The presentation shows how a model of Computer Supported Reflective Learning (CSRL) can be applied to a case of reflective learning in the workplace, aiding analysis and design.
Learning and imitation in heterogeneous robot groupsWilli Richert
As robots become increasingly affordable, they are used in ever more
diverse areas in order to perform increasingly complex tasks. These
tasks are typically preprogrammed by a human expert. In some cases,
however, this is not feasible -- either because of the inherent
complexity of the task itself or due to the dynamics of the
environment. The only possibility then is to let the robot learn the
task by itself. This learning process usually involves a long training
period in which the robot experiments with its surroundings in order
to learn the desired behavior. If robots have to learn a shared goal
in a group, the robots should imitate each other in order to reduce
their individual learning time. The question how this can be done in a
robot group has been considered in this thesis, i.e., how robots in a
group can learn to achieve their shared goal and imitate
each other in order to increase the performance and the speed of
learning by spreading the learned knowledge in the group.
To allow for this intertwined learning and imitation, a dedicated
robot architecture has been developed. On the one hand, it fosters
autonomous and self-exploratory learning. On the other hand, it allows
for manipulating the learned knowledge and behavior to account for new
knowledge gathered by the imitation process. Learning of behavior is
achieved by separately learning at two levels of abstraction. At the
higher level, the strategy is learned as a mapping from abstract
states to symbolic actions. At the lower level, the symbolic actions
are grounded autonomously by learned low-level actions.
The approaches of imitation presented in this thesis are unique in
that they relieve the requirements that governed multi-robot imitation
so far. It enables robots in a robot group to imitate each other in a
non-obtrusive manner. The robots can thus increase their learning
speed and thereby the overall performance of the group by simply
observing the other group members without requiring them to stick to a
certain communication protocol that would provide the necessary
information. With the presented approach, a robot is able to infer the
behavior that the observed demonstrator is performing and to replay
the beneficial behavior with its own capabilities.
In addition, the presented approaches allow the robots to apply
imitation even if the group is heterogeneous. Normally, the
performance of a group degrades if robots with incompatible
capabilities imitate each other. Capability differences arise if robot
morphologies differ in a robot group. This is the case if different
robots from different manufacturers form a robot group that has to
achieve shared goals. This thesis presents an approach that is able to
determine similarities or differences between robots. This can guide
the robots in a heterogeneous robot group in order to determine those
robots for imitation that are most similar to themselves.
Work descriptions are informal notes taken by developers to summarize work achieved in a particular session. Existing studies indicate that maintaining them is a distracting task, which costs a developer more than 30 min. a day. The goal of this research is to analyze the purposes of work descriptions, and find out if automated tools can assist developers in efficiently creating them. For this, we mine a large dataset of heterogeneous work descriptions from open source and commercial projects. We analyze the semantics of these documents and identify common information entities and granularity levels. Information on performed actions, concerned artifacts, references and new work, shows the work management purpose of work descriptions. Information on problems, rationale and experience shows their knowledge sharing purpose. We discuss how work description information, in particular information used for work management, can be generated by observing developers' interactions. Our findings have many implications for next generation software engineering tools.
Paper: Walid Maalej and Hans-Jörg Happel, Can Development Work Describe Itself? In Proceedings of the 7th IEEE Conference on Mining Software Repositories, IEEE CS, 2010.
The topologically adaptable snake model, or simply Tsnakes,
is a useful tool for automatically identifying
multiple segments in an image. Recently, in [4], a novel
approach for controlling the topology of a T- snake was
introduced. That approach focuses on the loops formed
by the projected curve which is obtained at every stage
of the snake evolution. The idea is to make that curve the
image of a piecewise linear mapping of an adequate
class. Then, with the help of an additional structure, the
loop-tree, it is possible to decide in O(1) time whether
the region delimited by each loop has already been
explored by the snake. In the original proposal of the
Loop Snakes model, the snake evolution is limited to
contraction and there is only one T-snake that contracts
and splits during evolution. In this paper we generalize
the original model by allowing the contraction as well as
the expansion of several T-Snakes.
Learning and imitation in heterogeneous robot groupsWilli Richert
As robots become increasingly affordable, they are used in ever more
diverse areas in order to perform increasingly complex tasks. These
tasks are typically preprogrammed by a human expert. In some cases,
however, this is not feasible -- either because of the inherent
complexity of the task itself or due to the dynamics of the
environment. The only possibility then is to let the robot learn the
task by itself. This learning process usually involves a long training
period in which the robot experiments with its surroundings in order
to learn the desired behavior. If robots have to learn a shared goal
in a group, the robots should imitate each other in order to reduce
their individual learning time. The question how this can be done in a
robot group has been considered in this thesis, i.e., how robots in a
group can learn to achieve their shared goal and imitate
each other in order to increase the performance and the speed of
learning by spreading the learned knowledge in the group.
To allow for this intertwined learning and imitation, a dedicated
robot architecture has been developed. On the one hand, it fosters
autonomous and self-exploratory learning. On the other hand, it allows
for manipulating the learned knowledge and behavior to account for new
knowledge gathered by the imitation process. Learning of behavior is
achieved by separately learning at two levels of abstraction. At the
higher level, the strategy is learned as a mapping from abstract
states to symbolic actions. At the lower level, the symbolic actions
are grounded autonomously by learned low-level actions.
The approaches of imitation presented in this thesis are unique in
that they relieve the requirements that governed multi-robot imitation
so far. It enables robots in a robot group to imitate each other in a
non-obtrusive manner. The robots can thus increase their learning
speed and thereby the overall performance of the group by simply
observing the other group members without requiring them to stick to a
certain communication protocol that would provide the necessary
information. With the presented approach, a robot is able to infer the
behavior that the observed demonstrator is performing and to replay
the beneficial behavior with its own capabilities.
In addition, the presented approaches allow the robots to apply
imitation even if the group is heterogeneous. Normally, the
performance of a group degrades if robots with incompatible
capabilities imitate each other. Capability differences arise if robot
morphologies differ in a robot group. This is the case if different
robots from different manufacturers form a robot group that has to
achieve shared goals. This thesis presents an approach that is able to
determine similarities or differences between robots. This can guide
the robots in a heterogeneous robot group in order to determine those
robots for imitation that are most similar to themselves.
Work descriptions are informal notes taken by developers to summarize work achieved in a particular session. Existing studies indicate that maintaining them is a distracting task, which costs a developer more than 30 min. a day. The goal of this research is to analyze the purposes of work descriptions, and find out if automated tools can assist developers in efficiently creating them. For this, we mine a large dataset of heterogeneous work descriptions from open source and commercial projects. We analyze the semantics of these documents and identify common information entities and granularity levels. Information on performed actions, concerned artifacts, references and new work, shows the work management purpose of work descriptions. Information on problems, rationale and experience shows their knowledge sharing purpose. We discuss how work description information, in particular information used for work management, can be generated by observing developers' interactions. Our findings have many implications for next generation software engineering tools.
Paper: Walid Maalej and Hans-Jörg Happel, Can Development Work Describe Itself? In Proceedings of the 7th IEEE Conference on Mining Software Repositories, IEEE CS, 2010.
The topologically adaptable snake model, or simply Tsnakes,
is a useful tool for automatically identifying
multiple segments in an image. Recently, in [4], a novel
approach for controlling the topology of a T- snake was
introduced. That approach focuses on the loops formed
by the projected curve which is obtained at every stage
of the snake evolution. The idea is to make that curve the
image of a piecewise linear mapping of an adequate
class. Then, with the help of an additional structure, the
loop-tree, it is possible to decide in O(1) time whether
the region delimited by each loop has already been
explored by the snake. In the original proposal of the
Loop Snakes model, the snake evolution is limited to
contraction and there is only one T-snake that contracts
and splits during evolution. In this paper we generalize
the original model by allowing the contraction as well as
the expansion of several T-Snakes.
Reflective Learning at Work – MIRROR Model, Apps and Serious GameseLearning Papers
This report discusses the initial results of a 4-year FP7 research project that developed a theoretical model and worked on the creation and evaluation of a range of ‘Mirror’ apps based on our Mirror reflection model. The findings divulge how the apps and serious games can facilitate reflectionº at work, by empowering employees to learn by reflection on their work practice and on their personal learning experiences.
A Conceptual Model for Ontology Based LearningIJORCS
Utilizing learning features by many fields like education, artificial intelligence, and multi-agent systems, leads to generation of various definitions for this concept. In this article, these field’s significant definitions for learning will be presented, and their key concepts in each field will be described. Using the mentioned features in different learning definitions, ontology will get presented for the concept of learning. In the ontology, the main ontological concepts and their relations have been represented. Also a conceptual model for learning based on presented ontology will be proposed by means of model and modeling description. Then concepts of presented definitions are going to be shown in proposed model and after that, the model’s functionality will be discuss. Twelve main characteristics have been used to describe the proposed model’s functionality. Utilizing learning ontology to improve the proposed conceptual model can be used also as a guide to model learning and also can be useful in different learning models’ comparison. So that the key concepts which can be used for considered learning model will be determined. Furthermore, an example based on proposed ontology and definition features is explained.
Fundamentals of object orientation, objects, classes, classification and object models delivered to post-graduate students of Object Oriented Software Engineering.
Learning, technology and collaboration in mobile environmentsThe Open University
This talk identifies the methodological challenges of trying to satisfy multiple stakeholders when evaluating learning and technology use in informal settings. A method for achieving this is proposed based on the specification of a semiotic and a technological space, and referring to Engesgtrom's (1987) extended model of human activity.
Software Reuse and Object-Oriented Programmingkim.mens
These slides on Software Reuse and Object-Oriented Programming are part of the course LINGI2252 “Software Maintenance and Evolution”, given by Prof. Kim Mens at UCL, Belgium
Reflective Learning at Work – MIRROR Model, Apps and Serious GameseLearning Papers
This report discusses the initial results of a 4-year FP7 research project that developed a theoretical model and worked on the creation and evaluation of a range of ‘Mirror’ apps based on our Mirror reflection model. The findings divulge how the apps and serious games can facilitate reflectionº at work, by empowering employees to learn by reflection on their work practice and on their personal learning experiences.
A Conceptual Model for Ontology Based LearningIJORCS
Utilizing learning features by many fields like education, artificial intelligence, and multi-agent systems, leads to generation of various definitions for this concept. In this article, these field’s significant definitions for learning will be presented, and their key concepts in each field will be described. Using the mentioned features in different learning definitions, ontology will get presented for the concept of learning. In the ontology, the main ontological concepts and their relations have been represented. Also a conceptual model for learning based on presented ontology will be proposed by means of model and modeling description. Then concepts of presented definitions are going to be shown in proposed model and after that, the model’s functionality will be discuss. Twelve main characteristics have been used to describe the proposed model’s functionality. Utilizing learning ontology to improve the proposed conceptual model can be used also as a guide to model learning and also can be useful in different learning models’ comparison. So that the key concepts which can be used for considered learning model will be determined. Furthermore, an example based on proposed ontology and definition features is explained.
Fundamentals of object orientation, objects, classes, classification and object models delivered to post-graduate students of Object Oriented Software Engineering.
Learning, technology and collaboration in mobile environmentsThe Open University
This talk identifies the methodological challenges of trying to satisfy multiple stakeholders when evaluating learning and technology use in informal settings. A method for achieving this is proposed based on the specification of a semiotic and a technological space, and referring to Engesgtrom's (1987) extended model of human activity.
Software Reuse and Object-Oriented Programmingkim.mens
These slides on Software Reuse and Object-Oriented Programming are part of the course LINGI2252 “Software Maintenance and Evolution”, given by Prof. Kim Mens at UCL, Belgium
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Model with different levelsofabstraction. This is thetoplevel. Containingthe elements wewant to understand and support: activityonthework arena, reflectiononthatwork, and particularlythetransitionsbetweenthem (hence separate steps). Cycleitselfconsistenswithotherlearningcycles in theliteratureonlearing.
Tasks in the i* modelsinformedtheselectionof a setofsteps for thereferencemodel
Diagramoutlining a story ofreflectivelearning in a hospital. (Story designed to describetheuseof a tool in MIRROR, how it is intended to support reflectivelearing. E.g. describinguserrequirements! Could be storyboard). Case: doctor in a hospital documenting a conversationwiththe husband of a stroke patient. Individuallyreflecting, gettingcomments from his team, and recognizing a more general issuethat is broughtinto a bi-weeklymeeting and leads to changes in theworkroutines (e.g. organizaitonallevel)
2a) = capture data relevant to reconstruction of /reflection on work experience7b) = provide data relevant to the reconstruction of experience
..skipping the middle cycles for purposes of illustrating
6b) = provide data on related experiences10b) = capture reflection outcomes
