Two new papers

Two new papers

de Heleen ter Pelkwijk -
Número de respuestas: 17

Dear all, 

Checked out some new articles again today:

 I have read some other things too, but they were not that interesting.  Found some new article but I want to read them first before presenting to you.

 Does anyone else has something to share in the area “what is already known from papers and research”?

Hope to hear from you too! 

Hartelijke groet,

 Heleen

En respuesta a Heleen ter Pelkwijk

Re: Two new papers

de Patrick Parrish -

Heleen, thanks for the great articles. I have read Marc Prensky’s article on “Why NOT Simulation” and the article on “The use of simulators in basic driver training.” They make a very nice pairing, and I recommend them to others. Both articles do a nice job of helping us avoid getting caught up in the glean of a new(?)  technology, and instead take a critical evaluation of the affordances and weaknesses they offer. Here are some thoughts that came to me while reading:

  • Simulation needs to be thought of as a spectrum of learning activities. Prensky excludes Role Play, but just because the Inputs are more general, the Calculations open-ended and spontaneous, and the Outputs less technologically based, they are undertaken for the same purpose as any simulation, and have the same fundamental structure—learners enter a make-believe, but to some degree realistic, situation where the purpose is learning. Computer technology may or may not be present in a role-play, but since when did use of technology define a learning activity? (It seems to me that weather forecasting simulations need some aspect of role-play to work. The technology is only needed to provide realistic data access and, maybe, forecast generation and dissemination.)
  • I think it is ok to think of simulation as containing all of these: role-play, computer-based simulation, and hands-on practice in a non-work environment. (In this sense, the Canadian Phoenix project is simulation.)
  • Yes, simulations have limitations, but so does any instructional method. The fact that simulations can never demonstrate complete verisimilitude is not a negative in my mind. We are talking about learning experiences, not job experiences. The goal is to create situations ripe for learning, and true-to-life experiences are often fraught with complexities and compromises and quick decisions that may not be conducive to learning. Is complete “authenticity” needed for learning? What does it mean to be “authentic” anyway?
  • Weather forecasting is not a procedural process except at a very high level. This is why simulation never perfectly replicates the work environment. It has human dimension, both in terms of complex and variable approaches to analysis and decision-making processes, and in the communications and collaborative work involved. But does that make simulation ineffective?
  • It seems to me that it is ok to be less than fully realistic, since in teaching we often want to focus on a few targeted skills at a time, which in fact can be preferable in the developing stages of expertise. Simulations don’t need full verisimilitude to be effective for learning. Learning one aspect of analysis, diagnosis, or prognosis, in a controlled environment rather than a realistic, open-ended one, can be quite effective and necessary. (See “Training Complex Cognitive Skills” by  Jeroen J. G. van Merriënboer)
  • How real is valuable? There is a concept called the “Uncanny Valley” that is used in relation to the design of robots. We accept and can interact with creations artificial intelligence that are to a good degree unreal (talking teddy bears, R2D2, even CP30), but when we get to the point of almost, but not quite, real (think Spielberg/Kubrick's “Artificial Intelligence") we get really nervous, and it becomes harder to interact because we KNOW it’s not quite real, but it is so close it is uncanny and distracting and even threatening.  To be able to fully interact without the revulsion created by the uncanny valley, we need Blade Runner replicants, or Matrix creations. Can this apply to simulations as well? Can a degree of artificiality help the learning process, since full realism is nearly impossible? The answer “Yes” comes up in a couple places in Prensky’s paper, but he seems to ignore it.
  • Simulations are NOT “Level 3” evaluation in Kirkpatrick’s scheme (which is evaluation of a change in performance on the job as a result of training). They can be recreations of the work environment, but simulations are NOT the work environment. Prensky’s paper argues this point quite clearly. Simulations are a learning tool, a rich and “authentic” one, but a learning tool. They can be a valuable part of a learning assessment, but not a job performance measure. We don’t perform in a simulation in the same way we perform on the job.
  • I agree with Heleen that it is the debriefing of a simulation that is probably the most valuable portion of a simulation experience. Also, in Prensky’s terms, I think that in weather forecast simulations it is most important to focus on creating realistic Inputs, and let the humans do the “Calculations.”
  • Learners have imaginations. Stimulate them and let them imagine that they are in a work environment. There is no need to recreate reality fully in a simulation.
  • I disagree with Prensky’s final assessment, that simluations of complex, human interaction-oriented simulations should be taken with a “very large grain of salt” (except when it comes to Level 3 evaluation).  He seems to harp on the lack of exact verisimilitude, but since it is learning that we are after, I think simulations can be worth their weight in gold when it comes to engagement in authentic tasks.
  • “Authentic” – what does this mean? I use the word, and most of my colleagues do as well. But it is certainly a slippery term. Authentic is a spectrum at best, describing how close a learning task mimics a task from real life. But since real life tasks are highly complicated, including analysis, reflection, recall of prior knowledge, articulation of that knowledge, and application in decision making, what instructional task is really “inauthentic”? I think the point is that at some point we need to get learners to practice tasks they will do in real life, in as close to realistic conditions as possible. That’s what simulations do.
  • As to the question of whether simulations help transfer of learning, I think this is also the role of the instructor, in the debriefing process, for example. On the job, do we have any guarantee that workers will transfer what they should learn from their mistakes to future work tasks? It depends on the learner, how reflective they are about their work, and on the supervisor or colleagues the worker interacts with, who might help them reflect.

These thoughts stuck out from the driver simulation article:

  • Procedural tasks can be trained very effectively with simulators, but driving (and weather forecasting) are only to a small degree procedural. Instructors need to make up the difference.
  • Situational awareness is the product of experience rather than education.  (We can’t train everything.)

Cheers,

Pat

En respuesta a Patrick Parrish

Re: Two new papers

de Maja Kuna -

Thank you Heleen and Patrick (and Mark) for starting such an interesting discussion.

Here are some of my first thoughts on the topic of simulations. Some thoughts on simulations and human thinking process and then simulations as an instructional strategy.

In my understanding, simulation is a methodology used to understand relations between parts of a system or process. Simulations are useful for veryfying "what if" statements, examining possible scenarios and testing hypotheses.

“Learners have imaginations. Stimulate them and let them imagine that they are in a work environment.”

Patrick’s post makes me think about a simple idea that one of the qualities of human brain is its capacity to simulate the reality. Imagining something, predicting and anticipating is a part of a thinking process. Human mind constructs 'small-scale models' of reality and use them to reason, to anticipate events and to provide explanations (Kenneth Craik). We use simulations very often.

“Is complete “authenticity” needed for learning? What does it mean to be “authentic” anyway?”

I totally agree that authenticity of things can be easily questioned. Realty will be always a starting point and a base for a simulation, but we should keep in mind that a simulation is a simplified or symbolic representation of reality. Then a huge advantage of a simulation is in a way its non-authenticity, especially when we think about consequences of erratic actions. The consequences in simulations are fortunately not ‘authentic’, so not negative. Simulations often do not follow an ‘authentic’ time frame, as for example often they permit to observe in a short time effects that in a real world would take much longer.

Simulation as an instructional strategy, you both mentioned it, can be very useful for an assessment, however difficult to evaluate in some cases. What about simulation as a tool for formative evaluation, practice and exploration?

What level of cognitive performance can be achieved through simulation? Or what cognitive level can be evaluated using simulations? Perhaps this strategy may be useful for the higher levels in Bloom / Anderson & Krathwohl classification, so analyzing, synthesizing /creating or evaluating?

The other interesting point raised here was the connection between game and simulation. Surely they have a lot in common. However a simulation differ from a game because simulation uses a model that should mimic or reflect some aspects of reality, and game not necessarily. But on the other hand game and simulation may share the “play” element, which can probably help to build an engagement and motivation in a learning experience. And again play is something so fundamental for a human function, but far from an ordinary, real or authentic life (J. Huizinga) and for this reason in a way powerful.

Subjects I would be happy to explore further would be simulations and e-learning (methods and tools), usefulness of simulations in problem solving, complexity of simulations and cognitive overload (different for a novice and expert?), how much guidelines are needed in an effective simulation? These are very generic thoughts related to the topic, but I would be glad to restrict them to the context of meteorological training :)

I share links collected a while ago on the topic of simulation and game, maybe you find some of them useful (and working:)

http://www.delicious.com/majakuna/tag_bundle/Simulation

Cheers,

Maja

En respuesta a Maja Kuna

Re: Two new papers

de Heleen ter Pelkwijk -

Wow Maja, interesting thoughts!

At this moment i think I have a far more simple few view on what simulations are than you all have. In my simulator I have tried to create an area where a forecasters can (safely) exercise rare situations en working methodologies. And yes of course they are useful to check whether the scenario's work the way you previously thought. For my idea you should already have a good view what the relations are between parts of a system or process are before you start building or thinking of a simulator training otherwise you will get stuck somewhere during the simulator test.

I also have problems with the word "authentic". In my view it is usually  used as a kind of buzz word and then I do understand what is meant by it (usually be original) but now I decided to look it up in a dictionary: authenic = handwritten or created, not falsified, real, reliable, original.

I think you are right with your ideas about the formative evaluation, practice and exploration.

Maja, that you for this reaction. It gave me a lot to think about.

hartelijke groet,

Heleen

En respuesta a Maja Kuna

Re: Two new papers

de Patrick Parrish -

Thanks for extending these ideas into new places, Maja. A couple of those places in particular caught my interest. Sorry for straying from meteorology, but here goes...

"Human mind constructs 'small-scale models' of reality and use them to reason, to anticipate events and to provide explanations" : The American philospher John Dewey wrote extensively on logic and reasoning processes, and he argues that rather than following inductive and deductive reasoning, more often we use "dramatic rehearsal" to test things out in our minds, using them as the basis for mental "simulations," as you've pointed out. He shows how we do this for practical, technical, and even moral decisions. So, in a sense, we are all walking simulations. :) Some people have even theorize that this capability is the genetic advantage of consiousness, why we would bother as creatures to evolve such a silly capability that creates such grief and keeps us awake at night. It allows predators to anticipate the movements of their prey, and it allows social creatures, like us, to anticipate how our actions will be perceived and accepted by others. 

I think it was Satre that said something about imagination as being the defining power of consciousness, not some special capability in addition to it. Learning is another defining power because of imagination, I suspect. 

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I'm happy also that you sympathize with my question about the term "authentic." It certainly is useful and valid, but can be overused and over-argued as well. I remembered that Jean Paul Satre also had something to say about authenticity. In essence, he used the term to say that to live a valid life we need to be authentic to our true selves, and not to live a stereotype imposed by others or by society. This he called "living in bad faith." He also offered this interesting quotation: 

"If you seek authenticity for authenticity's sake you are no longer authentic."

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I really like your suggestion that simulation can be used for more than instruction, but also for formative evaluation, practice, and exploration--but then those are just other forms of learning. Many scientists would look at our discussion and think that we overlooked the most powerful use of simluation of all--scientific research (another form of learning).

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Simulations do seem ripe for generating very high levels of cognitive overload, which is why I believe instructor feedback and guidance, and progressive levels of difficulty can be critical. Reality often has high cognitive overload as well, which is why we have simluations, to prepare people for it. :) But games have high cognitive overload as well, especially video games, and they are the most popular form of entertainment in the world. Go figure. 

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I'll end with another quote I found when browsing for some confirmation of the things I mentioned:

"We are what we pretend to be, so we must be careful about what we pretend to be." - Kurt Vonnegut, Jr.    

Patrick

En respuesta a Patrick Parrish

Re: Two new papers

de Maja Kuna -

Thank you for your response, interestingly digressing from the subject of meteorology. I appreciate this discussion, which definitely s(t)imulates :) my thinking, so I will follow your thread. When you talked about imagination, I recalled a beautiful phrase by Einstein:

“Imagination is more important than knowledge. Knowledge is limited, imagination embraces the world”.

How many times have we heard a teacher saying, “imagine that…” before we “knew that”.

One more thought on simulation as a symbolic representation. If we refuse to use simulation because of its weakness in representing reality, maybe we should not use maps as well? Isn't a map a kind of symbolic representation of a territory?

Interesting that you mention Sartre’s mauvaise foi (how they would say in Geneva?:), stereotypes and way of behaviour imposed by society here. It is good to recognize that our actions are automated or forced by customs or rules. For example such a trivial thing like shaking hands when meeting a person. But would we feel more true to ourselves when behaving differently, doing something alternative to it? Erich Fromm in his work “Escape from Freedom” expands Sartre’s theory saying that it is not enough to be “free from” but also “free to”. “Freedom from” would be like sartrean freedom, like the one you mentioned, like an escape from an imposed function in a movie “Truman show” (btw, almost perfect live simulation). “Freedom to” would be something positive and creative, found to replace for example restricted rules of society. However human beings escaping from one restriction move to another, refuse to be 'authentic', a free entity, because they need a security and order. Would people know how to react without following certain rules and procedure? So in a way human nature has an element of conformity, says Fromm. Fortunately? Unfortunately? How much would we like a pilot to be true self when performing an emergency landing? Perhaps we feel more “secure” knowing that he has a checklist. :) The author has something interesting to say about authenticity too.

You talked about stereotypes, we mentioned symbols (simulation as a symbolic representation, symbolic simulations by Gredler). That leads me to a digression that stereotypes have common elements with symbols, or better signs, like their function of making sense of the world, simplifying (or oversimplifying), reducing “cognitive overload of reality”. We need some common language to communicate meaning and express the reality. But how do we know that a flashing red light in a game or simulation signify danger? How do we know that green colour on the map is a forest? Is the meaning the same for everybody?

"Simulation can be used for more than instruction, but also for formative evaluation, practice, and exploration--but then those are just other forms of learning."

You pointed out  “Blade Runner” in one of your posts. Three different forms of narration: book, movie and a game (even if some might argue that game is not narrative, see Frasca or Eskelinen). Is there any variation in experiences when a person is exposed to those 3 forms (except different endings)? Form seems to matter in context of experience and learning. Like using “How to” simulation would be more appropriate for practice and “About” simulations for exploration?

Maja

En respuesta a Maja Kuna

Re: Two new papers

de Patrick Parrish -

Thanks for extending the non-meteorology aspect of our conference. (For those less interested in these potential digressions, the stuff on applications to meterorology follow the dashed line below)

(Did you know that The Truman Show and The Matrix were release within months of one another in the US? Is that a coincidence, or the zeitgeist at work?)

We should discuss more the semiological applications to simulation, and instructional design in general, in another venue (several coffees at the next Eumetcal?) How do we use synechdoche to enhance fidelity/verisimilitude for learners? Semiology has other contributions to ID, like in interface design. Would you believe that some don't distinguish indexical from symbolic signs? :)

Mauvaise foi has implications to the root of ID as well. A fundamental principle of ID since the 1960's has been Alignment of Leaning Objectives with Instruction and Assessment. It is a very common bad faith that trainers and educators demonstrate when they fail to make the connection between these. In simulation, it takes greater significance--you better have students practice and make decisions about your intended learning objectives. In real life, you are right. "Bad faith" as a fundamental guideline becomes just as fruitless as stereotype. We need both order and the freedom to violate it. Humans are not purists, and life is too messy for the pure of mind to survive long.

Narrative is an important topic for instruction, where it is often ignored. Experiences are narrative in nature, but I am not sure how fundamental are the differences between narrative forms. They all have beginnings, middles, and ends, even games. Even simlutations. I think that simulations are one of the most clearly narratively structured learning activities. All narratives are interactive, not just games and simulations, because they all generate dramatic questions in the reader/viewer that must then be answered. I think the differences between forms are less fundamental than the simularities.

-----------------------------------------------------

Sorry, only a few meteorogly-specific applications to talk about.

Making a weather forecast can certainly be seen as an unfolding narrative. And I think case studies, and simlations, too often ignore the human aspects of those narratives. Heleen, and Kathy-Ann as well, have told about about ways that simulations introduce the stress of human interactions and not just scientific decisions. That is key in my mind. Kudos to them.

I think we have both a a spectrum of fidelity (to use Tsvet's term) and a spectrum of operational/physical (how to/about) nature in simluations, as mentioned in another post. Fidelity we talked about. Passing out products on paper and discussing them lacks some physical fidelity, even it it has temporal or sequence fidelity, is at the low end of the fidelity spectrum, but still highly useful. A simulation system like Heleen's gets pretty close to fidelity.

Then we have simlulations that just help people understand the physical conceptual models at work (also a step in operations)(About), and those that help people with the rest of forecating procecures, like making a prognosis (How to).

I guess my advice to those deciding how and whether to use simulations is to use them, but don't get hung up on complete fidelity if that might cause you not to use simluation. Simplication is ok if it helps novice learners focus on a few things to learn at a time, of course, but also if it helps you get the workshop prepared on time and on budget. Check out Heleen's tools, and don't forget that just showing slides of products and asking students to think about them and make forecast decisions can also be built into a simulation of sorts with similar learning outcomes. Getting learners thinking and making decisions is the goal.

Pat

En respuesta a Patrick Parrish

Re: Two new papers

de Heleen ter Pelkwijk -

Ha Pat,

Thank you very much for your reaction.I agree with most of your comments but with the fact that weather forecasting is not a procedural process I am not quite sure.......Yes I agree simulations will never replicated the work environment because of all the other influences you mention which will influence the process, but........as soon as the decision is made what the forecast will be you will be back in the procedural world. There are many rules regarded the things that needed to be done and how the forecast has to be communicated his knowledge to the customers.

As you know I think that the simulator is extremely useful in this Meteorological environment. But I also think that before you start using a simulator for your training you should think what you want to reach with it....reverting on that great article "the three essential elements" you added to this discussion...."good simulations also work because practice makes people better at what they do" (page 82) and "if there is no need to transfer a skill to real life, the use of simulator elements might be over-kill" (page 84).....

For general forecasts I don't have the illusion that I have to teach my experience forecasters how to make a good forecast, but for novice forecaster it may be very useful to gain experiences with the day to day forecasts before they start working in forecasting office. BUT for rare situations the story may be completely different....without simulators there is in my eyes no possibility to gain experience with the weather (sometimes in combination with other factors like nucleair or chemical accidents) nor the procedures which need to be followed in those kind of situations. And for the forecaster and their company these are the situations that really matter. You can't fail in these type of situations! That is why I hope "the nugget there is that when you learn something, you are taking in everything --the learning method plus the entire environment. If you go into that context again, it allows you to search memory more effective" (page 84) really works.

From my experience with simulators I have see that some of my forecasters never went through the whole weather alarm procedures here at KNMI but for them was an eye opener when they did and they got acquainted with them. Next to that we had the opportunity to adjust both the procedures and their way of working before they had to do it in real......but later more on these experiences.

Hartelijke groet,

Heleen

En respuesta a Heleen ter Pelkwijk

Re: Two new papers

de Patrick Parrish -

Hi Heleen,

You are right, and I should have been more clear in saying the while weather forecasting includes many procedural tasks, I don't feel that these are its defining characteristics. It is more centered on analytic and problem solving tasks. For this reason, it is harder to simulate without instructor guidance, in my mind. Not useless, but probably not as effective. (As I say this, I hope someone proves the statement wrong by inventing a good simulation that has good built in guidance for providing assessement and feedback on the higher order skills.)

I suspect your use of simulations for weather alarm procedures is a shining example of the power of simulations in weather forecast training. For infrequently used skills, but situations with high impacts, simulations are perfect. (Like flight simulators) And the fact that also adjusted procedures after using the simulations is an example of Maja's suggestion of using simulations for formative evaluation.

I think simulation is so fascinating because it is an extreme example of instructional approaches. It tends to make you think about all the aspects of learning and training.

Pat 

En respuesta a Patrick Parrish

Re: Two new papers

de Izolda Marcinonienė -

Dear colleagues,

I really enjoy reading and taking part in your discussions in virtual way:)Sorry I am too "blank" in simulator but, on the other hand,  it is the reason why I am reading your messages.

To add, I wanna say there are (I am sure) much more people who also do the same as me-silent participants...

Best wishes and go ahead,

Izolda

En respuesta a Heleen ter Pelkwijk

Re: Two new papers

de Tsvetomir Ross-Lazarov -

Since we discussed “authenticity” in the posts, I wanted to share Alessi and Trollip’s suggestions.  They call it “fidelity” or “how closely a simulation imitates reality,” and consider it “an overarching issue that affects all aspects of a simulation, such as the underlying model, presentations, and interactions.”(p.233)

“An aircraft simulator with a sophisticated visual and motion system provides a high-fidelity simulation of flying.  A computer-based simulation, such as Microsofts Flight Simulation has much lower fidelity.  Fidelity affects both initial learning (the learner’s performance during the simulation) and transfer of learning (how well one applies new knowledge or skills to new situations).” (p.233)

After a very enjoyable discussion, they point out a simulation design dilemma: “Increasing fidelity, which theoretically should increase transfer, may inhibit initial learning, which in turn would inhibit transfer.  On the other hand, decreasing fidelity may increase initial learning, but what is learned may not transfer to the application situation if too dissimilar.” (p.234)

They offer this solution: “using a level of fidelity based on the learner’s current instructional level.  As a learner progresses, the appropriate level of fidelity may increase.  For a novice, initial learning is emphasized (with lower fidelity) and for an advanced learner, transfer is emphasized (with higher fidelity).  This can be accomplished by choosing point along the best learning line in fig 7.16 or, in consideration of economic and time limitations, along the most cost-effective lime.”(p.234-235)  They point out that Bruner, Reigeluth and others have proposed a similar idea.  In simulations, “this approach is called dynamic fidelity.”

They also point out that fidelity is not a single entity.  “In fact, simulation designers speak about fidelity of  the presentations and fidelity of the model and fidelity of many other components of a simulation.  A simulation may have realistic presentations but rather simple interactions.  Similarly, it may have a fixed level of fidelity for the underlying model but dynamically increasing fidelity of presentations and interactions.” (p.235)

The discussion is very informative and accessible, so if you have a few spare moments it will be worth your time.  My earlier post contains the full chapter.

Cheers,
Tsvet 

En respuesta a Tsvetomir Ross-Lazarov

Re: Two new papers

de Vesa Nietosvaara -

Hello , everyone.

First a short self-introduction: i work as a Training Officer at EUMETSAT, and part of my job is to learn more about using simulators in our upcoming training events. So I really welcome this CALMet Online topic . Thanks to all who contribute to discussion.

A question to Tsvet and all : you mention fidelity and use a flight simulator as an example. I have been wondering which type of simulator fidelity would be needed for forecaster training event. As a first thought one would tend to think that a fully functional meteorological workstation and forecasting room environment would be needed to really simulate the real conditions. But from your posting i understand that at least for a basic training for novices we could just as well use much quite simplified systems to focus on certain aspects of forecasting.

I think i understand the need for lower fidelity for initial training : it helps to concentrate on certain process , task or feature. The novice learner can then also be less stressed about knowing and memorising every button and tool. On the contrary , he can first learn the general process and physics and steps in forecasting.

I believe that a simulation having even a very low level of fidelity can be a powerful tool if it is capable to challenge the user to make decisions and see the consequences of his decisions.

En respuesta a Vesa Nietosvaara

Re: Two new papers

de Tsvetomir Ross-Lazarov -

Vesa,

I think you are correct.  A novice learner will benefit from a low fidelity simulation if it challenges the user to make the kinds of decisions they will face in reality.  As the learner's experience grows they will benefit from increased fidelity.

Alessi and Trollip offer the following ideas:" For a novice leaner, low fidelity does yeild learning, but some increase in fidelity might result in better learning.  For example, a student pilot would learn something from reading a text about flying an airplane, but might learn more from watching a film with narration.  The same person might learn less, however, from a high-fidelity experience, such as a mechanical simulator.  Putting the novice in a real airplane, the highest possible fidelity, may be so confusing and stressful as to result in no learning at all.  On the other hand, an experienced user initially learns more from higher fidelity, such as a mechanical simulator...  For the expert, such as an experienced pilot learning to fly a new plane, a high-fidelity simulator might be very effective, and the actual airplane even more effective." (p.234-235)

The experience level of the learner appears to be a significant factor in deciding what level of fidelity to use.  In a computer-based environment, the idea of dynamic fidelity seems very useful.

Game designers seem to have mastered the idea of dynamic fidelity well.  Most good games start the player with very simple tasks and a limited set of tools.  The user still makes the decisions that they will make later in the game, but at first, they deal with a small subset of basic tasks.

As the user's experience increases, the game challenges become more difficult and the user has more tools at their disposal.  The user may fail repeatedly until they make the correct decisions based on the challenges and their tools in the game.  If the user fails repeatedly, the game will offer feedback and suggestions. In the massively multyplayer online games, the challenges become so difficult that the user is forced to team up with other users in order to succeed.

Tsvet

En respuesta a Heleen ter Pelkwijk

Re: Two new papers

de Tsvetomir Ross-Lazarov -

Thank you all for contributing to this forum.  Your posts are very informative and thought-provoking.

A resource that I use in my study of simulations is a chapter from “Multimedia for Learning: Methods and Development” by Stephen Alessi and Stanley Trollip (3rd edition).  The chapter offers very comprehensive coverage of the instructional research in using simulations for learning and offers guidance on how to build a simulation.

As everyone has noted in their posts, simulations are a wonderfully complex, multifaceted instructional system.   I would like to share just a couple of the ideas from the simulations chapter that may be relevant to our discussion here. 

Alessi and Trollip divide simulations into two broad categories based on their main instructional objectives – simulations that “teach about something or to teach how to do something.”  Each group has two subcategories:

“About something simulations

            Physical

            Iterative

How to do something simulations

            Procedural

            Situational”

  • Physical simulations present an “object or phenomenon” and give the learner “the opportunity to learn about it.” (p.215)
  • Iterative simulations allow the learner to run the “simulation over and over, selecting values for various parameters at the beginning of each run, observing the phenomena occur without intervention, interpreting the results, and then running it all over again with parameter values.” (p.217)
  • Procedural simulations teach “a sequence of actions to accomplish some goal.”(p.221)
  • Situational simulations “deal with the behaviors and attitudes of people or organizations in different situations, rather than with skilled performance.”(p.225)

They are quick to point out that a drawback of categorizing simulations is the impression “that the categories are clearly distinct.  In truth, many simulations do not fall neatly into just one category but are a synthesis of more than one type.”(p.215)  Heleen and Pat pointed that out in their posts as well.

 

The chapter goes on to discuss advantages of simulations compared to reality and to other media, factors in simulations, the underlying model and components of simulations; instructional supports, learner actions and control of the simulation, system reactions and feedback, simulation design and development, and so on.

Thank you all.

Tsvet

En respuesta a Tsvetomir Ross-Lazarov

Re: Two new papers

de Maja Kuna -

Thanks for sharing this interesting resource Tsvet.

I have just realized that the main "how" and "about" classification you have mentioned in your post is very similar to the one by Gredler (p.523). Her classification consists of two categories: experiential simulations and symbolic simulations. The first one places participants inside a simulation and allows them to be a principal performer. The symbolic simulation instead permits learners to manipulate, observe, and learn about the object or phenomenon, but they are "not functional elements of the situation".

Maja

En respuesta a Tsvetomir Ross-Lazarov

Re: Two new papers

de Patrick Parrish -

I also like this distinction be About and How to simulations. For some examples of good About simulations in the field of meteorlogy, you can find COMETs module on SkewT Mastery (http://www.meted.ucar.edu/mesoprim/skewt/), which contains an interactive SkewT diagram whose inputs can be changed to study how outputs, like instability parameters, change in response. 

COMET also has many others, which might be nice to see collected or referenced all in one place. COMET has other things they variably refere to as "calculators" or "widgets", among other things, but in essence they are About simulators that are very simplified representations of atmospheric processes that help people learn by doing. They are also working on a series of "Dynamics Learning Objects" that will include many example of such things to help teach atmospheric dynamics. Maybe we can be pointed to some of the work in progress. 

The University of Wisconsin has been building simple interactive applets like this for teaching basic meteorology for many years. These can be found at http://profhorn.meteor.wisc.edu/wxwise/. 

Pat

En respuesta a Tsvetomir Ross-Lazarov

Re: Two new papers

de Ilboudo Goama -

Dear Tset,

Very interesting your development. I have some comments about the two categories of simulation you described above. 

The "Teach about something" seems to be apower tool to allow trainee to repeat the course as long as possible until he fixes all ideas. This can be helpfully for students who have problems of understanding theorytically. 

The "Teach how you can do something" looks more powerful as it is related to both capability and attitude development. It can be taken as similar to outcomes-training simulations with the end goal "At the end of the training, the learner shall be able to ....". In my company, we use the "how to do something" simulation to complete te Air Trafic Controler's training.

I also think that the "how you can do something" simulation can be used for assessing aeronautical meteorological forecasters. It can take the form "assess the show what you can do" by asking the learner to deal with the questions such as"What would you do" if you have the following weather conditions (all conditions are simulated).

Maybe should you think about simulation and competency development?

Ilboudo