Apresentação do Profº Helder Coelho no I Simpósio Internacional de Ensino na Saúde.

1. Teaching and Learning with
Simulation Environments
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2.  “Medical students
want to focus
experiential learning on
preparing for the
future.”
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3. A narrative (movie) of
reality (in Literature,
novels are seen often as
photographs of reality).
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4.  Third way of doing science, in contrast to
both deduction and induction.
 An effective tool for discovering surprising
consequences of simple assumptions.
 Instructional scenario, an environment and a
method of training students and teachers.
 A form of experiential learning.
 A game, role-play, and activity that acts as a
metaphor.
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5.  “Simulation means driving a model of a system
with suitable inputs and observing
corresponding outputs” (Bratley, Fox and
Schrage, 1987).
 Purposes: prediction, performance,
training,
entertainment,
education,
proof and discovery.
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6.  Simulation lies in prediction, proof and
discovery.
 In Social Sciences, the aim is to discover
important relationships and principles from
very simple models.
 The more simple the model, the easier it may
be to discover and understand the subtle
effects of its hypothesized mechanisms.
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7.  Induction is the discovery of patterns in
empirical data. Example: analysis of opinion
surveys and the macro-economic data.
 Deduction involves specifying a set of axioms
and proving consequences that can be
derived from those assumptions.
 The discovery of equilibrium results in game
theory using rational choice axioms and it is a
good example of deduction.
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8. Like deduction, it starts with a set of explicit
assumptions. But unlike deduction, it does not prove
theorems. Instead, a simulation generates data that
can be analyzed inductively. Unlike typical
induction, the simulated data comes from a
rigorously specified set of rules rather than direct
measurement of the real world. While induction can
be used to find patterns in data, and deduction can
be used to find consequences of assumptions,
simulation can be used as an aid in intuition.
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9.  Simulation is a way of doing thought
experiments. While the assumptions may be
simple, the consequences may not be at all
obvious.
 The large-scale effects of locally interacting
agents are called “emergent properties” of
the system. When the agents use adaptive
rather than optimizing strategies, deducing
the consequences is often impossible;
simulation becomes necessary.
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10.  Promote the use of critical and evaluative
thinking.
 Support concept attainment through
experiential practice.
 Help students appreciate more deeply the
management of health care (diagnostics).
 Reinforce other skills, such as debating,
critical thinking, and research.
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11.  Simulations are cheaper to create than real
life counterparts.
 They are easy to construct.
 They remove an element of danger from the
situation.
 They can be paused, whereas real life cannot.
Pausing allows more time for students to
assess what´s going on.
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12.  Resources and time are required to develop
quality learning experience.
 Simulated experiences are more realistic than
some other techniques and they can be so
engaging and absorbing that students forget
the educational purpose of the exercise.
 It has an element of competition, yet the aim
is not win, but to acquire knowledge and
understanding.
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13.  Prepare the case studies in advance as much
as possible.
 Monitor the process closely:
 Are the desired instructional outcomes well defined?
 Does the student demonstrate an understanding of his/her
role?
 Are problem-solving techniques in evidence?
 Will follow-up activities be necessary?
 Does it offer a suitable measure of realism for the group?
 Consider what to assess.
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15.  Simulations provide multiple chances to
practice, including making attempts with
higher risks and failures, and to learn, retry,
and master new skills faster and with less
effort than through experiences not
mediated by computers.
 Stimulate development of heuristic skills in
teachers.
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16.  The goal of advancing technologies in
education can be achieved through creative
application of education simulators.
 Online learning environments link pedagogy,
technology and the learner need.
 Systemic challenges of teacher education
include fundamental conceptions of teaching
and learning, organization of knowledge,
assessment practices and results, and
engagement of a global community practice.
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17.  This shift is based on self-direction and
personal validation, in a complex yet
repeatable practice environment.
 It is supported by emerging interdisciplinary
knowledge coming from fields such as
Cognitive Science and Complexity Science. AI
and Neurosciences are today at the front line
supporting the revolution of MOOC´s for
universal higher education.
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18.  They simulate an activity that is “real”.
 They are “hands-on”, involving students, so
they become participants, not mere listeners
or observers. Students learn better from their
own experiences than having others´
experiences related to them.
 They are motivators for learning. Student
involvement in the activity is so deep that
interest in learning, and along its subject
matter develops.
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19.  They are tailored to the student. When
simulations are designed specifically for their
audience, they can take development
requirements into consideration.
 They are inspirational. Student input is
welcome and activities are designed to
encourage students to enhance the activity
by contributing their own ideas.
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20.  They are developmentally valid. Simulations
take into account the students´
developmental level.
 They are empowering. Students take on
responsible roles, find ways to succeed, and
develop problem solving tools as a result of
the interaction.
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21.  A Computer-Based Educational simulation has 3
components:
1) A data model or set of algorithms that can be
manipulated by the learner and provides
dynamic feedback based on those
manipulations.
2) A role for the learner to adopt.
3) An objective to achieve, or set of tasks to
complete, using the data model.
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23.  Once the exercise is completed, a debriefing
is also necessary to fully assess and go
through what happened, and ascertain
student comments and reactions to the
experience.
 Simulation issues, processes and outcomes
can then be linked to course concepts and
learning objectives.
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24.  Improved student awareness of a topic or a
subject.
 Real-world and practical application of course
concepts.
 Enhanced analytical ability to resolve issues
and problems in the subject matter.
 Increased exposure to complex real-life
experiences.
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25. 1) Integrating seemingly disparate topics that
have definable relationships.
2) Learning a system or model of concepts
through experimentation.
3) Practicing difficult, rare, or dangerous tasks.
4) Decision-making and prioritizing.
5) Working with ambiguity.
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27.  Dynamic of epidemic diseases (non linear and
stochastic processes): generation measles.
 Mathematic model: Kermack-McKendrick
equation with Susceptible S(t), Infective I(t), e
Removed R(t).
 dS/dt=-rSI, dI/dt=rSI-pI, dR/dt=pI
 Environment: 2D grid
 Agents: blue (susceptible), red (infective);
memory of family, work place.
 Population of agents: variable size.
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31. Arab Spring (2011) + SNs: strong connectivity of tweets
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32.  Simulations are one way to incorporate an
innovative use of technology into the
learning environment.
 Technology is not needed for the creation or
administration of a simulation but it can
enhance the overall presence and impact of
the simulation for students.
 Start with an easy and simple tool, such as
NetLogo, before going to Repast or Mason.
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33.  Learn the Logo language by looking to small
programs and running them. Later on, you can be
inspired to copy parts of them.
 The interface is simple, but you must learn how to
complicate it, by transforming into a dashboard,
with fixed areas apart the window where the
experiences are to be observed.
 Two areas are necessary, the control one (command
of variables) and the dedicated to display graphics
of the all measurements.
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34.  Run Conway´s Game of Life in NetLogo.
 Be confident, and face the task of
development process. It is a difficult one, but
without this exercise you don´t feel at easy.
Remember you must think about creating a
simulation from start to finish.
This activity, rather than follow a linear step-by-step
approach, require students to be involved, creative
and innovative, as well as anticipate problems and
solutions.
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35.  Instead of just implementing something that
had already been developed, be responsible for
the development: a different approach to
learning than most of the students are used to!
 By using simulations to enhance traditional
teaching and learning, there is an opportunity
to participate in active learning.
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36.  Keep it simple (KISS).
 Encourage technology-related professional
development, in order student feel at easy
with the tools.
 The learning outcome is: the more they view
technology as an effective classroom tool for
1) analyzing info, 2) addressing critical
thinking skills, and 3) learning new concepts.
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37.  Repetitive performance of intended cognitive
or psychomotor skills in focused domain
coupled with rigorous skills assessment, that
provide learners specific, informative
feedback, that results in increasingly better
skills performance, in a controlled setting.
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38.  Inherently reductionist – you can´t model
everything.
 Require a commitment to discovery-oriented
learning and related support.
 More work to create than most other types of
educational technology (creation of a model).
 More difficult to evaluate what students learn
than many other types of educational
technology (need of evaluation methods).
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39.  The use of simulators for clinical skills training
increased because:
Simulation has been defined as a situation in
which a particular set of conditions is created
artificially in order to study or experience
something that is possible in real life.
 Simulator is a device that enables the
operator to reproduce or represent, under
test conditions, phenomena likely to occur in
actual performance.
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40.  Simulation based medical education can be
defined as any educational activity that
utilizes simulative aides to replicate clinical
scenarios. Simulation tools serve as an
alternative to the real patient.
 Apprentices can make mistakes and learn
from them without the fear of distressing the
patient.
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41.  Low-fidelity: static, and lack the realism or
situation context. They are used to teach
novices basics of technical skills. Example:
intravenous insertion arm.
 Moderate-fidelity: resemblance of reality with
features as pulse, heart sounds and breathing
sounds, but without the ability to talk and they
lack chest or eye movements.
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43.  They can be used for both the introduction
and deeper understanding of specific
complex competencies. Example: cardiology.
 High-fidelity: for intervention with computers
that drive manikins to produce physical signs
and feed physiological signs to monitors.
They resemble reality, by talking,breathing,
blinking and respond to physical and
pharmacological interventions. Example: a
human patient, obstetric case study.
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45.  Computer-based simulations have a history
as long as the development of the computer.
 The technique of using simulations for
teaching and learning start when students
faced solving problems, through role play and
the use of data.
 The use of simulations in education allow the
possibility of dynamic discovery-oriented
learning.
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47.  Team training emergency.
 From self to social cognition.
 Patient simulation as social practice.
 Identifying and training non-technical skill for
teams in acute medicine.
 Discrete-event in health care clinics.
 Measuring team performance in simulation-
based training.
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48.  Medicine Simulation Center:
 Medical training facility that incorporates 5 types
of simulation, including:
▪ Standardized patients and teaching associates.
▪ Human patient simulation.
▪ Virtual reality.
▪ Task trainers.
▪ Computerized simulation.
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49.  On disease dynamics: spread of influenza
through a population.
 The Lancet, Vol. 384, Special Issue, S20, 19
November, 2014.
“Effects of social networks on disease dynamics
of influenza through a population”.
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50.  MOOC´s: Interdisciplinary Course on
“Medical Education in the New Millennium”.
 Platform: Stanford Open EdX.
 Course topic: Medicine & Health.
 Speakers: Daphne Koller (founder of
Coursera) et al.
 Structure: Eleven week Course includes
discussions, virtual reality, simulation,
cognitive views, ...
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51.  Biological simulation.
 Medical simulation.
 Construction management simulation.
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52. InfoTech– Medical simulation
www2.technologyreview.com/spotlight/infotec
h/?a=1
 Healthcare Modeling and Simulation.
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53.  Flaminio Squazzoni and Niccolò Casnici:
“Is Social Simulation a Social Science
Outstation? A Bibliometric Analysis of the
Impact of JASSS”, JASSS, Vol. 16 (1), 10,
2013.
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