Cristin-prosjekt-ID: 491696
Sist endret: 16. januar 2020, 20:14

Cristin-prosjekt-ID: 491696
Sist endret: 16. januar 2020, 20:14
Prosjekt

Process Simulation and Learning Technologies

prosjektleder

Tiina Komulainen
ved Institutt for maskin, elektronikk og kjemi ved OsloMet - storbyuniversitetet

prosjekteier / koordinerende forskningsansvarlig enhet

  • OsloMet - storbyuniversitetet

Finansiering

  • Høgskolen i Oslo og Akershus
    Prosjektkode: 160054

Klassifisering

Vitenskapsdisipliner

Kjemisk prosessteknologi • Matematisk modellering og numeriske metoder • Simulering, visualisering, signalbehandling, bildeanalyse • Fagdidaktikk

Emneord

Simulatortrening • Forestilling • Vurdering • Feedback

Kategorier

Prosjektkategori

  • Doktorgradsprosjekt

Kontaktinformasjon

Telefon
45553909
Sted
Laura Marcano

Tidsramme

Avsluttet
Start: 1. september 2015 Slutt: 17. oktober 2019

Beskrivelse Beskrivelse

Tittel

Process Simulation and Learning Technologies

Populærvitenskapelig sammendrag

An intelligent tutoring system will help process operators to train technical skills on their own prior to team training sessions. By integrating process technology, simulation, optimization and pedagogy the intelligent tutoring system will enable off-site individual simulator training and enhance the learning effect of the on-site team simulator training. The intelligent tutoring system will assist the instructor during simulator training team sessions.

Research questions:

  1. How, when and where should individual technical simulator learning be applied? How to integrate the individual simulator training to the on-site training program?
  2. How should the learning be assessed, how to give feedback online during scenarios? Feedback and assessment through key performance indicators (technology), optimal path finder (technology) and recommender system (technology)
  3. How should the intelligent tutor system be implemented in the simulator platform (technology)?
  4. How should the individual simulator training be designed to support on-site simulator training (pedagogics)? How to create realistic training situation off-site?

Vitenskapelig sammendrag

Simulator training is widely used in different industries and in academia as a teaching tool. An expert instructor, who guides the users through the learning process with the simulator by giving verbal feedback, pausing the scenarios if necessary, and sometimes by developing certain evaluations, leads the simulation sessions. However, the availability of instructors is not always enough for the training demand, which can slow down the training process, as the trainees often need to wait for the instructor’s feedback before they can proceed with their tasks. Therefore, the feasibility of combining the guidance of the instructor with an automatic live assessment and feedback will be evaluated in this work. The aim of the study is to improve the learning conditions by giving more independence to the simulator trainees.

Metode

A. Test of the platform:

At the beginning, traditional simulator training sessions will be implemented. New features, such as automatic assessment and feedback, will be integrated gradually to the simulator training sessions. This way, it will be possible to compare the learning outcomes of the different sessions, and we will be able to identify aspects that could be improve for the following sessions.

B. Learning module:

OsloMet: Decide the course and the topic for the OsloMet students in collaboration with the teacher. Design the learning module using the didactic principles (goals, contents, inner and outer framework, evaluation, participant prerequisites, etc.). Design the simulator training module and the quiz with the teacher. Implement the simulator training module o for the course. Test with students, evaluate training and exam results and develop the learning module and simulator training sessions further.

End User: Decide simulator course and pre-simulator training topic in collaboration with the simulator instructor. Design the learning module using the didactic principles (goals, contents, inner and outer framework, evaluation, participant prerequisites, etc.). Design the simulator training module and the quiz with the simulator instructor. Implement the simulator training module on the mobile platform. Test with the operators, evaluate training and exam results.

C. Time:

Fall 2016: HiOA students test1, End User case description

Spring/fall 2017: HiOA students test2, End User test0

Spring/fall 2018: HiOA students test3, End User test1

Spring 2019: HiOA students test4, End User test2

D. Group size:

HiOA students (20-120): the size of the group will depend on the corresponding course in which simulation module will be implemented; all participants will take the same mi-exam and final exam on the learning topic at the end.

End User: to be decided how many operators will be evaluated.

E. Analysis:

The simulator training records will be compared with the quiz scores. The data will be processed using Microsoft Excel and IBM SPSS Statistics.

The project has been approved by the Data Protection Official, NSD, with the number 50496.

prosjektdeltakere

prosjektleder
Aktiv cristin-person

Tiina Komulainen

  • Tilknyttet:
    Prosjektleder
    ved Institutt for maskin, elektronikk og kjemi ved OsloMet - storbyuniversitetet
Inaktiv cristin-person

Laura Marcano

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for maskin, elektronikk og kjemi ved OsloMet - storbyuniversitetet
Aktiv cristin-person

Arne Ronny Sannerud

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for yrkesfaglærerutdanning ved OsloMet - storbyuniversitetet
  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for grunnskolelærerutdanning, idrett og spesialpedagogikk ved Universitetet i Stavanger

Finn Aakre Haugen

  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for elektro, IT og kybernetikk ved Universitetet i Sørøst-Norge
  • Tilknyttet:
    Prosjektdeltaker
    ved Institutt for maskin, elektronikk og kjemi ved OsloMet - storbyuniversitetet
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Resultater Resultater

A methodology for building a data-enclosing tunnel for automated online-feedback in simulator training.

Marcano, Laura; Manca, Davide; Yazidi, Anis; Komulainen, Tiina M.. 2020, Computers and Chemical Engineering. OSLOMET, PdMVitenskapelig artikkel

On Process Simulation and Learning Technologies.

Marcano, Laura. 2019, Universitetet i Sørøst-Norge/Universitetet i Søraust-Noreg. USN, OSLOMETDoktorgradsavhandling

Review of simulator training practices for industrial operators: How can individual simulator training be enabled?

Marcano, Laura; Haugen, Finn; Sannerud, Arne Ronny; Komulainen, Tiina M.. 2019, Safety Science. USN, OSLOMETVitenskapelig oversiktsartikkel/review

Online feedback for simulator training.

Marcano, Laura. 2018, Energy Simulation Technology Exhibition and Conference. OSLOMETVitenskapelig foredrag

Using the concept of data enclosing tunnel as an online feedback tool for simulator training.

Marcano, Laura; Yazidi, Anis; Manca, Davide; Komulainen, Tiina M.. 2018, Linköping Electronic Conference Proceedings. USN, OSLOMET, PdMVitenskapelig artikkel
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