8CoetseeEiselen.qxd The current context i.e globalisation, increased competition and the development of information technolog y, requires organisations to make the most of its intellectual assets (Donovan, Hannigan & Crowe, 2001). Development interventions require a substantial allocation of financial, human and time resources, but there is little evidence in research that the skills, knowledge and behaviour learnt in training programmes are transferred to the job or result in changed behaviour in the workplace (Baldwin & Ford, 1988; Ford & Weissbein, 1997; Gist, Bavetta & Stevens, 1990). This implies that learned behaviour is not generalised to the job context and maintained over a period of time in the job. The most commonly cited estimate in the literature is that only 10% of learning is transferred to improved job performance (Holton & Baldwin, 2000). Learning transfer can be considered one of the fundamental cornerstones in the establishment of a learning organisation (Senge, 1990) and to enable an organisation to utilise learned knowledge, skills and behaviour acquired during a learning event, learning transfer must take place between the classroom and the workplace. Baldwin and Ford (1988) as well as Ford and Weissbein (1997) define transfer as “…generalisation of the skills acquired during a learning event to the work environment and the maintenance of the acquired skills over time”. Further to the preceding statement Broad and Newstrom (1992) state that transfer of training can be defined as “the effective and continuing application, by trainees to their jobs, of the knowledge and skills gained in training – both on and off the job”. From the definitions, one can concur that there is consensus that the transfer of learning involves the application, generalisability and maintenance of newly-learned knowledge and skills. There is, however, no concensus regarding which factors influence learning transfer. Table 1 gives a concise layout of the most important components and variables cited in literature that could influence the effectiveness of learning transfer. From Table 1 it can be seen that there are numerous factors that could inf luence the effect iveness of an intervent ion. It is almost impossible to make an informed decision regarding the effectiveness of an HRD intervention if the stated variables are not taken into consideration. Numerous learning transfer studies (Table 1) conducted in the past utilised a wide variet y of instruments and measures (with questionable psychometric properties) to measure the transfer of learning (Holton, 2000). Much of the research has focused on training design factors that influence transfer (Kraiger, Salas & Cannon-Bowers, 1995; Warr & Bunce, 1995). A second research focus has focused on factors in the organisational environment that influence the individual’s abilit y and opportunit y to used newly learned knowledge in the work environment (Noe 1986; Rouillier & Goldstein, 1993). Another stream of research has focused on individual differences that affect transfer (Gist, Stevens & Bavetta, 1991) and contemporary research has focused on developing measuring instruments to measure transfer and its antecedent factors (Holton, Bates, Seyler & CArvalho, 1997) Authors such as Ford and Weisbein (1997) and Rouiller and Goldstein (1993) regard the transfer climate as an important variable that may impact on intervention effectiveness. In this regard Rouiller and Goldstein (1993, p. 379) concept ualise transfer climate as “... those situations and consequences which either inhibit or help facilitate the transfer of what has been learned in training into the job situation”. Bates et al. (1996) concur with Rouiller and Goldstein (1993) in regarding the transfer climate as the learner’s perception of the job environment and that it affects the extent to which a learner will utilise skills within the work environment. Research done by Tracy, Tannenbaum and Kavanagh (1995); Rouiller and Goldstein (1993); and Xiao (1996), found that transfer climate has an important influence on the learner’s motivation to apply acquired knowledge and skills within the job environment. Transfer climate can therefore act as mediator bet ween the organisational context and the learner’s work attitude and work behaviour. W J COETSEE jc@rau.ac.za Department of Human Resource Management University of Johannesburg R EISELEN Statistical Consultation Ser vice University of Johannesburg ABSTRACT The purpose of this study was to identif y learning transfer variables impacting on learning transfer using the Learning Transfer System Inventory (LTSI). The secondary objective was to determine if there are any statistically significant differences in the mean transfer variable scores between geographical areas, years of service, age groups, sex, qualifications and language groups. The sample used in this study was a convenience sample of 240 employees working for a Banking group. Analysis of variance (ANOVA), Multivariate analysis of variance (MANOVA) and post- hoc tests were used to analyse the data. The results show that, while age and gender do not have an impact on the learning transfer factors, level of education, home language and both length of service within the organisation and in the current position do. Geographic area also impacts on learning transfer indicators. Effect sizes, however, are small to moderate Key words Learning transfer variables, learning transfer, Learning Transfer System Inventory MEASURING LEARNING TRANSFER IN A FINANCIAL INSTITUTION (PART 2) 56 SA Journal of Industrial Psychology, 2006, 32 (2), 56-63 SA Tydskrif vir Bedryfsielkunde, 2006, 32 (2), 56-63 TABLE 1 FACTORS INFLUENCING THE EFFECTIVENESS OF LEARNING TRANSFER Factor Variable Description Learner � Training motivation Intra-personal processes refer to (Facteau et al 1995; Warr character traits unique to the and Bunce 1995) individual and that could � Self-concept (Mink et al. influence the effectiveness of 1994; Knowles 1984) an intervention. The individual � Learning motivation learner does not function in a (Mathieu et al. 1992; Baldwin vacuum, but forms part of a et al. 1991) greater system. This implies that � Ability (Wexley en Latham the interaction process between 1981) the individual and the greater � Attitude (Ford en Noe 1987) system results in reciprocal � Age, tenure; (Warr & Bunce, influencing that should be taken 1995) into account during the � Self-efficacy (Gist, Stevens & evaluation process. Bavetta, 1991; Stevens & Gist, 1997; Seyler, Holton, Bates, Burnett, Carvalho, 1998) � Ability to receive feedback (Knowles 1984) � Post-training maintenance (Gist et al. 1990) � Pre-training discussions/ motivations (Brinkerhoff & Montesino, 1995; Facteau, Dobbins, Russell, Ladd & Kudish, 1995); � Organisational commitment and job involvement (Tesluk, Farr, Mathieu & Vance, 1995) Environ- � Transfer climate (Baldwin en In order to have an impact mental Ford 1988; Rouiller en within the organisation, the factors Goldstein 1993; Xiao 1996; learner must apply newly Ford en Weissbein 1997) acquired knowledge, skills and � Culture (Marquardt and Engel attitudes in the workplace. 1993; Veldsman, 1998) Critical factors for intervention � Supervisory attitudes and success are work environment support, workgroup support aspects such as support, learning (Ford, Quinones, Sego & Sorra, transfer climate and the 1992; Quinones, Ford, Sego opportunity to apply new skills. & Smith, 1995; Xiao, 1996) The effectiveness of an � Team learning conditions and intervention is influenced by a processes (Watkins and variety of factors over which the Marsick 1993; Kasl et al. 1995) practitioner has little or no control. These factors should thus be taken into account during the evaluation process. Learning � Applicability of intervention; The effect of the previously event Needs analysis processes; mentioned processes on design; implementation and intervention effectiveness is well evaluation practices (Sullivan known and researched. et al. 1990; Brinkerhoff 1987; Therefore, the inclusion of these Broad and Newstrom 1992 ) factors in the evaluation process � Adult learning principles is instrumental in determining (Knowles, 1984; Knowles, intervention effectiveness. Holton, Swanson, 1998) Rouiller and Goldstein (1993) operationalise the construct Learning Transfer Climate by distinguishing between two categories of indicators, namely Sit uational Indicators (which remind learners of the training they have undergone or by providing learners with the opportunity to use their skills and knowledge in the workplace) and Consequential Indicators (which indicate that learners experience certain results or consequences when entering the workplace after training). Rouiller and Goldstein (1993) regard four types of dimensions, namely indicators concerning objectives, social indicators, task indicators and self-control indicators, as indicators which will either remind learners of what has been learned or which will provide learners with the opportunity to utilise what they have learned. The aforementioned thus refers to Situational Indicators encountered in the workplace. These dimensions are schematically represented in Table 2 as follows: TABLE 2 SITUATIONAL INDICATORS Indicators concerning These indicators remind the learner to apply Objectives newly acquired knowledge within the workplace. For example, by setting objectives a superior would encourage the learner to apply knowledge within the workplace. Social Indicators These indicators pertain to the extent to which group membership promotes or inhibits learning transference. This includes what the effect of the behaviour and influence of the superior, colleagues and subordinates would be on the learner. Task Indicators These indicators refer to the nature and design of the learner’s job. It also refers to the way tasks have been designed and the availability of equipment to assist learning transfer within the workplace. Indicators concerning The indicators here pertain to a variety of self- Self-control control processes that permit the learner to utilise newly acquired knowledge within the workplace. (Table Taken from Rouiller and Goldstein 1993, p.383) Managerial support for applying the skills learned in training has consistently been found to relate to more effective transfer (Facteau et al. 1995; Ford et al. 1992). In this regard Goldstein (1993) argues that superiors who are interested in and listen to the ideas employees learned in training and allow experimentation of new skills have been found to be an important factor in learning transfer. The second indicator, namely Consequential Indicators, are regarded by Holton et al. (1997:98) as “...on-the-job outcomes that affect the extent to which training is transferred”. Elements such as positive, negative, no feedback and punishment can be considered as indicators (Table 3) in this regard and are tabled as follows: TABLE 3 CONSEQUENTIAL INDICATORS Positive Feedback This indicator refers to positive information provided to the learner because application of acquired knowledge and skills is taking place. Negative Feedback Negative information is given to learners because application of knowledge and skills is not taking place. Punishment Learners experience negative consequences as a result of new skills and knowledge being applied, whether by superiors or by colleagues. No Feedback No information is given to the learner concerning the importance of utilising new knowledge and skills. (Table taken from Rouiller and Goldstein 1993, p. 383) Arguing that the construct Transfer Climate is only one set of factors that influence transfer, Holton et al (2000) use the concept Transfer System and define it as all the factors in the person, training and organisation that influence transfer of learning to job performance. The concept Transfer System is therefore a broader construct than Transfer Climate but includes all factors traditionally referred to as Transfer Climate. Building on his evaluation approach (Holton, 1996), the Transfer Systems Approach (Figure 1) describes a subset of this evaluation approach namely, the transfer of learning to individual, group and organisational performance. The model hypothesises that HRD outcomes are a function of both ability/ enabling elements and motivation and environmental influences (Noe, 1986) at three outcome levels namely learning, individual performance and organisational performance (Holton, 2000). MEASURING LEARNING TRANSFER 57 The outcomes are respectively defined as the achievement of learning outcomes desired in an HRD intervention, change in individual performance as a result of the learning being applied in the job, and results as a consequence of the change in individual behaviour (Holton 1996). Secondary influences are also included, especially those that affect motivation. Variables such as self-efficacy and learner readiness serve as examples in this regard. It is clear that the Learning Transfer System comprises four aspects (along with variables indicated in Figure 1), namely ability, motivational elements, the work environment and secondary influences. This is also indicative of mechanisms that should be measured and managed effectively in the learning transfer process in order to achieve intervention effectiveness. Using exploratory factor analysis of the Learning Transfer System Inventory (instrument that measures the operationalised variables in Table 4) to determine if an interpretable facture structure of latent transfer system constructs can be identified when the instrument is applied within the South African context, Coetsee and Eiselen (2004) found four interpretable factors. These factors are described in Table 4. TABLE 4 DESCRIPTION OF FACTORS Factor Variable Interpretation 1 Situational Factor 1 is associated with learning transfer climate as indicators maintained by Rouiller and Goldstein (1993). Work environment factors such as support, learning transfer climate and opportunity to apply acquired knowledge, can be regarded as being critical to learning transfer. Factor 1 refers to the learner’s perception of the work environment and this influences the extent to which a learner will or will not utilise learned skills in the work environment. Transfer climate has an important influence on the learner’s motivation to apply acquired knowledge and skills in the workplace. The learning transfer climate can furthermore act as a mediator between the organisational context and the learner’s attitude towards and behaviour at work. 2 Intra-personal Factor 2 (Intra-personal Indicators), it has been indicators indicated that they refer to characteristics which can and be considered as being unique to the individual, and motivation they reflect the individual’s intrinsic perceptions. It is apparent that aspects such as self-efficacy, “... a judgement about task-specific capability...” (Gist, Stevens and Bavetta 1991; Warr and Bunce 1995 and Tannenbaum, Mathieu, Salas and Cannon-Bouwers 1991) and learning motivation can be considered as important Intra-personal Indicators. 3 Conse- Factor 3 (Consequential and Managerial Indicators) quential and refer to “on-the-job outcomes that affect the extent to managerial which training is transferred”. Elements such as indicators positive, negative, no feedback and punishment can be regarded as indicators in this regard and are closely associated with the views of Rouiller and Goldstein (1993). The role of the supervisor holds important implications for learning transfer, not only in providing feedback and sanctioning behaviour, but also as far as structuring the learner’s job content, workload and so forth are concerned. Two aspects are therefore significant here, namely the extent to which he learner experiences positive or negative consequences in utilizing acquired knowledge, and the role that the superior plays in creating pportunities for applying this knowledge. 4 Learning As far as Factor 4 is concerned, it is apparent that the orientation extent to which a learner's’ input has been obtained indicators prior to the commencement of training, including the extent to which expectations are clarified, has a particular influence on learning transfer. Given the results, the conceptual model of transfer (Holton, 2000), is adapted according to the results in question as indicated in Figure 1. The adapted model hypothesises that HRD outcomes are a function of ability/ enabling elements, (learning orientation indicators), individual characteristics (intrapersonal indicators and motivation) and environmental influences (situational-, consequential and managerial indicators) at three outcome levels namely learning, individual performance and organisational performance (Holton 2000). The outcomes are respectively defined as the achievement of learning outcomes desired in an HRD intervention, change in individual performance as a result of the learning being applied in the job and results as a consequence of the change in individual behaviour (Holton 1996). Figure 1 is furthermore indicative of those factors that an organisation should include in its learning transfer system and which should be managed as such. Problem statement The general problem examined in this study mainly centers on the measurement of learning transfer variables in the work environment. Despite the importance of learning and the transfer of learning to the work environment, the HRD field does not have a generally accepted measurement approach nor does it have clear concensus on the nomological network of factors affecting transfer of learning in the workplace. In this regard, Coetsee and Eiselen (2004) identified 4 factors in the South African context that impact on learning transfer. An COETSEE, EISELEN58 Individual Factor 2: characteristics Interpersonal indicators and motivation Environment Factor 1: Factor 3: Situational indicators Consequential and marginal indicators Outcomes Learning Organisational Individual performance performance Ability/ Enabling Factor 4: elements Learning orientation indicators Figure 1: Adapted model understanding of these factors that prevent learners from applying will enable the organisation to increase its Return on Investment (ROI) and identif y the factors which make some learning programmes more successful than others. Against this background, the research problem in question is as follows: � Which factors impact on the transfer of learning in the work environment? From this, the following secondary objective was formulated: � Are there any statistically significant differences in the mean transfer variable scores between geographical areas, years of service, age groups, sex, qualifications and language groups; RESEARCH DESIGN Research approach This study is a quantitative study and a cross-sectional survey design was used to describe the information on the population collected. The study is also exploratory and descriptive as well as retrospective in nature (i.e. it was done on retrospective data). Elements of the research design are predetermined and in addition it is ex post facto and attempts to show causes and consequences after they have occurred. Research methodology Sample The sample utilised in this study is a convenience sample of SA employees undergoing training and comprises all employees (N=240) of the Home Loan Processing Section of a well-known listed Banking Group in South Africa. The section is responsible for processing all home loans, including credit screening, data capturing of information and administrative loan management, for the Banking Group. The respondents (Table 5) are dispersed over five geographic areas in South Africa, namely Randburg, Pretoria, Bloemfontein, Durban and Cape Town. TABEL 5 REACTION OF THE SAMPLE Geographical area Number of Number of Response % questionnaires questionnaires distributed returned Florida/ Randburg 86 79 92% Pretoria 54 50 93% Cape Town 48 43 90% Durban 27 21 78% Bloemfontein 25 22 88% Total 240 215 90% A total of 240 questionnaires were distributed of which 215 (90%) were returned. The data was captured and converted into a data file. After filtering of the data based on criteria such as incompleteness and the giving of socially acceptable answers (see the following paragraph), the workable number of questionnaires was 177, that is, 82% of the total number of returned questionnaires was usable. The large number of questionnaires considered unusable can be attributed to the following factors: � Some respondents felt threatened when confronted with the organisation being evaluated, and in spite of assurances that all information would be treated confidentially, feared being victimised by the organisation. This was particularly true for sensitive questions related to the organisation itself where respondents simply failed to answer these questions. � Some respondents gave socially acceptable responses. This indicates the extent to which respondents’ answers to the questions did not reflect the intensit y of their own experiences, but rather what they believed an acceptable response should be. Some questions were formulated in such a manner that socially acceptable responses could be identified through inspection. Measuring Instrument The items included in the measuring instrument (LTSI) were developed by Holton (2000). The original questionnaire, the Learning Transfer System Inventory consisted of 89 items. However, only 78 items were retained as the MSA values were larger than 0,6 (Coetsee & Eiselen, 2004). Research procedure Questionnaires were distributed electronically to the employees of the section. Prior to sending out the questionnaires, the Training Section of the Banking Group familiarised employees in each geographical area with the objectives of the investigation, the means of data collection and discussed the questionnaire’s content with them. Respondents completed the questionnaires in hard copy in their own time and returned the completed questionnaires to the Training Section by internal mail. Hence, responses were anonymous. TABLE 6 RELIABILITY COEFFICIENTS OF THE LTSI Factor Number of items Cronbach Alpha 1 45 0,9640 2 15 0,8828 3 13 0,8290 4 5 0,5093 Table 6 contains number of items and Cronbach Alpha Reliabilities. In addition to completing the 78 LTSI items (each measured on a 5-point Likert-type scale), respondents were also asked to provide background information including age, gender, qualification and years of service within the Banking Group and in their current job. RESULTS The secondary objective of the study was to determine whether there were any statistically significant differences in the vector of factor means of groups created in terms of the different biographical variables. Groups of employees were compared in terms of the four Learning Transfer factors using MANOVA. Where the null-hypothesis of equality of the vector of factor means could be rejected, ANOVA was used to determine in terms of which factors the groups differed. Finally, post-hoc comparisons were used to ascertain which specific groups differed significantly in terms of each of the factor means where significant differences were established: the Scheffe test was used if equal group variances could be assumed whereas Dunnett’s T3 was used if this assumption did not hold. Levene’s test for error variances was used throughout to establish whether the assumption of equal error variances could be assumed. Based on their responses, the following groups of employees were formed (Table 7). In each case, the number of respondents is indicated. Based on the MANOVA results, the null-hypothesis for the equality of the vector of factor means could not be rejected for either the four age groups (Wilks’ Lambda = 0,912; p-value = 0,217>0.05) or for the two gender groups (Hotelling’s Trace = 0,015; p-value = 0,624>0,05). MEASURING LEARNING TRANSFER 59 TABLE 7 GROUPS OF RESPONDENTS FORMED BY BIOLOGICAL AND BACKGROUND VARIABLES Variable Group Number of respondents Age group Up to 24 years 54 25 – 29 years 45 30 – 39 years 40 40 years and older 33 Gender Males 42 Female 134 Geographic area Florida/Randburg 66 Pretoria 40 Cape Town 33 Durban 19 Bloemfontein 17 Length of service at the At most 5 years 96 organisation More than 5 years 76 Length of service in current At most 5 years 156 position More than 5 years 12 Education level Less than grade 12 38 Diploma or B-Degree 45 Grade 12 but not a post school 70 qualification Home language Afrikaans 93 English 60 Africal Language 24 The null-hypothesis for the equality of the vector of factor means was rejected for groups formed based on geographical area (Wilks’ Lambda = 0,743; p-value < 0,005). The subsequent ANOVA results showed that the means of the geographic areas differed for each of the Learning Transfer factors (Table 8). TABLE 8 ANOVA RESULTS OF GEOGRAPHIC AREAS Source Dependent Type III DF2 MS3 F p-value Effect Variable SS1 size Corrected F_1 4,411 4 1,103 3,41 0,010 Model F_2 2,578 4 0,645 2,64 0,035 F_3 3,828 4 0,957 3,41 0,010 F_4 3,842 4 0,961 3,47 0,009 Intercept F_1 1414,823 1 1414,823 4377,65 0,000 F_2 2063,964 1 2063,964 8464,49 0,000 F_3 850,578 1 850,578 3030,99 0,000 F_4 1423,56 1 1423,560 5146,56 0,000 AREA F_1 4,411 4 1,103 3,41 0,010 0,27 F_2 2,578 4 0,645 2,64 0,035 0,24 F_3 3,828 4 0,957 3,41 0,010 0,27 F_4 3,842 4 0,961 3,47 0,009 0,28 Error F_1 54,943 170 0,323 F_2 41,452 170 0,244 F_3 47,707 170 0,281 F_4 47,023 170 0,277 Total F_1 1832,786 175 F_2 2610,29 175 F_3 1171,271 175 F_4 1810,479 175 Corrected F_1 59n354 174 Total F_2 44,031 174 F_3 51,535 174 F_4 50,865 174 The post-hoc comparisons showed that Bloemfontein (M = 3.0138) and Cape Town (M = 3,0658) differed significantly from Durban (M = 3,5633) in terms of the first factor, F_1 (situational indicators) while in terms of F_2 (Intra-personal indicators and motivation), Cape Town (M = 3,719) differed significantly from Durban (M = 4,14). The post-hoc comparisons however, could not detect which geographic areas differed in terms of F_3 (Consequential and Managerial indicators) and F_4 (Learning Orientation indicators). The effect sises (Table 9) showed that geographic area only has a small effect (between 0.1 and 0.3) on each of the factor means. Hence, although the result is of statistical significance, the practical significance is limited. There was a significant difference in the vector of factor means between people with at most 5 years of work experience at the organisation and those with more than 5 years experience (Hotelling’s Trace = 0,058, p-value = 0,049<0,05). The ANOVA results showed that this difference could be ascribed to a significant difference (F = 5,763; df1= 1, df2 = 170; p-value = 0,017<0.05) in terms of the first factor, F_1 (Situational indicators). In particular, the sample mean for the group with at most 5 years of experience was higher (M = 3,284) than the group with a minimum of 5 years work experience (M = 3,07). This difference has limited practical significance since the effect sise is small (0,181). A similar result was obtained for the two groups formed based on years of service in current position: the vector of factor means differed significantly between those who have been in their current position for at most 5 years and those who have been in the same position for a longer period of time (Hotelling’s Trace = 0,062; p-value = 0,042<0,05). The ANOVA results showed that it is in terms of F_1 (Situational indicators) only that the two groups were significantly different (F = 8,963; df1 = 1 df2 = 166; p-value = 003 <0,05). The result is of limited practical significance since the effect sise is only 0,226 The sample mean for F_1 was higher (M = 3,216) for those who have been in the same position for at most 5 years than the sample mean for the group who have been in the same position for more than 5 years (M = 2.7). The null-hypothesis for the equality of the vector of factor means was rejected for the three groups formed in terms of educational level (Wilks’ Lambda = 0,866; p-value = 0,006<0,05). The subsequent ANOVA results showed that the null-hypothesis of equal group means could only be rejected for the third factor, F_3, i.e. Consequential and managerial indicators (F = 5,047; df1 = 2, df2 = 150; p-value = 0,008<0,05). Based on the Scheffe post-hoc comparisons, it was established that the group with a low level of education (less than grade 12) differed significantly from those who have grade 12 but not a post school qualification. The sample mean for the group with an educational level less than grade 12 was higher (M = 2,741) than the mean for the group with grade 12 but not a post school qualification (M = 2,4). This result is of limited practical significance as the effect of educational level on F_3 was small (0,25). As far as the three home language groups are concerned (Afrika ans, English and African languages), the vector of factor means differed significantly (Wilks’ Lambda = 0,878; p- value = 0,004 < 0,05). ANOVA results showed that it is in terms of the second (F_2) and third (F_3) factors that the groups differed significantly, i.e. in terms of Intra-personal indicators and motivation and Consequential and managerial indicators. The ANOVA results together with the effect sises are shown in Table 9. Post-hoc comparisons revealed that the Afrikaans home language group (M = 3,74) differed significantly from the African language group (M = 4,01) in terms of F_2, Intrapersonal indicators and motivation while the English language group (M COETSEE, EISELEN60 = 2,34) differed significantly from the Afrikaans language group (M = 2,67) in terms of F_3, Consequential and managerial indicators. The effect sises, however, allude to a limited practical significance of the result. TABLE 9 ANOVA RESULTS OF HOME LANGUAGE GROUPS Source Dependent Type III DF MS F p-value Effect Variable SS size Corrected F_1 0,839 2 0,419 1,238 0,292 Model F_2 1,666 2 0,833 3,421 0,035 F_3 4,048 2 2,024 7,333 0,001 F_4 1,097 2 0,549 1,899 0,153 Intercept F_1 1355,342 1 1355,342 4002,318 0,000 F_2 1961,668 1 1961,668 8054,712 0,000 F_3 809,033 1 809,033 2931,248 0,000 F_4 1334,188 1 1334,188 4618,766 0,000 LANG1 F_1 0,839 2 0,419 1,238 0,292 0,118 F_2 1,666 2 0,833 3,421 0,035 0,195 F_3 4,048 2 2,024 7,333 0,001 0,279 F_4 1,097 2 0,549 1,899 0,153 0,146 Error F_1 58,923 174 0,339 F_2 42,376 174 0,244 F_3 48,025 174 0,276 F_4 50,262 174 0,289 Total F_1 1855,712 177 F_2 2639,213 177 F_3 1185,993 177 F_4 1836,847 177 Corrected F_1 59,762 176 Total F_2 44,043 176 F_3 52,072 176 F_4 51,359 176 DISCUSSION The main objective of this study was to determine which factors impact on the transfer of learning in the work environment. The secondary objective was to determine if there are any statistically differences in the mean transfer variable scores between geographical areas, years of service, age groups, sex, qualifications and language groups. From the results, it is apparent that the geographical areas of Cape Town and Bloemfontein differ significantly from Durban as far as Factor 1, Sit uational Indicators, is concerned. This factor is related to learning transfer climate, as claimed by Rouiller and Goldstein (1993), and can be considered as being critical to the learning transfer process. It appears that personnel working in the Durban area experience factors such as support, learning transfer climate and opportunity to apply acquired knowledge, more positively than people working in the Bloemfontein and Cape Town areas. Factor 1 refers to the learner’s perception of the work environment and this influences the extent to which a learner will or will not utilise learned skills in the work environment. Transfer climate has an important influence on the learner’s motivation to apply acquired knowledge and skills in the workplace. The learning transfer climate can furthermore act as a mediator bet ween the organisational context and the learner’s attitude towards work and behaviour at work. It can be speculated that the respondents from the Durban area in terms of Factor 1: � Believe that the application of skills and knowledge learned in training will lead to the recognition they value. This includes the extent to which the business unit demon- strates the link between development, performance, and recognition, clearly articulate performance expectations, recognise individuals when they do well, reward individuals for effective and improved performance, and create an environment in which individuals feel good about performing well. � Receive constructive input, assistance, and feedback from people in their work environment (peers, employees, colleagues, managers, etc.) when applying new abilities or attempting to improve work performance. Feedback may be formal or informal cues from the workplace. � Managers are involved in clarif ying performance expectations after training, identif ying opportunities to apply new skills and knowledge, setting realistic goals based on training, working with individuals on problems encountered while applying new skills, and providing feedback when individuals successfully apply new abilities. � Peers mutually identif y and implement opportunities to apply skills and knowledge learned in training, encourage the use of or expect the application of new skills, display patience with difficulties associated with applying new skills, or demonstrate appreciation for the use of new skills; � That skills and knowledge taught are similar to performance expectations as well as what the individual needs to perform more effectively. It also addresses the extent to which instructional methods, aids, and equipment used in training are similar to those used in the individual’s work environment. With regard to Factor 2, Intra-personal Indicators, it is apparent that workers in the Durban area have a more positive experience of this factor than the workers in the Cape Town area. This factor refers to characteristics that can be considered as being unique to the individual, and they reflect the individual’s intrinsic perceptions. It is apparent that aspects such as self-efficacy, “... a judgement about task- specific capability...” (Gist, Stevens and Bavetta 1991; Warr and Bunce 1995 and Tannenbaum, Mathieu, Salas and Cannon- Bouwers 1991) and learning motivation can be considered as important Intra-personal Indicators. As indicated, Factor 2 refers mainly to the intra-personal processes as applicable to the learner and on closer scrutiny of the items in question indicate that the Durban respondents: � Feel confident and self-assured about applying new abilities in their jobs, and can overcome obstacles that hinder the use of new knowledge and skills. � They are motivated to utilise newly acquired learning in their work. This includes the degree to which individuals feel better able to perform, plan to use new skills and knowledge, and believe new skills will help them to perform more effectively on-the-job. � Believe that applying skills and knowledge learned in training will improve their performance. � The work group accepts change, is willing to invest energy in changing, and supports individuals who use techniques learned in training. However, based on effect size, the geographic area only has a small effect on each of the factor means. Hence, although the result is of statistical significance, the practical significance is limited. It could be argued that the relatively youthful age of the respondents holds certain advantages for the study in question. Given the changed world of work, the employees would be expected to be more amenable to acquiring new knowledge and applying skills in the workplace. The aforementioned makes the respondents an ideal target group for reporting on learning transfer and on the variables it influences. On the other hand, one could speculate that persons in the 50-59 years old age group (4,2%) and the 60-69 years old category (,9%) are at the end of their careers and, therefore, are less enthusiastic about learning and utilising new skills. MEASURING LEARNING TRANSFER 61 It is also evident that persons with less than 5 years’ service differ significantly in respect of Factor 1 (Sit uational Indicators) from persons with more than 5 years’ service. Respondents who have less than 5 years’ service, experience variables such as learning transfer climate, support and opport unities to apply newly acquired knowledge more positively than respondents who have more than 5 years’ service. One could speculate that persons who have less than five years’ service still experience their organisation as being relatively new and that they are still in the process of acquiring work-related skills, consequently experiencing a steep learning curve. It could also be maintained that positive experience could be considered a function of the length of service. This carries the implication that persons with less than 5 years’ service still have certain expectations of the organisation, as opposed to persons with more than five years’ service who have already experienced different kinds of job limitations. These findings correspond with findings from Warr and Bunce (1995) who determined that significant independent contributions to learning scores are made by low age, general attitude to training and tenure. However, based on the effect size, the identified difference has limited practical significance. Furthermore, there are ostensibly no significant differences (regarding the four factors) bet ween the sexes. On the other hand, it is evident that the various qualification groups differ significantly in respect of Factor 3 (Consequential and Managerial Indicators). This is regarded by Holton et. al (1997) as on-the-job outcomes that affect the extent to which training is transferred. This factor thus emphasises the role of the supervisor/manager. One could speculate that the extent to which the supervisor creates a climate in which the learner experiences low levels of stress, has a reasonable workload and is empowered, would exercise an important influence on learning transfer. However, based on the effect size, the identified difference has limited practical significance Evidently, Afrikaans-speaking respondents have a pre- dominantly more negative experience of Factor 2 than Black respondents have. Insofar that the previous factor refers to intrapersonal factors and motivation, one could speculate that the Afrikaans-speaking group have probably experienced affirmative action/ employment equit y and therefore feel a lack of job security. On the other hand the black respondents enjoy more opport unities for promotion and have a high level of job security. The foregoing is also corroborated by the organisational policy of appointing and promoting only people from previously disadvantaged communities. The four factors, namely Situational Indicators, Intra-Personal indicators, Consequential and Managerial Indicators and Learner Orientation Indicators denote those factors that inhibit or facilitate learning transfer. 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