Environmental Factors Affecting Training Transfer Among the Instructors

This study explores the environmental factors that affect the transfer of training among technical education instructors in Nepal. In the exploration, a scale with 40 items was constructed by utilizing Delphi technique. Then, a survey was carried out on 251 instructors who completed instructional skills-related training. The result of Exploratory Factor Analysis (EFA) retained 26 items and showed six factors affecting the perceived transfer of training accounting for 58.8% of the total variance explained which are: (i) organizational transfer intervention, (ii) external monitoring and evaluation (M&E), (iii) local school governance, (iv) management support, (v) social support and, (vi) curriculum standard. Further using Confirmatory Factor Analysis (CFA), the study confirmed the model-fit of three constructs that affect training transfer: organizational transfer intervention, external M&E, and social support. The study concluded that the training transfer is affected by internal and external environmental factors, which are represented by two major driving forces of support and control.


Introduction
Training, a common intervention for filling the performance gap, is a planned intervention to systematically acquire knowledge, skills, and attitude (KSA) to improve employee performance (Salas et al., 2006). The role of training has been extensively documented in various spheres (Coultas et al., 2012;Ford et al., 2018). However, the meaningfulness of training can be observed only when the learning is transferred from training to the workplace. Therefore, the transfer of training has gained much research attention over time (Blume et al., 2010;Tonhäuser & Büker, 2016) due to the low level of training transfer and this issue has also remained pertinent among the teachers or instructors (McDonald, 2011). Baldwin and Ford (1988) explain the transfer of training as the generalization of learned behaviour and its maintenance on the job across time. Salas et al. (2006) further contribute to this elaborating transfer of training as the systematic gaining of KSA that collectively and consequently improves employee performance within the certain work environment. However, it is a complex process that often produces elusive results (Ford et al., 2018;Veillard, 2012), and it is a multiphasic process in which influential variables interact simultaneously rather than in a sequence (Park et al., 2016). Thus, several factors affect in the transfer process of learning from training back to the workplace at different phases. In this respect, the earlier work of Baldwin and Ford (1988) helps comprehend that three training inputs affect training outputs and, ultimately, conditions of transfer: trainee characteristics, training design, and work environment. These three input dimensions have been substantiated and referred to then after (Tonhäuser & Büker, 2016) in which work environment has remained in the central attention of numerous studies (Bhatti et al., 2013;Simosi, 2012). Expanding the contribution of Baldwin and Ford, Renta-Davids et al. (2016) explain individual characteristics, educational design, and work environment as the determinants of learning transfer in technical and vocational education and training (TVET). In this connection, this study aims to explore and confirm the environmental factors affecting training transfer in TVET instruction in Nepal. Before presenting the methods of the study, the literature on training transfer in global and Nepal's context has been presented.

Notion of Work Environmental Factors Affecting Training Transfer in Literature
Among the constructs affecting training transfer, the work environment falls under the organizational level (Tonhäuser & Büker, 2016), and it has been identified as a major factor influencing training transfer (Veillard, 2012). It influences training transfer which occurs externally beyond the training intervention (Burke & Hutchins, 2008) within which several factors foster or inhibit the transfer process, independently or in conjunction with other factors. Environment affecting learning draws the attention of several studies for it is multimodal and complex in nature (Billett & Choy, 2013). In this regard, Bates et al. (2012) confirm that supervisor support, supervisor sanction, peer support, performance coaching and resistance to change measure the work environment in their revised Learning Transfer System Inventory (LTSI). Other research also studied factors such as transfer climate, follow-ups (Grossman & Salas, 2011), commitment and organizational cultures and variability in job assignments (Tonhäuser & Büker, 2016). In a study by Lim and Morris (2006), the work environment was broadly categorized into social factors and structural or systemrelated factors. Furthermore, the literature has also reported environmental factors such as organizational learning culture (Martin, 2010), and risk-taking and qualityoriented culture (Kontoghiorges, 2004).
Literature review draws more research attention as there seem to be inconsistencies in the extant literature regarding the sub-categories which can be clustered thereunder. For instance, Rouiller and Goldstein's (1993) work classifies transfer climate into situational cues and consequences and includes supervisor support within it. Contradictorily, other researches have considered supervisor support different than transfer climate (Grossman & Salas, 2011;Nijman et al., 2006). Similarly, a personal capacity to transfer (Bates et al., 2012) lacks clarity on whether it falls under trainee characteristics or work environment. Capacity of instructors depends upon the curriculum that determines their workload, and in Nepali context, educational institutions function under the affiliation of universities or regulatory bodies which is Council for Technical Education and Vocational Training (CTEVT) (Ministry of Education [MoE], 2012). So the workload of a heavy curriculum is beyond the control of school management. Contradictions also prevail in the findings of work-environmental variables. For instance, Ghosh et al. (2015) exhibit a positive association of supervisor support with training transfer, while some exhibit a negative association (Facteau et al., 1995) and even no association at all (Chiaburu & Marinova, 2005). Therefore, these conflicting findings indicate a dire need for contextual research on TVET instructors.
In TVET instruction, the role of instructors is directly related to the labour market and are required to be adaptive to the labour market needs (Bhattarai, 2021). However, challenge prevails, affecting real learning, especially in developing countries where teacher training is not taken as a compulsory requirement and where there are numerous untrained TVET teachers lacking industrial experience (Euler, 2018). Consequently, trained TVET teachers with competence and motivation have become the key to better teaching/learning and meeting the objectives of education (Machado & Cury, 2009). Moreover, there is a greater significance of TVET graduates in a country such as Nepal since nearly half a million people enter the job market without marketable skills (Asian Development Bank, 2015). In such contexts, training for instructors and training transfer climate are considered instrumental for the overall quality in TVET.
Literature on the work environment affecting training transfer in TVET instruction in Nepal is yet limited and underexplored. From a policy perspective, training on teaching/instructional skills for TVET instructors has been ascertained in Nepal's national education policy, 2019 (Ministry of Education, Science and Technology [MoEST], 2019) and TVET policy, 2012(MoE, 2012. Yet these policies are unclear on ways to ensure the transfer of training or find out the factors that promote or inhibit transfer. Among a few studies on training transfer, Adhikari (2018) exhibits transfer level in general education, and Koirala et al. (2016) show trainee satisfaction of TVET instructors at the reaction level. However, these studies do not address the issues of environmental factors affecting training transfer among TVET instructors. With this consideration, this study was conducted with the research question: what environmental factors affect the training transfer among the instructors of technical education in Nepal? The subsequent sections include methods applied to answer the above research question, followed by results, discussion, conclusion and implications of the study.

Methods
Merely relying on the extant literature to conduct exploratory factor analysis (EFA) entails a greater risk on content validity since all the previously identified factors may not be replicable in TVET instruction in Nepal, and there might be other potential factors too, which may have remained in shadow due to insufficient empirical researches. In this regard, Delphi method was deemed appropriate by the authors and was used to explore such contextual knowledge. Delphi method is a group consensus-building method in which a researcher/research team carefully selects a panel of subject matter experts, collect their ideas, opinions, and judgements on certain issues or fields of research re-iteratively for the purpose of scrutinizing them for setting goals, affecting the occurrence of future events or exploring determinants of an event (Keeney et al., 2011). Further, it is a re-iterative process in which ideas are collected or confirmed from the Delphi experts maintaining anonymity among them to avoid biasness and possible dominance of one expert over another in each round and are refined using controlled feedback, by allowing them to adjust their responses as required, and again taken to other rounds with the use of simple statistical summary. This process continues until a reliable consensus is concluded (Powell, 2003). This study is therefore guided by five characteristics of Delphi: iteration, anonymity, controlled feedback, statistical aggregation, and judgemental inputs of experts in between the rounds of the Delphi implementation phase (Keeney et al., 2011;Rowe & Wright, 1999).
Delphi is deemed appropriate in the areas where previous research is limited and there is a need to identify and prioritize an area of a concern or to develop a concept, framework or model (Okoli & Pawlowski, 2004). Further, it has also been used to identify elements that would contribute to a model in a given context (Palo & Tähtinen, 2011). Delphi, however, is subject to judgemental inputs. In Delphi, the epistemological stance is often ignored (Keeney et al., 2011), and ambiguity prevails on the ideal number of panel of Delphi experts (Rowe & Wright, 1999). This study's analysis thus is based on the surveyed data after generating statements from Delphi.

Executing Delphi Method
Taking note of Beech's (1999) work, this study formulated three phases: preparation, implementation, and instrument construction. In phase one, which is a preparation phase, four steps were undertaken. The first step of phase one was issue comprehension, based on the researchers' professional experiences and literature review. The second step was the careful selection of panel of experts with substantial knowledge and experience to exhibit a deeper understanding of the issue which was one of the most crucial tasks in assuring quality of final results (Saizarbitoria, 2006). 14 Delphi experts were purposively selected based on their availability, interest, and heterogeneity (Powell, 2003). They were identified as (i) those experienced TVET instructors who had participated in at least one instructional skills-based training event and attempted to apply the learning back on their job or (ii) those trainers who had previously worked as instructor in technical schools of Nepal thereby ensuring more knowledge in all of them than most of the population (Keeney et al., 2011). The third step was the appointment of a facilitator holding sufficient knowledge of the given issue, which was carried out by the researchers maintaining neutrality. The fourth step was the preparation of interview guidelines.
The second phase was the implementation phase, which consisted of three rounds by which consensus was built in this study. In the first round, known as idea-generating stage (Reynolds et al., 2008), in-depth interviews for an average of an hour were carried out using the classical Delphi method with open-ended questions (Keeney et al., 2011). The experts were duly thanked for their time and contribution of ideas and inputs along with the information of the next round. Initial themes were generated at the end of the first round, such as support from management, curriculum standard, resource availability, peer influence, organizational culture and such. Quantitative statements were then generated from the qualitative data obtained from the interviews. Duplicate items and those giving similar meanings were removed, and only meaningful statements were retained. Items were clustered into two broad themes: (i) internal work environment with 56 items and (ii) external environment with 51 items summing up to 107 items. For the second round, these items were then developed into a questionnaire using 5-point Likert Scale ranging from 'Strongly Disagree' to 'Strongly Agree' (Keeney et al., 2011), also allowing the experts a space to make comments subjectively on any statement as well as on the whole process. Sample item includes 'Lengthy process of decision making on purchasing resources affects the transfer of training'. The questionnaire was distributed online with a verbal notification marking the advent of the round two.
Data collected in round two ensured reliability in both themes: internal work environment (α = 0.78) and external environment (α = 0.93). Statistical aggregation was done using Median values as the favoured statistics (Keeney et al., 2011). Some experts were approached again at the end of this round whose responses were not consistent with those of the majority following the principle of controlled feedback. They were allowed to review their previous responses and have room for subjective explanations, to which a few experts revised their scores. Sample item includes 'External regulatory bodies other than CTEVT (Example: Nursing Council) should also come for inspection on the transfer of training.' In round three, only those items with below 70% consent were sent back to them which became final round in this study. Yet only 13 experts completed this final round dropping the response rate to 92.86%. A few items which scored below 70% in group consensus were discarded, considering their subjective comments. For instance, the statement 'The students' habit of copying the notes from the instructors in the class encourages the instructors to teach conventionally and not apply the training' was discarded. Round three concluded with 38 items under the internal work environment and 35 items under the external environment.
Phase three was the instrument construction phase, and the items were further refined and reduced to 40 items without compromising the key contents. In this, internal work environment consisted of 22 items (α = 0.89) and external environment consisted of 18 items (α = 0.83). A 6-point Likert Scale was used ranging from 'Strongly Disagree' to 'Strongly Agree' with no option of neutrality (DeVellis, 2017). Thus, an instrument was developed that is contextual to training transfer among the instructors of technical education in Nepal. The statements used in round two and three were in English as they were preferred by the Delphi experts. Thus the instrument developed was originally in the English language which was translated into the Nepali language for survey, and later back-translated into English to assure that the items still held similar meaning to what was originally developed. With this, the study reached to the next level of scale construction.

Research Instrument Development Process Using EFA
To address the literature-informed issues of Delphi method, survey method was further carried out using the instrument generated from Delphi method. Survey was conducted on 251 instructors or similar position holders out of a total of 719 instructors who had previously taken training related to instructional skills including Training of Trainers (ToT) from Training Institute for Technical Instruction (TITI) under CTEVT from October 2018 to December 2019, and were engaged in teaching up to Bachelor's level students in different technical schools and colleges across Nepal at the time of survey. Such trainings are mandatory for the instructors to teach in the classroom since they are designed to enhance their instructional and pedagogical skills. Further, TITI was selected as the training provider since the TVET policy of Nepal has declared TITI as the authorized body to provide training to technical instructors (MoE, 2012). The time frame of the training was taken from three to 15 months referring to past studies to engage a substantial number of respondents for the study (Bhatti et al., 2013;Timperley et al., 2007). A self-report questionnaire was emailed to the geographically dispersed respondents with one gentle reminder as a part of the follow-up.
The surveyed data was analysed using data reduction (EFA) tool in SPSS 25. EFA was used to explore Delphi's generated variables that best described the environmental factors that could affect training transfer among the technical education instructors in Nepal. Before running EFA, a few essential safety checks were carried out and met. Sample size was 251 which was classified somewhere between fair and good (Comrey & Lee, 1992), the ratio of the sample size to the number of variables was 8:1, higher than the minimum ratio of 5:1 (Hair et al., 2014), no values were missing in analysis (Field, 2017) and absence of outliers was ensured (Cohen et al., 2018). Normality of data was assured taking the references of the values of Skewness and Kurtosis (George & Mallery, 2016). Besides, nine reverse statements were generated to increase respondent engagement, and reverse coding was carried out on them (DeVellis, 2017).
Prior to factor generation, other essential decisions were also made. Firstly, eight items were removed for Promax rotation on the basis of correlations value (r) < 0.3 resulting in 32 items for EFA. The measure of sample adequacy was ensured with Kaiser-Mayer-Olkin (KMO) of value 0.916. Kaiser's Eigen value of greater than 1 rule was followed. Communalities of average extraction of all items scored 0.61 which was above the minimum value of 0.5. Finally, the items loading in Promax Rotation was selected among available rotation methods to rotate all the variables and identify where these variables fit the most. Coefficient values below 0.50 were suppressed at this point; and cross-loadings were removed (Field, 2017).
Items clustered by EFA were then run on the grounds of correlational values that they possessed with other items. Further, Principal Component was selected for Extraction and maximum iterations for Convergence were set at 25. Hence, after running EFA on 32 items, substantive interpretation based on the factor loadings (Hair et al., 2014) referring to TVET experts and literature, it produced 26 items and six factors. Nomenclature, on the grounds of common features they acquire and their ability to incorporate all the statements (Cohen et al., 2018) was done which were: (i) organizational transfer intervention, (ii) external monitoring and evaluation (M&E), (iii) local school governance, (iv) management support, (v) social support, and (vi) curriculum standard. Only factors with a minimum of three items (interchangeably used as statements) were retained in this study. Table 1 shows the descriptive statistics, reliability estimates and measures of association using Pearson Correlational tool among these explored six external and internal factors. Table 1 shows the Cronbach's Alpha score that ranges from 0.61 to 0.90. Referring to Hair et al. (2014), α value of 0.61 was accepted in this exploratory research that Hinton et al. (2014) explains as moderate reliability. A few other studies related to transfer of training were also found to have accepted similar α values (Chiaburu & Marinova, 2005;Hinrichs, 2014). The Mean values extend from 3.41 for curriculum standard which is the lowest to 4.72 for social support which is the highest. The correlation coefficients of all the explored factors exhibit positive associations with statistical significance (p < .01) among one another and span from low (Example: association between curriculum standard and external M&E), to strong (Example: association between organizational transfer intervention and management support).

Results
The study results proceeded in two-step process after the instrument generation. First, EFA was executed and second, confirmatory factor analysis (CFA) was carried out to test the model.

Exploring the Model: Exploratory Factor Analysis
Among the six factors explored using EFA, the first factor i.e. organizational transfer intervention explains the highest variance among all the six factors which is 35.27% of the total variance while the second factor 'external M&E' explains only 6.31% of the variance. The remaining factors explain less than 5% of the variance in which the factor 'curriculum standard' explains 3.69% of the variance, the lowest among the six factors. The items coded 'ie' represent internal work environment and those coded 'ee' represent external environment.

Factor One: Organizational Transfer Intervention
Factor one named organizational transfer intervention explains the measures and concerns of the organizational management towards training transfer (see Table 2). Interventions from management level, particularly head-teachers on whether training is applied or not, and gathering feedback from students are theoretically guided (Willms, 2000). On the other spectrum, Renta-Davids et al. (2016) explores that among the environmental factors, access to resources significantly moderate between the competences learned at school and those used at the workplace. So, access to resources, and alongside, assessment on their use for training transfer are necessary to foster the transfer process. Also, the role of students has been confirmed to influence teaching styles and methods used by instructors (Lekena & Bayaga, 2012). This factor is related to previously used Factor 'Opportunity to use' in Revised LTSI (Bates et al., 2012), but goes beyond its scope since providing resources is simply not adequate to ensure training transfer and intervention may also be required.

Factor Two: External Monitoring and Evaluation
The second factor named External Monitoring and Evaluation (M&E) is a newly explored factor representing environment external to the workplace, beyond its control (see Table 3). This factor includes M&E activities with regard to training transfer. M&E is widely studied and acknowledged in improving TVET in Nepal (MoE, 2012) as well as in overall teaching quality (Phelps, 2014;Supovitz & Taylor, 2005). External M&E may drive the instructors to give better performance also indicating its influence on training transfer. Besides that, conducting M&E requires integrity to address the issues of pseudo-evaluation. Literature also suggests the need for state and district monitoring systems in order to encourage learning outcome-oriented teaching strategies and hold teachers, students and guardians accountable for the school results (Willms, 2000). In the context of Nepal, Education Policy 2019, in one of its objectives, has stated about ensuring competence, honesty, commitment and accountability of the teachers which is done through M&E (MoEST, 2019). In TVET, skills assessments are stressed by respective universities or regulatory bodies which is closely linked with teacher's training application. In this manner, this factor 'external M&E', highlighted as the impetus to improve education quality, was explored as a new factor.

Factor Three: Local School Governance
The third factor 'local school governance' (see Table 4) explains the governance which functions at a local level and quasi-market in which actors of local schools govern and make influence on schooling and education (Hanberger et al., 2016). So to ensure good governance at school level, the efforts of different actors and institutions are required such as state, local level education committees, school management committees, parents, pressure groups and teachers themselves. This factor includes learning through professional networks, concerns of local stakeholders and even guardians. Besides, in local government model, the local government governs education and the institutions applying both national and local school policies (Hanberger et al., 2016). This can also be linked with Nepali context as Article 56 along with Schedule 6, 7 and 9 of the constitution of Nepal have clarified power devolution to state and local government that includes matters related to education (Government of Nepal [GoN], 2015). Furthermore, studies have confirmed the positive role of parental involvement in evaluation of teacher's teaching methods and style, and in academic success and school's effectiveness (e.g. Wilder, 2014). School level governance thus influences school's education and thereby the extent to which instructors transfer the training.

Factor Four: Management Support
The fourth factor explored was management support (see Table 5). This factor is different from the supervisor support which has also been discussed distinctly in the past studies (Facteau et al., 1995). Borrowing the conceptual understanding from Tracey and Tews (2005), this study presents management support as the extent to which the school leaders encourage the employees to take part in training and then support them in the process of training transfer. While supervisory support has remained salient in extant literature (Park et al., 2016), this study shows that the senior level management has more robust role than supervisors in the training transfer process. Lack of support from management has been reported to hinder the transfer process (Jackson et al., 2019) and support from superiors has shown to foster it (Festner & Gruber, 2008). Since the role of leadership in schools is instrumental in student achievement and teacher performance (Louis & Lee, 2016), their roles in training transfer related matters also influence the transfer rate of instructors.

Factor Five: Social Support
The fifth factor is social support manifested from the lens of knowledge sharing culture with peers, and support from them (see Table 6). The roles of peers correspond to the previously used scales as well (Example: Bates et al., 2012;Tracey et al., 1995). The influence of social factors such as appreciation of peers, cooperation and such has also been reported in past studies in TVET institutions (Collin et al., 2008). Both peer support and family/friends support are accepted as important sources of social support (Kassis et al., 2019). Peers and family/friends of teachers were found to be the common sources of social support to share about their workload stress more than their head-teachers and to foster training transfer process (Ferguson et al., 2017).

Factor Six: Curriculum Standard
The sixth factor explored in this study is curriculum standard (see Table 7) which is an essential determinant of instructor's workload and has been recognized in previous studies (Festner & Gruber, 2008). The result indicates that curriculum standard comprises load of the course content concerning personal capacity of instructors to transfer (Bates et al., 2012), and student teacher ratio (STR) as one of the indicators of TVET quality (Inter-Agency Working Group on TVET Indicators, 2014; Wilson, 2006). Also, their heavy engagement to meet curriculum standards and complete the course in time increases their workload taking away their time and effort from planning and key instructional activities including training transfer (Kim, 2019). These components directly influence the training transfer of the instructors. The ideas of STR and curriculum are beyond the control of the school environment, and therefore represent external environment.

Testing the Model: Confirmatory Factor Analysis
In the second step, CFA was run to test the model-fit using AMOS 23 which uses maximum likelihood estimation procedure (Hair et al., 2014). For model fit assessment, chi-square test and a group of descriptive goodness-of-fit indices were referred. However, since the initial results for the six constructs explored through EFA showed poor model fit, the concerns of construct validity (discriminant and convergent validity) were addressed to validate the measurement model (Bhatti et al., 2013) for which items with less standardized loadings were removed in the constructs (Hair et al., 2014). Consequently, three constructs namely: local school governance, management support and curriculum standard were removed since there were less than three items remaining in them since literature (Example: Raubenheimer, 2004) suggests a minimum of three variables in a construct. With these, only three constructs were retained: organizational transfer intervention, external monitoring and evaluation and social support. Table 8 shows composite reliability of all the three factors above 0.70 and shows that their Average Variance Extracted (AVE) was at an acceptable level. To assess the model fit, Chi-square goodness-of-fit index was initially tested. However, the actual size of test statistic is based on other conditions along with the model adequacy. Moreover, chi-square statistic is very sensitive to sample size and model complex- There is adequate number of instructors in comparison to the number of students to apply the training.  (Raykov & Marcoulides, 2006). Therefore, alternative measures of fit such as Adjusted Goodness of Fit Index (AGFI), Comparative Fit Index (CFI), normed fit index, (NFI), root mean square error of approximation (RMSEA), CMIN/Df and Tucker-Lewis Index (TLI) were further examined (Hair et al., 2014;Kline, 2016). Therefore, though the value of χ 2 in the CFA model was statistically significant (p < .05), the remaining results suggest the three-factor model can be considered a good fit for the data on the grounds of acceptable baseline data from the literature (Bhatti et al., 2013;Hair et al., 2014): CMIN/DF = 2.868; CFI = 0.945; AGFI = 0.869; NFI = 0.919; RMSEA = 0.079 and TLI = 0.926 (see Table 9). With this model fit, the standardized factor loadings of three retained constructs are shown in Fig. 1.

Discussions
The purpose of the study was to first explore, and then confirm the environmental factors that affect training transfer among the instructors of technical education in Nepal. In this respect, from both EFA and CFA, the study revealed that there is an instrumental role of organizational transfer intervention. In this study, the role of the organizational management with their decisions and actions is shown to be instrumental in influencing the training transfer. The management unit requires intervention to assess the transfer of training among the instructors in the classrooms or workshops through direct queries, observing resource consumption, and even asking the students. The 8th amendment of the Education Act, 2028 of Nepal also dictates head teachers' appraising responsibility of the instructors (MoE, 2016). On the other hand, support from social circle also promotes the training transfer. The role of instructors often extends beyond the conventional notion of classroom teaching as they often interact with their peers. Support from colleagues therefore positively influences them to apply training (Bates et al., 2012). Extant Literatures have also revealed the role of various internal environmental factors influencing the training transfer (e.g. Blume et al., 2010;Tonhäuser, & Büker, 2016).
This study has further shown that there are both external environmental factors and internal environmental factors that affect the transfer of training among instructors. These concepts of external and internal environmental factors originated in the very first round of Delphi and were retained till the assessment of the model using CFA. Unlike the internal environment, external environmental factor such as external M&E is beyond the grip of the school environment, and is influential in the transfer of training among the instructors. Though the roles of management support or the actors of school governance, and even curriculum standard were initially explored representing both internal and external environment, CFA results made it evident that their influence in the transfer process of the instructors can rather be contextual. When examined carefully, all the confirmed factors affecting the transfer of training among the instructors of technical education can be explained through two driving forces: (i) Support and (ii) Control. The former driving force is explained by organizational support theory which posits that the support such as aid, resources or psychological-social support that the organization provides to their employees, the value they give to their efforts and the concerns they show to their well-being oblige them to help the organization reach its goals (Eisenberger et al., 2001). This reciprocity fosters the transfer climate and training transfer (Zumrah & Boyle, 2015). Meanwhile, control functions as the second driving force which indicate that getting support may not necessarily ensure that instructors will transfer the training (Simosi, 2012). In this connection, the transfer climate framework has also presented two workplace cues viz. situation cues and consequence cues in which the latter explains that trainees while applying the learning after returning to their job will face different consequences. They are positive and negative feedback, punishment and no feedback  (Rouiller & Goldstein, 1993). The theories behind positive and negative feedback are also closely associated with positive and negative personal outcomes respectively in revised LTSI (Bates et al., 2012). However, further to the existing body of knowledge, this study claims that both support and control are required at different circumstances, independently or together, to facilitate the training transfer among the instructors of technical education in Nepal and these forces can be both internal and external to the organization. Figure 2 below offers a model of environmental factors contributing to the transfer of training among the instructors of technical education in Nepal.

Conclusions and Implications
In the context of instructors of technical education in Nepal, the three environmental factors that affect training transfer among the instructors represent both internal and external environment. The study suggests that the role of internal organizational management is central in affecting training transfer. Besides, peer support and culture of sharing knowledge also can enhance instructors' performance. External environment that includes M&E implementing bodies and policy makers also influences the transfer process but that effect is beyond the scope of the school management. It is Trainings are transferred by the instructors through support or control from environmental forces. Therefore, it is essential for the training providers to scan the school environment and facilities during the training needs analysis and training design phase in order to enhance the level of training transfer. Based on these study findings, management of the organizations can intervene as per the necessity and maintain culture of knowledge sharing and support in the school. Furthermore, TVET regulatory bodies and policy makers can also emphasize and develop post-training mechanisms to promote training transfer. Proper transfer of training promotes students' learning and overall quality of TVET.
This study included the respondents who had participated in the instructional skills trainings conducted 15 months to three months before the survey commenced. Though the broad timeframe was taken referring to past studies, this might affect in the level of training transfer as explained by Blume et al. (2010). Hence, acknowledging this as a limitation, further research can be carried out taking the reference of a specific time frame. Besides, the study also opens the avenue to examine the model fit of the explored factors through CFA using other data sets and to include structural model and conducting structural equation modelling (SEM) using the explored or confirmed constructs as independent variables and including training transfer as the dependent variable.
Prakash C Bhattarai PhD is Associate Professor and Associate Dean at Kathmandu University -School of Education, Lalitpur, Nepal. He teaches qualitative, quantitative and mixed methods research, and carries out research in the education and development sectors of Nepal. He has been working as a faculty, project evaluator, researcher, and trainer in several national and international organizations. He has presented papers and got training in several countries. He is an active member of non-profit and educational forums in Nepal. He has keen interests in anti-corruption, integrity, ethics, ethical leadership, inclusion, educational and societal reform, comparative education, TVET, and mixed-methods research. He is engaged in writing and carrying out research in these areas.