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This module measures-simulates the way students learn and possibly forget by using principles of cognitive psychology concerning human memory + , =
Student Model
the student model takes into account:
How long it has been since the student has last seen a part of the theory
How many times s/he has repeated it
How well s/he has answered questions relating to it (& P$ E 2 Test Bed $To test the generality of our approach and its effectiveness within an educational application we have incorporated it in a knowledge based authoring tool. The authoring tool is called Ed-Game Author (Virvou et al. 2002) and can generate ITSs that operate as educational games in many domains2% ] N 3 #Cognitive model (Ebbinghaus, 1998)$ :
t: is the time in minutes counting from one minute before the end of the learning
b: the equivalent of the amount remembered from the first learning.
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Learning Process
Whenever a students encounters a new part of the theory, the date and time are stored in the system s database (TeachDate).
Whenever a student uses a part of the theory, the date and time of this action is also stored in the system s database (LastAccessDate)6p }:p } Retention Factor (RF)The Ebbinghaus model is generic. To personalize it we will use the Retention Factor.
The RF is a base percentage of the how much of the fact a student actually remembers
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Retention Percentageb is the result of Ebbinghaus power funtion if we set t=Now-TeachDate
X is the Retention Percentage(e7̙L
Custom Retention FactorTo customize the Retention Factor of a student we will introduce two new factors:
Memorize Ability Factor
Response Quality Factor,S0S0 Memorize Ability FactorBased on the student model we define the memorize ability factor, a constant number with the following values:
0 Very Weak Memory
1 Weak Memory
2 Moderate Memory
3 Strong Memory
4 Very Strong Memory4oZbZq_
Memorize Ability Factor (2)RThe new range for the RF is from 90 (very weak memory) to 100 (very strong memory)R Response Quality Factor>During the test, depending on the student s answer we define the Response quality factor, a constant number with the following values:
0 No memory of the fact
1 Incorrect response; the student was close to the answer
2 Correct response; the student hesitated
3 Perfect Response6 Response Quality Factor (2)FAt that point the RF is again modified as shown in the following tableF Response Quality Factor (3)fWhen a student gives an answer, the modification of his/her Retention Factor depends on his/her Memorise Ability factor
In the end of a virtual lesson , the final RF for each fact is calculated. If this result is above 70 then the student is assumed to have learnt the fact, else s/he needs to revise it.
42 | G 3 Conclusions We have described the part of the student modelling process of an ITS authoring tool that keeps track of the students memory of facts that are taught to him/her
For this reason we have adapted and incorporated principles of cognitive psychology into the system
In this way the system may know when each individual student may need to revise each part of the theory being taught@ c w t d Z T
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WingdingsArial 3SQUARESMicrosoft Equation 3.0XIndividualizing a cognitive model of students memory in Intelligent Tutoring Systems
IntroductionStudent Model Test Bed$Cognitive model (Ebbinghaus, 1998)Learning ProcessRetention Factor (RF)Retention PercentageCustom Retention FactorMemorize Ability FactorMemorize Ability Factor (2)Response Quality FactorResponse Quality Factor (2)Response Quality Factor (3)ConclusionsFonts UsedDesign TemplateEmbedded OLE Servers
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