex RoboTic platfOrm ( MIRTO ), an open-source platform that has been used for teaching First Year Computer Science students since the academic year 2013/2014, with the aim of providing a physical manifestation of Software Engineering concepts that are often delivered using only abstract or synthetic case studies. In this paper the authors provide a detailed description of the platform, whose hardware specifications and software libraries are all released open source ; they describe a number of teaching usages of the platform, report students ’ projects, and evaluate some of its aspects in terms of effectiveness, usability, and maintenance. 

Given the level of maturity and stability of the platform, the authors are now beginning to start using the platform for research purposes to study energy consumption in wireless sensor networks and genetic algorithms for strategy selection in a multi-robot environment.