Indire, sito ufficiale
Istituto Nazionale di Documentazione, Innovazione e Ricerca Educativa MIUR
immagine di contorno      Formazione separatore dei progetti      Documentazione separatore barra alta      Didattica separatore barra alta      Comunicazione separatore barra alta Europa
contorno tabella centrale
MEDIA EDUCATION

Imparare facendo

Contributo di Daniele Baranzini al 4 International Conference on New Educational Environments ICNEE di Lugano

di Francesco Di Martile
24 Settembre 2003

4th International Conference on New Educational Environments ICNEE, May 8-11, Lugano

LEARNING BY DOING: IF, AT FIRST YOU DONT SUCCEED

 

Stefan String (stuering@iff.fhg.de)

Alberto Trasi (trasi@iff.fhg.de)

Fraunhofer Institut IFF

Dept. Interactive Visualisation and Simulation

Sandtorstrasse 22, 39106 Magdeburg, Germany

 

Daniele Baranzini (baranzid@tcd.ie)

Paul Liston (listonp@tcd.ie)

Aerospace Psychology Research Group

Dept. of Psychology

Trinity College, Dublin 2, Ireland

 

 

 

KEYWORDS: Virtual Reality, Maintenance Training, Human Factors, Authoring Tools

 

 

INTRODUCTION

 

Theory Vs practice training

Within the last few years, technical equipment has become more and more complex. This requires an increasing level of expertise from both the operator and the maintenance staff. Whereas information technology has been successfully applied in the field of teaching theory, there are only a few applications in the field of practice training. Traditional training methods, such as printed documentation and slide shows, are often not sufficient to convey the entire complexity of a machines design and its functions. Therefore, it is still common to train operators and maintenance staff utilising a piece of real equipment. For this purpose, manufacturing companies even maintain specialised training centres that are equipped with a variety of training equipment. Although this traditional approach provides adequate training, there are some disadvantages that have become more apparent within the last few years: training centres are bound to a specific location, experts are only available locally, there is an increasing variety of products, the cost for equipment, and so on. By means of Virtual Reality (VR) these disadvantages can be eliminated or at least diminished.

 

The aim of the ongoing European funded project AITRAM (Advanced Integrated TRAining in Aeronautics Maintenance European Commission, 5th framework program, IST Programme, Key action III, Multimedia content and tools), is the improvement of the learning process of aeronautic maintenance technicians through the development of an advanced training system based on the VR technology.

 

 

 

REQUIREMENT FOR A CREDIBLE TRAINING SIMULATION

 

When dealing with training media it is impossible to avoid the fidelity question (Hays and Singer, 1988). Two types of fidelity can be addressed in training simulations: physical fidelity and psychological fidelity (Sian and Robertson, 1999). Physical fidelity is the degree to which real-world operational equipment is reproduced (Goldstein, 1993). Psychological fidelity, on the other hand, can be conceived as the degree to which training tasks reproduce actual behaviours, task situations or behavioural processes that are required for the job.

 

This has implications for the requirements of the AITRAM solution. From our point of view fidelity is an important dimension in the development of training applications in that it significantly contributes to the credibility of a training simulation in a very substantial way (Hintze et al., 1999).

 

An essential characteristic of the AITRAM application is a high grade of interactivity. In contrast to many other developments that are mostly fly-through with relatively few user interactions the work in AITRAM is primarily focussed on user interaction. The technical system must be modelled close to reality in order to attain realistic training conditions. This means the model must behave as the real equipment does and also react to user actions in the same way. More importantly, technicians need to be able to perform in the synthetic environment all those relevant actions which the technician would perform in the real world.

 

 

THE TRAINING STRATEGY

 

There are different training strategies and methods relevant to the use of simulators in training (Patrick, 1992). It is an open question as to which strategy will work best with a training system based on a VR tool. This is an empirical question that should be answered by experimental tests. Different strategies may be appropriate to different trainee groups and different training goals. Different organisations and cultures may require different approaches. It is possible to distinguish between shallow-end and deep-end strategies.

 

In the shallow-end strategy, the task is initially made as simple as possible, and as much assistance as possible is given to the trainee. As the trainee masters the task the difficulty is increased and/or the level of support is decreased. The idea of this approach is that the trainee is instilled with a sense of competence; of being able to cope. The training gives a high sense of achievement and is perceived positively, with the pace of the training being adjusted to the trainee.

 

On the other hand, the deep-end strategy exposes the trainee to the full complexity of the task from the start, with guidance and feedback only at the end of the session. The task is very difficult from the start, but each time it is attempted the trainee becomes more successful at it by learning to deal with the problems more successfully. Initially, this type of training impacts quite negatively upon the trainee, but with persistence the task can be mastered. The idea of this approach is to foster resourcefulness, problem solving and creativity in the learning process. By working out the solutions for themselves trainees have a greater confidence in tackling new tasks. This could be a very valuable attribute in the maintenance environment where tasks often have to be done for the first time under commercial and time pressure.

 

The training modes

 

In the design of the AITRAM system we decided not to adhere strictly to one training strategy or another. The development of the application is based on the implementation of four different modes. This provided more flexibility to the training system as it makes the tool applicable to a large range of trainees with different levels of expertise and task knowledge.

 

Discovery mode

In the discovery mode trainees do not deal with a procedure in a task but with the scenario per se. First of all, the trainees become confident with the scenario without focusing their minds on a particular procedure or task configuration. Secondly, for those trainees who are not confident with a synthetic environment, this mode can be a good starting point to learn how to navigate inside a near-new world. One benefit of this mode lies in its ability to reduce the anxiety that trainees may feel when introduced to a piece of technology that is unfamiliar to them.

 

Presentation mode

The presentation is comparable to an interactive video where the users can observe the execution of the task procedure, determining the progress and the viewpoints on their own and where it is possible to get more details on specific topics. Even if possible, it is not necessary to interact with the objects.

 

Graphical description of the four modes

 

Depending on the possibility of having automatic assistance or not it is possible to distinguish between Guided and Free modes.

 

Guided mode

In this modality the trainees have to be active. Using the knowledge acquired with the presentation mode, and guided by the system, they have to perform a given task, by manipulating objects in the virtual environment (VE). They receive task-related hints and explanations. The order of subtasks is given by the system. This learning by doing approach (with assistance) is instrumental in helping the trainee to really learn the job.

 

Free play mode

In free training mode the tasks get more complex and the hints and explanations are only available on demand. It is possible to collect every request of help and consider them for the evaluation of the training session.

 

 

CONCLUSION

 

Currently, there is a need to support maintenance training using complex equipment. A credible training simulation should not consist solely of sophisticated visualisation and an immersive user interface; it should also include a high-fidelity representation of the real system. The modelling methodology developed in AITRAM allows for the development of appropriate authoring systems that enable instructors to develop training scenarios designed around specific selected training goals and objectives.

 

Herein lies the attraction and utility of the AITRAM system: a high fidelity training solution which is focused on user interactions, thereby achieving realistic training conditions and leading to optimal transfer of training from the training course to the workplace.

 

 

REFERENCE SECTION

 

GOLDSTEIN, I. (1993). Training in organizations (3rd ed.) Pacific Grove, CA: Brooks/Cole.

HAYS, R. and  SINGER, L. (1988). Simulation Fidelity in Training System Design. New York: Springer-Verlag

HINTZE, A., SCHUMANN, M., STUERING, S. (1999) Distributed Virtual Training Applications for Education of Maintenance and Service Personnel. Interservice/Industry Training, Simulation and Education Conference, Nov 29 - Dec 2, 1999 , Orlando, FL/USA

SIAN,B. and ROBERTSON, M. (1999). Line-oriented Human Factors training: MRM III. In FAA/AAM Human Factors in Aviation Maintenance and Inspection Research Phase Reports (1991-1999)/Phase VIII Progress Report /Chapter 3..

PATRICK, J. (1992). Training Research and Practice, New York: Academic Press.

 
Articoli correlati

Social network, narrazioni e identità digitali
di Redazione (15 Giugno 2015)

Il tablet e linclusione scolastica
di Silvia Panzavolta (31 Ottobre 2014)

Manipolare quel che si crea, un altro modo per imparare
di Lorenzo Guasti (18 Luglio 2014)

Quando la classe è digitale
di Elena Mosa (01 Luglio 2013)

Soluzioni di apprendimento e tecnologie didattiche
di M. Gentile, G. Filosi, M. R. Gaetani, F. Pisanu (12 Dicembre 2012)

Rappresentare la conoscenza
di Francesco Vettori (05 Luglio 2012)

Dalle mappe concettuali allo spazio digitale
di Francesco Vettori (03 Luglio 2012)

I database digitali e la carta geografica
di Francesco Vettori (03 Luglio 2012)

Dalle digital skills alla digital competency
di Elena Mosa (02 Aprile 2012)

Il contributo dellUnione Europea per ogni europeo digitale
di Fiora Imberciadori (02 Aprile 2012)

A colloquio con lEuropa sulle classi creative
di Elena Mosa (01 Aprile 2012)

Intervista al Prof. Alfonso Molina
di Francesco Vettori (30 Marzo 2012)

Il valore educativo delle dinamiche del gioco
di Andrea Benassi (21 Febbraio 2012)

Visible Thinking, Slow Learning
di Isabel de Maurissens (30 Gennaio 2012)

Crossmedialità e apprendimento
di Isabel de Maurissens e Silvia Panzavolta (30 Settembre 2011)