Case study - Student selection for last year of Industrial Engineer at Politecnico

di Roma

MCDA Summer School 2010Ecole Centrale de Paris

July 9, 2010

Agenda

1. Context2. Aim3. Decision process4. Model description5. Main steps6. Conclusions

2Case study - Student selection

1. Context• The selection process is changing from

paper based to paper based + interview

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GradesCover letterCV

GradesCover letterCVInterview

2. Aim• Affect at most 50 good students to the

different groups while keeping these homogeneous

– Numbers– Gender– Culture– Personalities

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3. Decision process• Sorting and ranking step– Separate students into categories– ‘Accepted’, ‘Recommended’ and ‘Rejected’

• Assignment step– Use the obtained ranking and remaining

information (gender, PT & P preferences)

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4. Model description

• Alternatives– Students

• Decision makers– Two that act like one

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4. Model description• Criteria

– Gap year– 3rd year grades– 4th year grades– Motivation– Personality– Project– Jobs– Professional track– Path– Gender– Culture– Personalities

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Evaluate good candidates

Assign students to groups

In case of problems

4. Model description

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4. Model description• Methods

– Sorting & ranking step: FlowSort 1

• Weights

– Elicited from the results of 2009– Higher importance of 4th year compared to 3rd year– Lower importance of Motivation compared to other

marks– Global higher importance of the marks compared to

grades

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1. P. Nemery de Bellevaux and C. Lamboray (2008), FlowSort : a flow-based sorting method with limiting and central profiles. *TOP (*Official Journal of the Spanish Society of Statistics and Operations Research), Vol. 16-1, pp. 90-113.

3rd year 4th year Motivation Personality

Project Jobs

5% 15% 10% 22% 23% 27%

4. Model description• Importance of criteria (Decision tree 1)

10

1. Quinlan, J. R. (1993) C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers. Case study - Student selection

4. Model description• Parameters (FlowSort)

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Criterion 3rd yr 4th yr Motivation

Personality

Project Jobs

Weight 5% 15% 10% 22% 23% 27%

Indifference thresh

0 0 0 0 0 0

Preference thresh 12 7 3 3 3 3

Profile 1 30 30 5 5 5 5

Profile 2 24 27 3 3 3 3

Profile 3 21 25 2.5 2.5 2.5 2.5

Profile 4 18 18 1 1 1 1

4. Model description• Profiles based on 2009 results (FlowSort)

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4. Model description• Validation of the model on 2009 results

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5. Main steps• Sorting of the 2010 students (using

FlowSort)

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5. Main steps• Sorting of the 2010 students (using

FlowSort)

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38 st.

3 st.

9 st.

5. Main steps• Assignment procedure– Affectation of the selected students to groups– Determine the capacity of each path for

F/M

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14

f

f

NC

14

m

m

NC

),( mf CC

:

:

m

f

N

N Number of selected females

Number of selected males

Algorithm

(1) Start with student rank:1 (r=1)

(2) If he/she has made a choice;For the gender (M/F) of the student, check path’s

capacity• If there is capacity, assign the student to the path • Else go to the next choice

Else, put the student to the waiting list

(3) Let r = r+1. Continue with step 2.

If student is in waiting list: affectation to the path with minimum students

17Case study - Student selection

An Example - Affectation

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Path Female(Capacity:3)

Male(Capacity:8)

SCM 1, 7, 9 2, 5

SFM 3 6

IP 4

MID 8

If we have a student,Rank: 10 Female & Path: SCM

Wait until all assignments are finished

• Affectation to Paths for Students of 2010

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Path Female(Capacity:3)

Male(Capacity:8)

Total(Capacity:11

)

SCM 1, 14, 15 2, 5, 8, 10, 19, 20, 22, 25

11

SFM 3, 38 6, 13, 30, 32, 33, 36, 37, 40

10

IP 18, 26 4, 7, 11, 12, 17, 24, 27, 35

10

MID 16, 29, 39 23, 9, 21, 28, 31, 34, 41 10

5. Main steps

• Step 1. Sorting in 3 groups (Accepted, Recommended, Rejected)

• Step 2. Ranking for the first 2 groups to present to the DM

• Step 3. Application of the assignment procedure

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6. Conclusions

6. Conclusions

• Homogeneity

Number of students in each path, gender √ Cultures, variety of personalities X

• Number of selected students

Maximum of 50 from the best categories

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6. Conclusions

• A student is rejected if– He/she cannot satisfy the minimum requirements– He/she is ranked below 50

• A student cannot enter his/her preferred path if

– The capacity is full with higher ranked students

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Thank you for your attention

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Appendices• PROMETHEE II Ranking (for the 2009

results)

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Appendices• Tree rules (for the 2009 results)

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Appendices• Decision tree (using results from our

model)

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Appendices• Tree rules (using results from our model)

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Appendices

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An example - Affectation

If we have a student,Rank: 9 Female & Path: SCM

Path Female(Capacity:3)

Male(Capacity:8)

SCM 1, 7 2, 5

SFM 3 6

IP 4

MID 8