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An extensive research for information about computer simulations has proved to be an impressive way of students' learning. The three learning outcomes that can be listed are: conceptual change, skill development and content area knowledge.
Conceptual change- this outcome is the most exciting curriculum of computer simulations of the generation of abstract change. Students of this today's generation very often hold on to concrete misconceptions - they may be scientific, historical, mathematical or grammatical. Computer simulations thus, has been able to help out students to confront and correct these misconceptions, which usually has ways of learning concepts. For example, Hewson & Zietsman in 1986 found out the effect of this simulation on this generation students' about the relationship between speed and distance, which are fundamentals of physics. The main focus of this investigation was to change in the conception, even though we can notice the mathematical base of the study, Potter and Jiang in 1994). All the three studies that we see by Zietsman & Hewson in 1986,Jiang & Potter in 1994 and Kangassalo, 1994 all of these supported the computer-simulations to assist to accomplish necessary conceptual change. Where as in 1997 Stratford discussed further evidence of this kind. Brna in 1987, Gorsky and Finegold in 1992 reviewed models which were computer-oriented and researched in precollege science class in Stratford, in 1997.
Skill development -
In the computer simulation literature a more widely investigated outcome is measured for the skill development .11 out of 12 studies confirmed that computer simulations can be used for skill development. Most of them involved scenarios of scientific or mathematical background, for example, a simulation of spinner and dice probability experiment or simulation of chemical molecules , but very few of them used the topic related to the areas of history (a digital text which simulates all the historical events and permit's students to produce more influencing decisions) and creativity (which is based particularly on Lego block building). Willing, 1988 stated skills which were most likely to be improved are reading, problem solving stated by Jiang and Potter in 1994; then Rivers and Vockell in 1987 came up with science process skills like for e.g. measurement and data interpretation. Next was Askar, Ozkan ,& Geban in 1992;, Lomask, Lazarowitz, & Huppert in 2002 said 3D visualization, Barnea & Doriin in 1999 said mineral identification where as Kelly, in 1997-98 said abstract thinking , White & Berlin supported creativity, Michael in 2001 found out algebra skills.
B - The IT Background of the Issue
In the beginning, the final result from simulation was generally presented in a matrix or a tabular form, stating how exactly the data reacts to various and many changes in the simulation parameters. The matrix format was commonly used, and the traditional use of this concept of models of mathematics is related to each other. Most of the Psychologists have stated and proved that our brain can swiftly make out trends by looking at a moving pictures of graphs or moving-images, created from the data, as displayed by the computer-generated-imagery (CGI). Observers might be able to predict events faster than scanning tables of rain-cloud even though they couldn't consistently spout math formulas , or read out numbers, observing the weather chart ,and noticing the rain was heading their way. Such intense graphical displays transcends the numbers and formulas ,this may led to results that do not include coordinate grid or timestamps which are eliminated, being way apart from numeric data displays. Modern Weather forecasting models use moving snow/rain clouds against the traditional use of a map which used numeric coordinates and timestamps of events .
Prediction of how a tumor is cured in a medical treatment, by presenting the spinning view of visible human heads in the time span, as the tumor changes , can be similarly done using CGI computer simulations of CAT scans.
Applications of CGI simulations for graphical displays of large amounts of data are in development phase , as changes occur during a simulation run.
Classification of Computer models :
Discrete or Continuous
Stochastic or deterministic - have a look at the External links listed below for more examples of stochastic vs. deterministic simulations
Distributed or Local .
Dynamic simulations model changes in a system according to change in (usually changing) input signals.
use of numerous number generators to model chance or may be random events for Stochastic models
A discrete event simulation (DES) manages events are in time. Most of such logic-test computer simulations are of fault-tree and are of this type. Such simulation, a queue of events in maintained and sorted so that they occur in stimulated time. The simulator mostly reads only the queue and triggers new events as every event is managed. Real time simulation is not so important . Accessing the data that is produced by the simulation is more important, to discover, the event's sequence or logical defects in the design.
Numerical solution for differential-algebraic equations are performed by a continuous dynamic simulation. All the equations are solved by the simulation program , and use the numbers to changes that state and output of the simulation. Applications developed are chemical process modeling, electrical circuits simulation , , flight simulators, construction, simulation games and management simulation games. Initially analog computers were used to implement simulators. Differential equations were represented directly by numerous varieties of electrical components. In late 1980s, conventional digital computers which acted as an analog computer were used to run most of the analog simulations.
An agent-based simulation is a special type of discrete simulation which avoided relying on model with an underlying equation, instead represented formally. In an agent-based simulation, the individual entities are represented directly by internal state or a set of behaviors or rules which decides step by step up gradation.
Internet is used for Distributed models to run on a network . Simulations spread across multiple host computers are referred as "distributed simulations". Standards for distributed simulation are , Distributed Interactive Simulation (DIS), Test and Training Enabling Architecture (TENA), High Level Architecture (HLA) and analog computers.
C - Impact of the Issue
Researches in 1987 by Bourque and Carlson; Sherwood, Kinzerand Loofbourrow in 1989 report an lesser outcome comparative to the traditional methods of learning. But both the researches were failed and didn't include a pretest, due to which it was even more difficult to understand posttest scores. Now a days due to more of experience students in simulation groups have achieved bigger and more even scoring low in the posttest because eventually they began with less knowledge. In 1997 Carlson & Bourque designed a experiment in such a way that they have confused the computer simulation with other various experimental variables. Students who worked the computer took interest in such activities which were unfortunately not similar to those with students working with computer simulations and were very much experienced. Only particular students with the hands-on groups were occupied in post-lab problem solving exercise and other tutorials. Experimental errors are very problem giving for several of the 11 studies which indeed supported the benefits of using the computer simulations. In 1985/86 neither Hasselbring and Sherwood, Woodward et al nor Choi or Gennaro in 1987, integrated pretest. Like as said above in 1997 Carlson & Bourque, Dori & Barnea in 1999 and Andre & Akpan in 2000 established confusing experimental variables by connecting it to the computer simulation group with supplementary learning activities. While adding up, four studies of Dori & Barnea, in 1999; Huppert et al.; Woodward et al. Atkins & Yildiz ,in 1996 didn't provide a clear suggestion that they randomized assignment, and plus didn't contain a control group. Additional study is essential to repeat these result; the quality of such evidence is not very strong in sustaining the use of traditional approaches. There is always a reasonably support for the performance of using simulations as a complement to traditional approaches for the teaching satisfied knowledge. However, similar question arises when talking about the skill development literature which needs to be addressed in upcoming research. Where as it is not essential to have computers in the classroom when explaining reading ability. Thus,trying and putting large amounts of money to the buy the hardware's, software's or teacher training could overshadow many other essential educational expenditures such as for example music programs or vocational education or even new textbooks and the arts equipments. But this does not off course mean that computers don't have a place in the classroom. But yes it does shows you that computers may or may not have any effect on academic in getting the reading which some might even expect more, even though they are used by the well-trained instructors.
D - Solutions to Problems arising from the Issue
I think regarding this proble all the student should hav the basic knowledge of text before they are exposed Computer Simulation. The School should make a point to follow traditional teaching methods as well as computer simulation and should focus less on it. Proper Computer Configurations is must in order to avoid various errors. At present only these measures are available to prevent and stop the errors in Computer Simulated Teaching.
E - Selection and Use of Sources
NEWS ITEM - EXTRACT
A study found that people who used computer simulations and collecting data from viewing the moon to learn about moon phases understood it just well , but in some cases people using computer simulation understood it a bit better . Kathy Cabe Trundle, lead author of the study and associate professor of science education at Ohio State University said "The results suggest that computer simulations based studies may be a more effective way and less expensive and time-consuming way to teach some science concepts". "These results increase our confidence on computer simulation's effectiveness in the classroom". "But we need to analyze its utility in others areas of science." He conducted the study with Randy Bell, associate professor of science education at the University of Virginia. There have been numerous studies to examine computer use in the classroom, most of them only resulting in finding whether students find it easy and enjoy using them. Only a few studies have tested computer's efficiency for learning contents, but all have had mixed results. It was an improvement as it actually compared people using a computer simulation with those who had more direct observations. "The expectation were that the computer simulation would be as efficient as direct observation in teaching . "When analysis was done, the simulation were found to be just as effective in teaching two aspects of moon phases, and more effective in a third aspect. Study included 157 pre-service teachers-- master's degree students as participants who were in training to become childhood teachers. Studies have shown that the majority of people do not understand the cause of moon phases. This study aimed in finding how well these pre-service teachers understood moon phases before and after taking a 10-week science methods course .This course included a unit on moon phases. This class was more of an inquiry-based course rather than being a traditional one, which meant that students gather data themselves and then learn directly from viewing the moon or from the computer simulation. They then analyzed the data they gathered to identify patterns. One class learned about moon phases using only a computer simulation, one group only from observations of nature alone, and a third group from both a computer simulation and nature's observations . They provided a commercially available software that allows users to visualize the movement of the sun and the moon through time from any point on Earth. The researchers tested the participants' understanding before and after the class in three areas: knowledge of sequences of moon phases, the causes of moon phases, and the shapes of moon phases. Before the class, none of the pre-service teachers had a complete scientific knowledge of the moon phases. But after the class, teachers in all three groups -- computer simulation only, nature only and simulation and nature -- dramatically improved their scores. Up to 98 percent of the teachers showed they understood moon phases after the class was completed. Those who used only computer simulations did just as well as others in learning causes of moon phases and shapes of moon phases. But those who used the simulations were actually understanding the sequences of moon phases well