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2nd Meeting of Young Researchers on MULTIPLE CRITERIA DECISION AIDING Iryna Yevseyeva Niilo Mäki Instituutti University of Jyväskylä, Finland

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Presentation on theme: "2nd Meeting of Young Researchers on MULTIPLE CRITERIA DECISION AIDING Iryna Yevseyeva Niilo Mäki Instituutti University of Jyväskylä, Finland"— Presentation transcript:

1 2nd Meeting of Young Researchers on MULTIPLE CRITERIA DECISION AIDING Iryna Yevseyeva Niilo Mäki Instituutti University of Jyväskylä, Finland iyevsev@cc.jyu.fi iyevsev@cc.jyu.fi Utilizing Verbal Decision Analysis for Computerized Estimation of Children’s Learning Abilities

2 Main topics of presentation Introduction to the problem in question Possible tools for solving problem  Expert system  Verbal decision analysis Examples of application Future research directions

3 Problem area development of the computerised tool for testing and estimation cognitive abilities of children through behaviour problem area is numerical calculations particularly simple one-digit addition

4 Example of test 2 + 3 = 5 2 + 3 = 5 The child solve 50 tasks 10 times The teacher  evaluate child’s knowledge  make “diagnose” and classify child to one of the group  propose future direction for development of the abilities

5 Features of the problem Unstructured problem Experience and skills of the unique experts is exploited Verbal estimations of the preferences

6 Possible Tools for solution Expert systems Verbal Decision Analysis Other MCDM methods Other AI techniques

7 Expert System + MCDM Expert system’s still contain expert’s personal experience, but MCDM technique utilized That allow form expert’s preferences in the structured model Combination of MCDM methods and ES overcome limitation of the both

8 MCDM definitions in context of learning environment Decision Maker: psychologist or special teacher; Alternatives: set of all possible “diagnoses” or conclusions teacher can make; Criteria : age, time, correctness, strategy, result > 10 or 10 or <10; Decision Rule: are based on the Decision Maker’s preferences.

9 VDA principles (1) Qualitative or verbal estimations DM creates the ordinal scale for every criteria Built pairwise comparison of alternatives differing in values not more than two criteria

10 VDA principles (2) The rule for the comparison: Alternative A is more preferable then alternative B if it has criteria levels that are not less preferable on all criteria and is more preferable on at least one Create joint ordinal scale on which all possible values upon all criteria are rank- ordered according to the DM’s preferences

11 VDA principles (3) Checking of inconsistency of information with transitivity and independence properties Learning procedures Explanation of the way of obtaining decision

12 PACOM and ZAPROS Methods PACOM (PAired COMpensation)  Small set of alternatives for selection  Selection of the best alternative ZAPROS (Closed procedure near references situations)  Large set of alternatives for selection  Rank-ordering of the best alternatives

13 Estimation of the learning abilities with ZAPROS method Selection of the set of most suitable “diagnoses” from the large set of possible ones Rank-ordering of “diagnoses” on the joint ordinal scale

14 Estimation of the learning abilities with PACOM method Selection of the most preferable or best “diagnosis” on the joint ordinal scale But from the small set of possible ones

15 Future direction of the work Analysis of MCDM methods for neuropsychological diagnostics Implementation of MCDM methods Comparative study of the applied MCDM methods EUROOPAN UNIONI


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