The LTSI measures learning transfer in terms of 16 factors. They range from ‘Learner Readiness’ to ‘Performance Coaching’. Each factor is made up of various questions. These factors were described in detail in Chapter Three.
The factors with the highest mean scores are Factors 2, 12 and 15. These factors relate to motivation, effort and self-efficacy as follows:
Factor 2: Motivation to Transfer (3.91).
Factor 12: Transfer Effort: Performance Expectations (3.87).
Factor 15: Performance Self-Efficacy (3.95).
Performance Self-Efficacy is a secondary influence that can support or inhibit transfer of learning while Motivation to Transfer and Transfer Effort: Performance Expectations are motivational factors that impact the success of learning transfer. The statistical results of the factors with the highest mean scores are presented in Table 4.7.
Table 4.7 Factors with the highest mean scores
Motivation to Transfer
Valid Missing
Q2 Personal productivity. 154 0 4.05 4.00 4 .744 1 5
Q3 I can't wait to try what I learned. 153 1 3.73 4.00 4 .763 1 5
Q4 Training helps me do my job better. 154 0 3.95 4.00 4 .680 2 5
Minimum Maximum Question number & description N
Mean Median Mode Std. Deviation
Transfer Effort: Performance Expectations
Valid Missing Q35 Performance improves when using
what I learned.
154 0 3.84 4.00 4 .628 2 5
Q36 Working harder at learning helps me do my job better.
154 0 3.88 4.00 4 .640 2 5
Q40 More training application helps me do my job better.
154 0 3.73 4.00 4 .639 2 5
Q47 Confident in ability to use new skills at work.
154 0 4.03 4.00 4 .594 1 5
Minimum Maximum Question number & description N
Performance Self Efficacy
Valid Missing
Q48 I don't doubt my ability. 154 0 4.01 4.00 4 .667 2 5
Q49 I can overcome obstacles. 154 0 4.00 4.00 4 .626 2 5
Q50 Confident to use what I learned. 154 0 3.84 4.00 4 .661 2 5
Minimum Maximum Question number & description N
Mean Median Mode Std. Deviation
These results reveal that there is agreement from the respondents that they are able to use the skills and knowledge obtained during the training when they return to the working environment. The highest mean is for Question 2 (4.05). The question asks respondents to rate the following statement: “Training will increase my personal productivity.”
The question with the second highest mean is Question 47 (4.03). The question asks respondents to rate the following statement: “I am confident in my ability to use new skills at work.” The question with the third highest mean is Question 48 (4.01). The question asks respondents to rate the following statement: “I never doubt my ability to use newly learned skills on the job.”
Although these three questions form part of different factors, these results are enabling as opposed to hindering factors. A strong motivation for the transfer of learning and skills acquired during the training is evident (Question 2). The respondents are confident in their abilities to apply these skills (Question 47). This positive motivation and confidence is evident in the strong agreement of their ability to put their learning into practice in the working environment (Question 48).
Hence the findings of this study reveal that the three factors of motivation, effort and self-efficacy are the strongest enablers of learning transfer within this research population. There is a strong motivation and belief within this group of respondents that they will be able to use and transfer their learning on returning to the workplace after training. Furthermore, respondents indicated that, as a result of their ability to transfer their learning, they will experience positive performance outcomes.
The factors with the lowest mean are Factors 5, 8, and 14. These factors relate to:
Factor 5: Personal Capacity to Transfer (2.66).
Factor 8: Supervisor Sanctions (2.02).
Factor 14: Resistance to Change (2.19).
Personal Capacity to Transfer relates to the ability of respondents to utilise individual will power to apply new knowledge and skills acquired in the training intervention. Supervisor Sanctions and Resistance to Change are external environmental factors that can be managed extrinsically to ensure successful transfer of learning.
The lowest mean is for Question 25 (1.92). The question asks respondents to rate the following statement: “My line manager thinks I am being less effective when I use the techniques taught in this training.” The question with the second lowest mean is Question 24 (2.06). The question asks respondents to rate the following statement: “My line manager will oppose the use of techniques I learned in this training.” The question with the third lowest mean is Question 23 (2.09). The question asks respondents to rate the following statement: “My line manager will object if I try to use this training on the job.”
These three questions relate to the same factor (Supervisor Sanctions). These questions are asked in the negative and thus are not barriers to transfer of learning. The interpretation is that respondents perceive that their supervisors will not object to the respondents using their newly acquired knowledge and skills and do not think they are less effective when they apply these skills in the workplace. It reveals that supervisors do not prevent the respondents from applying their new knowledge and skills when they return to work after training has taken place.
The questions of Factors 5, 8 and 14 are all posed in the negative and as such are not barriers to transfer of learning. The low mean score indicates that a problem is not evident with this group of respondents. The statistical results of factors with the lowest mean scores are presented in Table 4.8.
Table 4.8 Factors with the lowest mean scores
Personal Capacity to Transfer
Valid Missing
Q10 No time to try and use training. 151 3 2.43 2.00 2 .883 1 5
Q11 Using training will take too much energy away from my work.
151 3 2.46 2.00 2 .877 1 5
Q14 Too much happening at work to try and use training.
154 0 3.08 3.00 3 1.003 1 5
Minimum Maximum Question number & description N
Mean Median Mode Std. Deviation
Supervisor Sanctions
Valid Missing Q23 Manager meets with me to discuss
training application.
154 0 2.09 2.00 2 .873 1 5
Q24 Manager will oppose using techniques learned in training.
154 0 2.06 2.00 2 .818 1 4
Q25 Manager thinks I am less effective using techniques taught in training.
154 0 1.92 2.00 2 .775 1 4
Minimum Maximum Question number & description N
Mean Median Mode Std. Deviation
Resistance to Change
Valid Missing Q42 Peers negatively critique others when
using tecniques learned in training.
153 1 2.18 2.00 2 .820 1 4
Q43 Not willing to put in effort to change way things are done.
154 0 2.19 2.00 2 .849 1 5
Q44 Reluctant to try new ways of doing things.
154 0 2.20 2.00 2 .896 1 5
Minimum Maximum Question number & description N
Mean Median Mode Std. Deviation
A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values. The questions with the highest standard deviation were Questions 13, 14 and 21. The questions ask respondents to rate the following statements:
Question 13: “My workload allows me time to try the new things I have learned.”
Question 14: “There is too much happening at work right now for me to try to use this training.”
Question 21: “My line manager meets with me regularly to work on problems I may be having in trying to use my training.”
The standard deviation of the factors in this study reveals that the factors with the highest standard deviation scores are factors 7, 5 and 4. These factors relate to:
Factor 7: Supervisor Support (.928).
Factor 5: Personal Capacity to Transfer (.921).
Factor 4: Negative Personal Outcomes (.879).
With factor 7, there is no consistent agreement on the respondents receiving support from their supervisors. Factors 4 and 5 are stated negatively and do not pose a problem to learning transfer. With the high standard deviation of these questions it appears that they might have been misinterpreted or that the respondents do not strongly agree with the statements.
These results are further supported by the findings of the qualitative responses received for Questions 52 and 53. Respondents indicated that time was a major factor that prevented them from applying their new learning when returning to the workplace after training.
It was indicated that there is too much happening in the working environment, preventing the respondents from applying their skills and knowledge. This high deviation shows that agreement on the question is not strong. The statistical results for factors 7, 5 and 4 and their standard deviation scores are shown in Table 4.9.
Table 4.9 Factors with the highest standard deviation scores
Supervisor Sanctions
Question number and description Mean Std. Deviation N Q35: Performance improves when using what I learned. 3.84 .628 154 Q36: Working harder at learning helps me do my job better. 3.88 .640 154 Q40: More training application helps me do my job better. 3.73 .639 154 Q47: Confident in ability to use new skills at work. 4.03 .594 154
Personal Capacity to Transfer
Question number and description Mean Std. Deviation N Q10: No time to use training. 2.42 .881 148 Q11: Using training takes too much energy
from my work.
2.45 .883 148
Q14: Too much happening to use training. 3.07 1.001 148
Negative Personal Outcomes
Question number and description Mean Std. Deviation N Q12: Penalised for not using training. 2.42 .871 153 Q15: Criticised if training not used. 2.84 .877 153 Q16: Cautioned if training not used. 3.05 .876 153
The factors with the lowest standard deviation scores are factors 12, 15 and 10. These factors relate to:
Factor 12: Transfer Effort: Performance Expectations (.625).
Factor 15: Performance Self-Efficacy (.651).
Factor 10: Transfer Design (.726).
With the low standard deviation scores, respondents agreed and felt strongly about the questions and what they aim to assess. These questions relate to the belief that if learning is applied, positive performance expectations will be achieved; in addition, the respondents have the confidence to use their knowledge and skills once they return to the workplace. A strong agreement in their abilities is thus a strong indicator of learning transfer with this group of respondents.
The statistical results for factors 12, 15 and 10 and their standard deviation scores are shown in Table 4.10.
Table 4.10 Factors with the lowest standard deviation scores
Transfer Effort: Performance Expectations
Question number and description Mean Std. Deviation N Q35: Performance improves when using what I learned. 3.84 .628 154 Q36: Working harder at learning helps me do my job better. 3.88 .640 154 Q40: More training application helps me do my job better. 3.73 .639 154 Q47: Confident in ability to use new skills at work. 4.03 .594 154
Performance Self-Efficacy
Question number and description Mean Std. Deviation N
Q48: I don't doubt my ability. 4.01 .667 154
Q49: I can overcome obstacles. 4.00 .626 154 Q50: Confident to use what I learned. 3.84 .661 154
Transfer Design
Question number and description Mean Std. Deviation N Q30: Trainers understand how I will use learning. 3.48 .815 151 Q31: Trainer examples shows how I can use learning. 3.58 .715 151 Q32: Way in which trainer taught made me confident. 3.66 .654 151
Chronbach’s Alpha relates to the internal consistency of factors. The values for all the factors are above .700 so they cannot be excluded. The three factors with the highest Chronbach’s Alpha scores are:
Positive Personal Outcomes;
Performance Self-efficacy; and
Supervisor Support
Table 4.11 summarises the results of the three factors with the highest Chronbach’s Alpha scores in terms of the measure of reliability.
Table 4.11 The three factors with the highest Chronbach’s Alpha scores
Positive Personal Outcomes
Performance Self-Efficacy
Supervisor Support
The three factors with the lowest Chronbach’s Alpha scores are:
Negative Personal Outcomes;
Resistance to Change; and
Personal Capacity to Transfer.
Table 4.12 summarises the results of the three factors with the lowest Chronbach’s Alpha scores in terms of the Chronbach’s Alpha measure of reliability.
Table 4.12 The three factors with the lowest Chronbach’s Alpha scores
Negative Personal Outcomes
Resistance to Change
The Component Matrix scores for each factor were all shown to be positive (above 0.6) and hence there is no need to reverse-score them. The factors with the highest scores are factors 3, 15 and 7. These factors relate to:
Positive Personal Outcomes(.891).
Performance Self-efficacy (.885).
Supervisor Support (.882).
Principal Component Analysis was used as the extraction method. Table 4.13 summarises the results of the three factors with the highest Component Matrix scores.
Table 4.13 Factors with highest Component Matrix value
Positive Personal Outcomes
Component 1
Q5: Using training gets me higher performance ratings. .842 Q6: Likely to be rewarded if I use training. .923 Q7: Recognition if I use training. .909
Component Matrixa
Question number and description
Extraction Method: Principal Component Analysis.
Performance Self-Efficacy
Component 1
Q48: I don't doubt my ability. .897 Q49: I can overcome obstacles. .886 Q50: Confident to use what I learned. .872
Question number and description
Extraction Method: Principal Component Analysis.
Supervisor Support
Component 1
Q21: Regular meetings with line manager. .922 Q22: Line manager discusses ways to apply training. .912 Q26: Line manager sets goals for me. .811
Component Matrixa
Question number and description
Extraction Method: Principal Component Analysis.
The factors with the lowest scores are factors 13, 11 and 12. These factors relates to:
Performance – Outcome Expectations (.756).
Opportunity to Use (.775).
Transfer Effort – Performance Expectations (.788).
Principal Component Analysis was used as the extraction method. Table 4.14 summarises the results of the three factors with the lowest Component Matrix scores.
Table 4.14 Factors with the lowest Component Matrix value
Performance – Outcome Expectations
Component 1
Q37: People rewarded deserve it. .791
Q38: Good things happen. .848
Q39: Training increases productivity. .582 Q41: Ideal job to be rewarded when doing good. .804
Question number and description
Opportunity to use
Component 1
Q13: Workload allows trying new things. .710 Q17: Have time to change things. .766 Q33: Enough human resources available. .797 Q34: Adequate staffing levels. .829
Question number and description
Extraction Method: Principal Component Analysis.
Component Matrixa
Transfer Effort – Performance Expectations
Component 1
Q35: Performance improves when using what I learned. .864 Q36: Working harder at learning helps me do my job
better.
.841 Q40: More training application helps me do my job better. .838 Q47: Confident in ability to use new skills at work. .610
Component Matrixa
Extraction Method: Principal Component Analysis.
The LTSI is divided into two sections. Section 1 (Question 1 to 34) asks the respondents to answer the questions as they relate to the specific training programme they attended, and Section 2 (Question 35 to 51) asks the respondents to answer the questions as they relate to training in general in the organisation.
Communality is that part of a variable’s total variance that can be explained by the factors. Looking at the communalities for each construct, all were shown to be positive (above 0.3), and hence there is no need to reverse-score them. Principal Axis Factoring, with the goal of determining the cause of the correlation structure, was used as the extraction method.
The results for the communalities of Question 35 to 51 are listed in Table 4.16.
Table 4.16 Communality values for Question 35 to 51 of the LTSI
Factor Matrixa scores for each factor are significant (above 0.4) and there is no need to reverse-score them. The LTSI uses a Likert scale and Principal Axis Factoring was used as the extraction method.
The three factors with the highest Factor Matrixa scores are:
‘Positive Personal Outcomes’ (made up of Questions 5, 6 and 7) has an average score of .834.
‘Supervisor Support’ (made up of Questions 21, 22 and 26) has an average score of .821.
‘Performance Self-efficacy’ (made up of Questions 48, 49 and 50) has an average score of .821.
The results are listed in Table 4.17.
Table 4.17 The three factors with the highest Factor Matrixa values
Positive Personal Outcomes
Factor 1
Q6: Likely to be rewarded if I use training. .919 Q7: Recognition if I use training. .871 Q5: Using training gets me higher performance ratings. .711
Question number and description
Extraction Method: Principal Axis Factoring.
Factor Matrixa
Supervisor Support
Factor 1
Q21: Regular meetings with line manager. .922 Q22: Line manager discusses ways to apply training. .885 Q26: Line manager sets goals for me. .657 Extraction Method: Principal Axis Factoring.
Factor Matrixa
Performance Self-Efficacy
Factor 1
Q48: I don't doubt my ability. .854 Q49: I can overcome obstacles. .824 Q50: Confident to use what I learned. .786
Factor Matrixa
Extraction Method: Principal Axis Factoring.
The factor with the lowest Factor Matrixa value is ‘Performance - Outcome Expectations’ with an average value of .664.
The measure of sampling adequacy (MSA) test was used for factor analysis in this study. The MSA criterion indicates the degree to which the variables are related, and it thus helps in evaluating the interpretation of using a factor analysis. The value must be more than 0.6., with no items excluded.
All factors were shown to be significant, as the significance value (p) is less than 0.05. Table 4.18 shows the MSA value for each factor (factor 1 to 16) as well as their significance values.
Table 4.18 Kaiser-Meyer-Olkin MSA results for each factor
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6
Factor 7 Factor 8 Factor 9 Factor 10 Factor 11 Factor 12 Factor 13 Factor 14 Factor 15 Factor 16
An Eigen value indicates the extent to which the total variance of all variables is covered by the factor. It is conducted on the factor analysis on the correlation matrix and the variables are standardised. It suggests that each variable has a variance of one, and that the total variance is equal to the number of variables used in the analysis. The Principal Axis Factoring method was used to extract the Eigen value results. After rotation, all the values were bigger than one and the cumulative percentage was above 50%. The results of the Eigen values for Question 1 to 34 are displayed in Table 4.19.
The Principal Axis Factoring method was used to extract the Eigen value results. After rotation, all the values were bigger than one and the cumulative percentage was above 50%. The results of the Eigen values for Question 35 to 51 are displayed in Table 4.20.
Table 4.20 Eigen values for Question 35 to 51 of the LTSI
A further investigation of the data revealed nine possible factors. The extraction of these factors is supported. The only factor that could possibly be renamed based on the data is Factor 1, as it is made up of questions from three different factors (‘Perceived Content Validity’, ‘Transfer Design’ and ‘Opportunity to Use’). The names of the factors are as follows:
Factor 1: Instructional Design Considerations.
Factor 2: Supervisor Support (as used by the international LTSI
instrument).
Factor 3: Supervisor Sanctions (as used by the international LTSI
instrument).
Factor 5: Peer Support (as used by the international LTSI instrument).
Factor 6: Learner Readiness (as used by the international LTSI
instrument).
Factor 7: Motivation to Transfer (as used by the international LTSI
instrument).
Factor 8: Positive Personal Outcomes (as used by the international LTSI
instrument).
Factor 9: Negative Personal Outcomes (as used by the international LTSI
instrument).