Transfer of training may be defined as the degree to which trainees apply to their jobs the knowledge, skills, behaviors, and attitudes they gained in training. see Elwood Holton defining Transfer of Training
Transfer of learning has long been an important HRD research issue. Since Baldwin and Ford’s (1988) review of the literature over a decade ago, considerable progress has been made in understanding factors affecting transfer. Much of the research has focused on training design factors that influence transfer (cf. Kraiger, Salas & Cannon-Bowers, 1995; Paas, 1992; Warr & Bunce, 1995). Another stream of research has focused on factors in the organizational environment that influence individuals’ ability and opportunity to transfer (Rouillier & Goldstein, 1993; Tracey, Tannenbaum & Kavanaugh, 1995). Other researchers have focused on individual differences that affect the nature and level of transfer (Gist, Bavetta, Stevens, 1990; Gist, Stevens, Bavetta, 1991). Finally, recent work has focused on developing instruments to measure transfer and its antecedent factors in the workplace (Elwood Holton, Bates, Ruona, 1998; Holton, Bates, Seyler, & Carvalho, 1997).
In recent years there has been an explosion of organizational interest in becoming “learning organizations,” creating corporate “universities”, and generally being more proactive in approaching education and learning. Many organizational leaders increasingly recognize that their firms’ future success will depend on the speed with which people can learn and transfer new ideas and information.
There is no question that transfer of learning is a formidable challenge for organizations. The most commonly cited estimate is that only 10% of learning transfers into job performance (although there is little empirical basis for this claim) and reports from the field suggest that a substantial part of organizations' investment in HRD is wasted due to poor learning transfer. see The Trillion Dollar Training Problem
There is no question that much has been learned over the past twenty years that has affected our understanding of transfer and its antecedents and inhibitors. At the same time, there are some persistent misconceptions that we suspect have served to constrain progress on the transfer problem:
Transfer is a function of a system of influences – not just learning design.
Questions of transfer are hardly new. In fact, they were among the first issues addressed by early psychologists such as Thorndike and Woodworth (1901). However, until fairly recently, the majority of transfer attention has been focused solely on the design and delivery of the learning event. Holton, Bates and Ruona’s (2001) concept of the transfer is of a system which they defined as all factors in the person, training and organization that influence transfer of learning to job performance. Transfer climate, the more common term, is actually but one sub-set of factors that influences transfer, though the term is sometimes incorrectly used to refer to the full set of influences. Other influences on transfer include training design, personal characteristics, opportunity to use training, and motivational influences. Thus, the transfer system is a broader construct than transfer climate but includes all factors traditionally referred to as transfer climate. Transfer can only be completely understood and influenced by examining the entire system of influences.
Transfer is not necessarily resistant to intervention.
Clearly, achieving transfer of learning is a complex and difficult challenge and there is no question that the amount of transfer from the learning initiatives in our organizations has been disappointing. Left to chance, the likelihood that significant transfer will occur from most learning initiatives is truly very small. However, to conclude that transfer is resistant to intervention is based on the assumption that interventions have regularly been designed and implemented and yet failed to yield transfer. That is not the case. While a number of exceptions exist, the reality is that transfer has generally not been actively pursued or managed with planned interventions. Transfer can be greatly affected by intervention. But you have to intervene. Moreover, the most successful transfer-inducing interventions will be those based on the accumulating evidence of what affects transfer in organizational contexts. In short, transfer is difficult but has not been shown to be resistant to intervention.
Achieving transfer does not require substantial new processes and systems.
One of the justifiable fears of practicing professionals is that prescriptions for improvement (particularly those stemming from academic authors) will likely involve new systems and more infrastructure and additional resources – at a level often not realistically available. To be clear, transfer of learning in organizations will not dramatically improve with a “business as usual” mindset. At the same time, we do not believe that the solution to the transfer problem lies in a radical increase in systems, people or organizational infrastructure. Rather, we contend that the most significant gains in transfer will come when learning is more tightly integrated into the process and reward systems that already matter in the firm. The challenge is not how to build a bigger and more influential transfer support system, but how to make transfer a more integral part of the existing organizational climate.
Transfer interventions will be most successful where the explicit goal is performance improvement.
It is a rare organizational learning context where transfer would not be included as a desirable outcome. But the reality is that learning activities have often been created more as a reward (top sales people seminar), an evaluation/assessment tool, or a designation of status than to truly improve work performance. It is hardly surprising to see little performance improvement when such improvement is not the ultimate objective of the initiative. Our experience is that the importance of performance improvement varies widely across learning contexts and some low transfer outcomes may well be because improved performance was never the primary goal to begin with. If we are to truly understand and build interventions that will improve transfer, then it is important that we do so when and where performance really matters to the learning sponsors.
Transfer is multi-dimensional
Most authors in the Industrial/Organizational Psychology discipline have adopted the definition of transfer as the application of learned skills to the workplace. However, at the risk of stating the obvious, transfer is not just one thing. Distinctions among types of transfer are not new, but they are often obscured. We find it particularly useful to think in terms of transfer distance. To illustrate, learning to drive a car and then finding yourself in a truck would be a situation that would demand transfer, but of a very short distance. On the other hand, learning principles of organizational change in a management development seminar and then attempting to practice behaviors stemming from those principles over time as head of a merger and acquisition team would define much greater distance. It is important to have some degree of clarity about the nature of the transfer of interest before designing and evaluating particular interventions.
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Metaphorically, transfer distance refers to the gap between the learning environment and application in the job environment. Various labels have been applied to this gap, including lateral vs. vertical transfer, specific vs. non-specific transfer, literal and figural transfer, and best known to HRD learning professionals, near vs. far transfer (Royer, 1979). Actually, all of these terms were originally used by educational and cognitive psychologist to talk about various levels or types of cognitive learning. Transfer distance integrates the cognitive notions of transfer as well as the learning to performance concepts into a single continuum. The transfer distance continuum progresses through two phases with six key events representing points along the journey from cognitive learning to broad performance application. The first phase, moving from knowledge to performance capability, is the learning process and the traditional domain of training. Node 1 represents the starting point for most training: acquiring cognitive knowledge or “know that.” However, for transfer to be possible requires that learning be expanded to node 2, acquiring knowledge for how to use the learning, or “know how.” Nodes 1 and 2 represent the minimum learning required to make transfer possible. Node 3, building performance capability through practice, we suggest is likely to significantly enhance transfer by providing learners opportunities to practice what is learned.
The second phase moves the learner from performance capability to sustained performance and represents the work process using the learning. Node 4 represents the traditional notion of near transfer, and that is the application of learned material to the learners’ immediate job and for the tasks at which the learning was targeted. Note though that Node 4 also represents proficiency, not just attempts at application. Learning transfer does not stop here, even though common uses of the term imply that it does. Node 5 represents the next step, repeating and maintaining learned performance. That is, the desired outcome is not just limited use of what is learned, but for the learner to continue to use the learning and maintain the job application. Node 6 then represents the pinnacle of transfer, the generalization of learning for application to tasks or jobs not originally anticipated by the training, but related in a way that allows the learning effects to multiply.
The traditional view of learning transfer in training has been from node 1 to node 4. Usually this represented classroom instruction to immediate job application. Nodes 5 and 6 have not been discussed as heavily because, frankly, the challenge of closing the gap from nodes 1 to 4 has been so significant. Newer learning designs which integrate learning with work significantly improve the transfer problem because they shorten the distance between nodes 1, 2, 3, and 4 until they are so small that they seem to disappear. Indeed a strong argument can be made that work-based learning initiatives move learning at least to node 3. However, it should also be apparent that they do not make the transfer problem disappear completely. At best they leave nodes 5 and 6 (repetition, maintenance, and generalization) still unresolved and usually node 4 (job application) is not fully addressed because the work systems (social and process) that support learning on the job are not incorporated into many learning initiatives. Consider management development training in coaching skills as an example. In this case, each node could mean the following:
Node 1 – learning the characteristics of effective coaching
Node 2 – learning the steps effective coaches use to conduct coaching sessions
Node 3 – role plays during training to practice coaching skills
Node 4 – trying out the new skills in a coaching session with an employee a few weeks after training
Node 5 – learner continues to coach employees on a regular basis, and the new coaching skills become more natural for the learner as success is experienced
Node 6 – learner builds on the principles of coaching to create more empowered employees who are more self-directed
Transfer distance provides a useful means of thinking about learning transfer systems. First, it helps by locating the type of learning event on the continuum. Second, it is useful to locate the type of transfer that is being targeted. That is, is the goal limited job-specific transfer (node 4), long-term performance (node 5) or generalized learning application (node 6). Together these provide a conceptual map of the distance to be closed by transfer improvement interventions.
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