Level 2 Evaluation of Training. LBAT Model Case Study Workbook

IMS Analysis

Series Batch 1 Batch 2 Batch 3 Pre-Test 166 248 261 Post-Test 422 465 560

600

560

500

465 422

400 300 200

248

261

166

100 0

Batch 1

Batch 2

Batch 3

P

P

IBA-Karachi

Series Batch 1 Batch 2 Batch 3 Pre-Test 2.3 2.5 2.1 Post-Test 4.4 4.6 4.5 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0

Batch 1

Pre-Test Post-Test

Batch 1

Batch 2

Batch 3

Series

Batch 2

Batch 1

Pre-Existing Learning

29.87% 40.48% 29.65%

Net Learning Learning Lag

Definitions: Pre-Existing Learning

Pre-test Score

Net Learning

Post-test score minus pre-test score. This is the score attributable to the training.

Learning Lag

100 minus post-test score

Example: Pre-Existing Learning

28.87%

Net Learning Learning Lag

44.52-28.87=44.52% 100-73.39=26.61%

Note: The data for batch 2 & 3 are hypothetical and inserted as example only.

40.85% 28.79% 30.36%

Batch 3 35.71% 42.86% 21.43%

100.00% 90.00% 80.00%

29.65%

30.36%

21.43%

70.00% 60.00% 50.00%

28.79%

40.48%

42.86%

40.00% 30.00% 20.00% 10.00% 0.00%

29.65%

40.85%

29.87%

B a tch 1

30.36%

B a tch 2

21.43%

35.71%

B a tch 3

3%

6%

1%

h 3

Serial 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Name

Pre Test Marks

% Score in Pre Test

Ali Abdullah

5

36

Ali Shah

2

14

AnilaAzmat

5

36

Dr. Amjad Ali

4

29

Dr. Faisal Aftab

5

36

Dr. Faisal Nouroz

2

14

Dr. HooriaYounas

6

43

Dr. Imran Wazir

2

14

Dr. MahboobAlam

4

29

Dr. Mudassar Iqbal

5

36

Dr. Muhammad Qasim

5

36

Dr. SabahatAkram

7

50

Dr. Salman Ahmad

1

7

Dr. Sartaj

2

14

Dr. Tariq Habib

5

36

Dr. ZainabJehan

5

36

Fayyaz Ahmed Khan

3

21

Habib ur Rehman

3

21

Humaira Zulfiqar

5

36

Khalid MujtabaMughal

3

21

Mariam Mohsin

7

50

MoazamMaqsood

3

21

Muhammad Haseeb

6

43

Muhammad Waseem

4

29

Muhammad Zaheer

3

21

MunazzaNazir

2

14

Nighat Ahmad

3

21

Noor Muhammad

6

43

Prof Dr Allah Nawaz

5

36

Qamar Ahmed

4

29

RosemeenRiaz

4

29

SumeraKauser

6

43

Zafar Iqbal

6

43

100 90 80 70

100 90 80 70 60 50 40 30 20 10 0 1

2

3

4

5

6

Post Test Marks

% Score in Post Test

12

86

8

57

6

43

9

64

9

64

12

86

11

79

11

79

10

71

12

86

10

71

8

57

10

71

10

71

11

79

10

71

11

79

9

64

9

64

9

64

11

79

13

93

9

64

7

50

8

57

10

71

12

86

9

64

9

64

10

71

11

79

8

57

11

79

% Increase in Learning 50 43 7 36 29 71 36 64 43 50 36 7 64 57 43 36 57 43 29 43 29 71 21 21 36 57 64 21 29 43 50 14 36

2

3

4

5

6

7

8

9

10

11

12

13

14

15

% Pre-Existing Learning

16

17

18

19

% Net Learning

20

21

22

%Learning Lag

23

24

25

26

% Gap in Learning

Trainees 50 57 93 64 71 29 64 36 57 50 64 93 36 43 57 64 43 57 71 57 71 29 79 79 64 43 36 79 71 57 50 86 64

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

% Pre-Existing Learning 36 14 36 29 36 14 43 14 29 36 36 50 7 14 36 36 21 21 36 21 50 21 43 29 21 14 21 43 36 29 29 43 43

21

22

earning Lag

23

24

25

26

27

28

29

30

31

32

33

% Score in Post Test

%Learning Lag

% Net Learning 86 57 43 64 64 86 79 79 71 86 71 57 71 71 79 71 79 64 64 64 79 93 64 50 57 71 86 64 64 71 79 57 79

50 43 7 36 29 71 36 64 43 50 36 7 64 57 43 36 57 43 29 43 29 71 21 21 36 57 64 21 29 43 50 14 36

14 43 57 36 36 14 21 21 29 14 29 43 29 29 21 29 21 36 36 36 21 7 36 50 43 29 14 36 36 29 21 43 21

Key Learning Areas in Project Proposal Writing inTraining Series Results Framework Indicators Finanacial Proposal PreExisting Learning 24.00% 13.00% 35.00% Net Learning

56.00%

47.00%

50.00%

Learning Lag

20.00%

40.00%

15.00%

100.00% 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00%

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