GustavoRibeirodaCostaAlves · Paraná–Entre&Ríos&–Argen1na 13Sepembre2017 Slide1 ADQUISICIÓNDECOMPETENCIASEXPERIMENTALESENINGENIERÍA* CONTRIBUCIÓNDELOSLABORATORIOSREMOTOS*

Paraná – Entre Ríos – Argen1na 13 Sep1embre 2017 Slide 1

ADQUISICIÓN DE COMPETENCIAS EXPERIMENTALES EN INGENIERÍA CONTRIBUCIÓN DE LOS LABORATORIOS REMOTOS

Gustavo Ribeiro da Costa Alves


Estrutura •  Laboratórios presenciais (hands-‐on), remotos e virtuais (simulação) •  Educação (ensino & aprendizagem) em Engenharia (EE) • A1vidades e competências laboratoriais •  Estratégia(s) de E&A baseadas em laboratórios remotos e virtuais

•  Exemplo na área da Engenharia Eletrotécnica: circuitos elétricos e electrónicos

• Conclusão


Laboratórios presenciais (hands-‐on), remotos e virtuais (simulação)

• Critério •  Tipo de acesso

•  Local •  Remoto

•  Natureza •  Real •  Simulada

• Comp. experimental vs. 1po de lab. •  Soysal (2000) – Eng. Elétrica •  Ma & Nickerson (2006)

Simulador

Lab. remotos

Hands-‐on

Lab. virtuais

Real

Local

Remoto

Simulado


EE: Modelo ensino/aprendizagem

Cálculo

Hands-‐on

Primeiras Escolas de Engenharia Séc. XVIII

Royal Society mo]o 'Nullius in verba’ (1660): “… express the determina1on of its Fellows … to verify all statements by an appeal to facts determined by experiment.”

Max Planck: “An experiment is a ques1on which science poses to Nature and a measurement is the recording of Nature’s answer.”

Lyle Feisel (2005): “The value of combining theory and prac1ce traced back to the 1st engineering school in the US, the US Military Academy, founded at West Point, NY in 1802.”


Simulações em computador Meados do Séc. XX

Séc. XX -‐ Anos 70-‐80 Um novo ator: O computador pessoal!


Um PC por bancada laboratorial Finais do Séc. XX Inícios do Séc. XXI

Cálculo

Lab. virtual

Hands-‐on


Second-‐Best to Being There (SBBT) Aktan, Bohus and Shor (1996)

Cálculo

Lab. remoto

Hands-‐on

Instrumentação controlada por computador Séc. XX -‐ Finais dos anos 60 Controlo via Internet Séc. XX -‐ Década de 90


GPIB


Cálculo

Lab. virtual

Lab. remoto

Hands-‐on Hands-‐on, simulated, and remote labs: A literature review Ma and Nickerson (2006) Developing the TriLab Abdulwahed and Nagy (2010) Learning outcome achievement in non-‐tradi1onal (virtual and remote) versus tradi1onal (hands-‐on) laboratories: A review of the empirical research Brinson (2015)

The Impact of Remote and Virtual Access to Hardware upon the Learning Outcomes of Undergraduate Engineering Laboratory Classes Euan Lindsay’s PhD (2005) Weigh1ng and sequence of use of different lab environments in the teaching-‐learning process Alves et al. (2008)



Five Major ShiDs in 100 Years of EE

1.  A shir from hands-‐on and prac1cal emphasis to engineering science and analy1cal emphasis

2.  A shir to outcomes-‐based educa1on and accredita1on 3.  A shir to emphasizing engineering design 4.  A shir to applying educa1on, learning, and social-‐behavioral sciences

research 5.  A shir to integra1ng informa1on, computa1onal, and communica1ons

technology in educa1on

Froyd, Wankat, and Smith (2012)


5.  A shir to integra1ng ICCT in educa1on •  content delivery: television, videotape, and the Internet •  programmed instruc1on: individualized student feedback •  personal response systems (clickers) •  computa1onal technologies •  intelligent tutors: second phase of individualized student feedback •  simulaIons •  games and compe11ons •  remote laboratories •  grading

Five Major ShiDs in 100 Years of EE

Froyd, Wankat, and Smith (2012)


The Fundamental ObjecKves of Engineering InstrucKonal Laboratories

•  Lyle D. Feisel and George D. Peterson, “A Colloquy on Learning Objec1ves For Engineering Educa1on Laboratories”, Proceedings of the American Society for Engineering Educa1on, p. 12, 2002.

•  Lyle D. Feisel and Albert J. Rosa, ”The Role of the Laboratory in Undergraduate Engineering Educa1on," Journal of Engineering Educa1on, pp. 121-‐130, January 2005.


The Role of the Laboratory in Undergraduate EE

The Fundamental Objec1ves of Engineering Instruc1onal Laboratories

•  Objec1ve 8: Psychomotor •  Objec1ve 9: Safety •  Objec1ve 10: Communica1on •  Objec1ve 11: Teamwork •  Objec1ve 12: Ethics in the Lab •  Objec1ve 13: Sensory Awareness

•  Objec1ve 1: Instrumenta1on •  Objec1ve 2: Models •  Objec1ve 3: Experiment •  Objec1ve 4: Data Analysis •  Objec1ve 5: Design •  Objec1ve 6: Learn from Failure •  Objec1ve 7: Crea1vity

Feisel and Rosa (2005)


ObjecIvo 2: Modelos IdenIficar as potencialidades / limitações dos modelos teóricos como ferramentas de previsão de comportamentos do mundo real. Pode incluir a capacidade de avaliar se uma dada teoria é capaz de descrever adequadamente um dado evento Ysico e ainda estabelecer ou validar uma relação entre dados obIdos por medição e princípios Ysicos subjacentes.

ObjecIve 2: Models IdenIfy the strengths and limitaIons of theoreIcal models as predictors of real-‐world behaviours. This may include evaluaIng whether a theory adequately describes a physical event and establishing or validaIng a relaIonship between measured data and underlying physical principles.


Estratégia(s) de E&A baseadas em laboratórios remotos e virtuais

• Aspectos a considerar: •  Plano curricular: objec1vos e resultados da aprendizagem! •  Recursos (materiais, infraestrutura, ambientes disponíveis, etc.)

•  Considerar tempo de aprendizagem / adaptação aos recursos disponibilizados •  Es1los de aprendizagem e métodos de ensino

•  Diversidade! •  Feedback constante e rápido.

•  Avaliação •  Combinar elementos comuns e individuais. Garan1r igualdade de oportunidade e níveis aproximados de dificuldade.

•  Promover trabalho colabora1vo na fase de aprendizagem e independência de resultados na fase de avaliação (individual)


Recursos: Laboratórios remotos e virtuais


Estratégia(s) de E&A baseadas em laboratórios remotos e virtuais

•  Exemplos na área da Engenharia Eletrotécnica: circuitos elétricos e electrónicos

VISIR@UNR: h]ps://labremf4a.fceia.unr.edu.ar/labs/visirnet/default.aspx Falstad: h]p://www.falstad.com/circuit/circuitjs.html


Virtual Instrument Systems in Reality (VISIR)

• Ingvar Gustavsson (inspired in Max Planck):

‘‘Experimen1ng could be compared to a conversa1on with nature. The experimenter asks and nature answers. The tricky thing is formula1ng a useful ques1on and above all interpre1ng the answer. The only way to learn the language of nature is performing many experiments in laboratories that can be hands-‐on or remote.”






VISIR Laboratories •  Blekinge Institute of Technology (BTH), Sweden (VISIR+) (PILAR) •  University of Deusto (UD), Spain (VISIR+) (PILAR) •  FH Campus Wien University of Applied Sciences, Austria •  Carinthia University of Applied Sciences (CUAS), Austria (VISIR+) (PILAR) •  School of Engineering – Polytechnic of Porto (IPP-ISEP), Portugal (VISIR+) (PILAR) •  National University for Distance Education (UNED), Spain (VISIR+) (PILAR) •  Indian Institute of Technology Madras (IIT-Madras), India •  Batumi Shota Rustaveli State University, Georgia •  Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil (VISIR+) •  Federal University of Santa Catarina (UFSC), Brazil (VISIR+) •  Federal Institute of Santa Catarina (IFSC), Brazil (VISIR+) •  National University of Rosario (UNR), Argentina (VISIR+) •  National University of Santiago del Estero (UNSE), Argentina (VISIR+) •  University of Hassan 1st , Morocco



Conclusão

• A integração de laboratórios remotos e virtuais no contexto de uma unidade curricular depende de vários aspectos:

•  Individuais: a vontade do responsável da UC (professores) e o grau de adesão dos alunos e alunas

•  Ins1tucionais: disponibilização de recursos e suporte à sua integração

• Objec1vos: •  dotar os alunos de mais e melhores competências experimentais •  permi1r a realização de mais experiências de forma sustentável


• Economic prac1ce + environmental protec1on

•  Experiments with electrical circuits

Remote labs as Sustainable Learning Environments

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•  Typical problem – components •  They can be damaged!


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• Economic prac1ce + environmental protec1on •  Typical problem – components – 1 •  One resistor is typically used 100-‐500 1mes and then it either gets damaged or mixed with other components and is (are) thrown away at the end of a semester.

•  One resistor has been used more than 1,000,000 1mes in VISIR (@UNED) •  Savings: (1,000,000 / 500) = 2,000 * 0.0286 = £57.2 ≃ €65.3 (in a single component)


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• Economic prac1ce + environmental protec1on •  Typical problem – components – 2 •  A simple inspec1on test made arer an individual lab assessment exercise revealed a percentage of 30% damaged ICs (OpAmp 741). One class with 16 students. 2 ICs per student. Approx. 10 ICs were damaged (per class).

•  Savings: 10 * 0.367 = £3.67 ≃ €4.18 (in a single class)


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Obrigado pela atenção!

Gustavo R. Alves IPP – ISEP -‐ CIETI [email protected]



•  Typical problem – components


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GustavoRibeirodaCostaAlves · Paraná–Entre&Ríos&–Argen1na 13Sepembre2017 Slide1 ADQUISICIÓN*DE*COMPETENCIAS*EXPERIMENTALES*ENINGENIERÍA* CONTRIBUCIÓN*DE*LOS*LABORATORIOS*REMOTOS*

GustavoRibeirodaCostaAlves · Paraná–Entre&Ríos&–Argen1na 13Sepembre2017 Slide1 ADQUISICIÓNDECOMPETENCIASEXPERIMENTALESENINGENIERÍA* CONTRIBUCIÓNDELOSLABORATORIOSREMOTOS*