The corporate goal to accelerate proficiency is as intriguing as it is mysterious. Though there is plenty of research on elite expertise and accelerated expertise, the area of accelerating proficiency is under-represented. Not many approaches or strategies are known to professionals and business leaders to accelerate proficiency in professional skills. A while ago I presented the paper on “Rethinking Professional Skill Development: Accelerating Time-to-Expertise of Employees” at Conference on Human Development in Asia, Japan. In that paper, I presented the analysis of proficiency curve which suggested three potential approaches that could conceptually and potentially accelerate proficiency acquisition of their employees. Simple principles of mathematics such as equations of straight lines, slope, and piece-wise representation were used to derive these three possibilities. This post attempts to describe those 4 possible routes or approaches without getting into mathematical analysis.
A simplified concept of accelerated proficiency is shown in figure 1, which depicts ‘normal proficiency curve’ in solid line and ‘accelerated proficiency curve’ in dotted line. Along the vertical axis is hypothetical proficiency levels represented as P1 to P6. Certain ground assumptions are made in this representation. Though not everyone will be truly a novice in any job, for the sake of simplicity, in context of new job role, it may mean base level proficiency in new skills represented as P1. If nothing is done, an individual will start learning the skills required to do the new job at time N1 and may follow ‘normal proficiency curve’, assuming a constant rate of proficiency acquisition. Eventually, that individual will attain desired or target proficiency P4 in time ‘N6’. This time interval ‘N6-N1’ (measuring from start of job) is called time to proficiency.
In a business context, the goal of an accelerated proficiency project would be to reduce the time to proficiency i.e. time taken by employees to acquire desired proficiency. In other words, it would mean to raise the slope of ‘normal proficiency curve’ to a new slope represented by dotted ‘accelerated proficiency curve’. The efforts are made to raise the slope of this curve so that the other individuals in same job/role/function may attain the same level of desire proficiency, P4, in shorter time ‘N4′ (compared to N6). Shortening this time is the goal of any accelerated proficiency project. See this post to read more about the business need of accelerating or reducing time to the proficiency of employees.
Mathematically, using equations of a straight line, slope, and piece-wise representation, it is seen that the ‘accelerated proficiency curve’ can follow 4 possible but different routes to attain desired proficiency.
The first route revealed by proficiency curve analysis is quite straightforward, called ‘proficiency-based training’ approach. What if an employee/learner is made to attend a program in which time is not a constraint i.e. a learner could receive training and move to next level by demonstrating the competence rather than spending some specified time in that program. In such an arrangement, the learner would keep getting structured training, learning assignments, continuous assessment/feedback, and support until he reaches the desired proficiency. In other words, the training/learning does not stop until he attains desired proficiency level. For such an intervention, the proficiency growth curve under normal circumstances is shown in solid line in figure 2 as ‘conventional proficiency-based training curve’, leading to desired proficiency in time ‘N6’.
If there were some strategies that could accelerate the slope of this curve to a new ‘accelerated proficiency-based training curve‘, it might allow a learner to reach desired proficiency in a shorter time ‘N4’, compared to ‘N6’, thus accelerating proficiency of that individual.
Though the concept sounds impractical at first, but this actually is based on Blooms’ Mastery Learning Approach in which the whole idea is to make trainees achieve proficiency right during training event and removing the time limits (Bloom, 1968). The educational theorist Carroll (1963) provided the first complete model of attaining proficiency in her “Mastery learning model”. Carroll challenged traditional educational philosophy with his model stating that ‘the learner will succeed in learning a given task to the extent that he spends the time that he needs to learn the task’ (p. 725). Carroll used certain factors like aptitude, or time needed to learn the task under ideal instruction, ability to understand instruction, and perseverance and external conditions like the time allowed for learning, and the quality of instruction. She speculated that majority of learners would be successful in gaining mastery in learning by a suitable combination of these factors and systematically maximizing time allowed for learning.
Bloom (1968) further developed this theory with an experiment in which he argued that with the proper condition of learning and time given to learner almost all learners were able to demonstrate desired performance. Inherently this approach builds practice into its training philosophy. This is the fundamental premise of the proficiency-based training movement which supports the idea of continuing to allow the trainee to practice until he has demonstrated desired standards of performance. Time is usually not a constraint in such situation but the mastery of some skills to a certain level is the target.
The outcome of proficiency-based training is that it is possible to achieve a constant level of mastery across several learners and to make it independent of time or number of practice trials. Recently several surgical and military educators have adopted Blooms’ Mastery Learning model to build proficiency right through training interventions. The training does not end until desired proficiency is achieved (Willis et al. 2012; Wilcox et al. 2014; Lee 2011; Rosenthal et al. 2009; Angelo et al. 2015; Stefanidi et al. 2005). Pilot training has recently started using this methodology by lifting the restrictions on the same number of hours of practice for all trainees but to actually track progress by task (Stewart and Dohme, 2005).
This approach would mean that even though an employee is not yet at full productivity level for every aspect of his job, he could be still competent to perform several functions of his job. Since learner is constantly involved in on-the-job practice mode during the entire training cycle, organizations probably could use them for certain part of the regular job.
In this approach, during the training, cycle learner is engaged in learning and practice embedded together. It includes regular practice (like S-OJT) or deliberate practice in which learners engage in repetitive performance, receive rigorous assessment, and receive informative feedback (Ericsson et al., 1993). Proficiency metrics for training tasks can provide the external motivation necessary to engage them in the skills acquisition process in ways that are not simply passing the time or performing some arbitrary number of practice repetitions.
As of now, there are several research studies, mainly in surgical areas which have demonstrated developing proficiency using proficiency-based training approach. In some research studies, simulation has been demonstrated to accelerate proficiency-based training approach. In general, there is still a lack of research studies which particularly investigated accelerating proficiency-based training approach itself. The reason probably is its philosophical origin to make training program ‘timeless” that would then be counter-intuitive to accelerate in any variation of this approach.
This method has its challenges too due to the undefined time limit. The first challenge with this approach is that it completely disregards any limit on the time needed to achieve desired proficient level, thus faster time-to-proficiency is not even the purpose of believers of this philosophy. It will be a hard sell to corporate managers telling them that time to proficiency could be unpredictable.
Such an approach at the educational institution might work. However, from a business standpoint, the employee is still under training until he reaches target proficiency. In other words, training continues until ‘desired proficiency’ level is achieved. It might be challenging for organizations to keep a newly hired employee “under-training” for an unpredictable amount of time, not knowing when he or she would reach desired proficiency.
In general, most employees get some sort of training (typically classroom training) to start their job or new role. This is shown as ‘conventional classroom training curve‘ in figure 3. In most cases, this conventional/formal classroom training would not be more than a couple of weeks or so. A new employee is provided with a systematic training event to learn the skills needed for the job. The training helps the novice to acquire the skills and attain a certain level of proficiency in the skills at the time of exit from the training course, say P2. The literature argues that traditionally training prepares a novice only to attain a level called “advanced beginner” as defined by Dreyfus & Dreyfus’s model (Clark, 2008). The definitions and characteristics of these stages (novice, advanced beginner, competent, proficient and expert) are described in other posts: 7 Phases of Skill Acquisition: A Novice’s Journey To Expertise And Beyond and Mastery Demystified: How Does a Novice Develop Himself into Master in Any Domain? Simply put, an advanced beginner is someone who starts comparing the new situations with previously experienced situations but still applies the earlier learned rules. Classroom training usually results in a spike in performance change and bring a novice to a level of advanced beginner.
What a novice lacks at the end of such formal training program is the required experience, and time to practice the skills he learned in the training program. Therefore, after the learners finish their training, they are usually assigned to the job or projects where they perform things and learn on the job. Some of these arrangements may have formal on-the-job training while others may have just informal job-shadowing. Employee learns several tasks during this phase at a rate which is determined by a number of cases or issues encountered, time available to practice and opportunities apply and further his skills. During this phase, the learning curve may take all sort of shapes and slopes depending on the person, job, situations, opportunities, and assignments. Steadily, learner acquires proficiency at a rate depicted by ‘conventional on-the-job experience curve’ in figure 2. Depending on the rate of learning on-the-job individuals may reach desired proficiency eventually in time ‘N4’.
This approach suggests focussing solely on the on-the-job experience component of the proficiency curve. If there were some suitable strategies, it might be possible to shift the slope of ‘conventional on-the-job experience curve’ to a slope as in ‘accelerated on-the-job experience curve’. It may be possible to reach desired proficiency in time ‘N4’ which is shorter than time ‘N6’ – thus, accelerating proficiency.
The companies using on-the-job training as the main approach are substantial in number. In one study by Rothwell and Kazanas (1990), it was revealed that 365 of managers believes on-the-job training is an essential part of company’s training strategy but don’t know how to improve it. In a study by Barbian (2002), 77% of the leading companies in Training Magazine’s Top 100 companies offer formal mentoring, 66% have job shadowing programs, and 51% have job rotation programs. Lately, 70:20:10 model emphasized that 70% of the learning happen on the job and hence should be the critical focus of organizations towards accelerating proficiency. See this post which shares application of 70:20:10 model to accelerate proficiency using mostly the on-the-job experience. This may appear to be a common sense approach because most organizations rely on on-the-job experience to build the expertise of their employees.
Increasing number of jobs has shown that on-the-job experience is required to perform the job independently (i.e. proficiently). For example, to demonstrate proficiency to attain a license to fly a jet-powered commercial passenger airplane with a scheduled airline, a pilot needs an average 3000 flight hours of experience on-the-job (which include at least 1,500 hours’ multi-engine, and at least 1000 hours as pilot in command).
Many corporations still use informal or unplanned approach to OJT. As Filipczak (1993, p.30) explains, “OJT has often meant having a new employee ‘go sit by Nellie’ or follow Sam around the factory floor playing monkey-see, monkey-do”. This is a case of unplanned OJT. However, the paradigm has shifted in the last couple of years. Jacobs (2014) revisited a structured OJT (S-OJT) model which takes a system view on skills required by newer staff to perform the job, systematically design shadowing to deliver experiences at the workplace, and checklists to evaluate it. More and more organizations have adopted training approaches such as structured on-the-job training (S-OJT) (Jacobs & Bu_rahmah 2012; Jacobs 2014).
On-the-job learning period is certainly significantly longer than classroom training. Most of the organizations have understood that on-the-job training, learning, and experience are critical to accelerating proficiency of employees. However, there is clear lack of knowledge-base on how to accelerate on-the-job experience. Some of the techniques that are shown promising in the literature are discussed in other posts.
Though “nothing can replace the field experience”, this approach leads to long wait time for right experience to present itself on-the-job to the learner. Hoffman, Andrew, Feltovich (2012) state that “A key factor which makes achieving the status of “expert” difficult is that typically, to be considered an “expert”, an individual must be able to solve very difficult problems that most of their peers are not able to address. A similar equation is applicable to develop a highly proficient employee. However, these types of problems are relatively rare, which makes learning by practice on the job problematic since they are seldom encountered”. Sometimes it may take a really long time before someone is exposed to the events and acquire enough experience to become proficient. This is particularly true for complex problem-solving skills in which proficiency can only be acquired when an individual has acquired the refined schemata and mental representation which is possible only by working on several cases of a wide variety.
Further, it is seen that if organizations rely heavily on on-the-job experience/training as the mechanism to build proficiency, they usually undermine the value of formal training.
Figure 4 shows a ‘conventional classroom training curve’ which represents a block of training which typically happens within a reasonable time frame. Conventional training curriculum has historically used the premise to provide basic skills and knowledge to learners’ and make them learn specific rules of the game on the job. This is indicated as proficiency level P2 in figure 3. However, the traditional training courses tend to provide the novice with rule-based guidelines and structure to give him the ability to apply these facts and figures into different situations and hence by definition trying to exiting him out of training at ‘advanced beginner’ level (See characteristics of advanced beginner above).
Conceptually, one possibility is suggested by this graph to achieve desired proficiency faster. What if training curriculum can be re-structured to uplift the exit proficiency level of the individual from P2 to P3 (i.e. being at ‘advanced beginner’ to at least a ‘competent’ level as per definition of Dreyfus & Dreyfus model (1986) as shown by curve ‘re-structured classroom training’? When we lift up the exit proficiency level of the learner in such a way from ‘advanced beginner’ (P2) to ‘competent’ (P3), then he possesses much-refined knowledge when he exits out of the training. With increased competence, he would start his post-training assignments at a higher starting point of proficiency. The individual is likely to have a head-start for his post-training on-the-job experience. Assuming the same rate of skill acquisition, as was in ‘conventional on-the-job experience curve‘, an individual could achieve ‘desired proficiency’ in time N4, much faster than the original time-to-proficiency N6. This again leads to accelerating time to proficiency, conceptually.
Under this premise, the employee is developed right during the training course to exit at a higher level of proficiency. This proficiency is achieved with a curriculum training structure that enables learners with abilities such as mature information processing, better mental knowledge representation, skills in chunking information, speedy pattern recognition and highly developed metacognitive skills, to a certain extent, which all are characteristics of the expert performer (Dror, 2011). Thus at exit level, the learner is more competent than the learners who are put into the conventional route. The higher competence also means better grasp of knowledge before learner starts his on-the-job journey. According to literature, such pre-existing knowledge makes the learner to approach problems quickly and leverage previous mental representations to achieve expertise or proficiency faster (Chi, Glaser & Farr, 1988). This leads a competent learner to learn at faster rate achieving ‘desired proficiency’ in a shorter time.
Several studies attempted in providing insight into how training can be used to “uplift” the proficiency of employees in a training event or a training program. In one of the previous posts [See Exploring 9 Training Models That Answer The Question: Can Expertise be Accelerated?], an insight was provided about how those famous models answer the question regarding acceleration of proficiency. Some of the instructional design or training models support this approach. Sternberg’s (1990) model of intelligence provides 6 training strategies to accelerate expertise. This model explains that metacognitive skills, learning skills, and thinking skills are most essential ingredients of lifting up the proficiency during training. The job roles are becoming complex now and increasingly requires learners to solve complex problems. To that effect, restructured training approach focuses heavily on developing complex problem skills [see this post 6 Guidelines to Develop Training for Acquiring Complex Problem Solving Skills]. Along similar lines, Dr. Robert Hoffman emphasized [See Accelerated Expertise with Mentoring and Tough Cases: An Expert on Accelerated Expertise Shares] using tough cases to accelerate expertise through well-structured training. Hoffman et al. (2014) specified a range of case studies and past research studies how training should be restructured to accelerate expertise towards high proficiency. Proposing similar stand of tough cases, Dr. Lia DiBello proposed a strategy of simulating rapid failures in a compressed time frame to rapidly accelerate proficiency [See Simulation of Rapidized Failure Cycles: How Does This Powerful Methodology Accelerate Expertise Rapidly?]. In her most recent work, Clark (2008) specified cognitive strategies to build the expertise through training. She presented a range of techniques starting from managing cognitive load to a part-task technique for building expertise, retention and skill practice, etc. Her compilation is one of the recent efforts in proposing range if training strategies drawn from previously well-established research studies as a solution to build a higher level of proficiency through training interventions. In my another post [See 4 Cognitive Training Strategies To Accelerate Expertise of Complex Skills: Revelations by a Cognitive Scientist], Dr. Clark particularly shared 4 cognitive training strategies to accelerate proficiency through training, which included metacognitive expertise, worked examples, whole task approach and challenging assessment.
This is a simple concept how focusing on training intervention has many rewarding effects allowing organizations to build a certain level of proficiency within the training course and attaining desired proficiency faster. However, it is a common belief that classroom training never leads to proficiency, though it can provide initial readiness at the job. Also, the new philosophies like 70:20:10 tend to undermine the value of training. On the other hand, the believers of structure training like 6 Disciplines of Training, warn that initial training is an extremely important piece of the equation for workplace success. Nevertheless, this approach suggests that training intervention needs to be restructured in such a way to build a portion of proficiency right during training. However, it may mean longer training duration than required by traditional models.
While each of the three approaches has some merits, it would be reasonable to think that none of these are perfect. To develop and accelerate proficiency holistically, one has to merge all the three approaches together. The key driving factor would be the analysis of the inventory of skills, knowledge, behaviors, and nature of tasks to be supported in a new job role. Once the inventory to attain desired business goals for the stated role are defined, then it is a matter of proper analysis to understand what skills must be delivered in formal training, what skills/tasks must be performed during the on-the-job experience, what can be supported with tools like performance support systems.
Part of this analysis also would tell what skills are pre-requisites and individuals should either be hired for those skills or they should be provided all the content and other self-learning support that potentially can get them started with some heads-up before they attend a formal training program. Using such a ‘pre-training’ approach, the rate of learning/proficiency acquisition during restructured training could be much higher and this may give an advantage to further accelerate the on-the-job experience curve. This is shown in figure 5. In another post, I described findings of a research study how pre-training using e-learning strategies could provide this head-start. If the amount of “lift” is appropriately supported, it may even be possible for an individual to attain desired proficiency in a time shorter than N4. Further, balancing the classroom training vs. on-the-job interventions, one could accelerate proficiency significantly [See 5 Guidelines to Develop Unconscious Competence and Become Expert].
This post acts as an anchor to introduce this holistic approach. The strategies and practices to implement such holistic approach will be discussed in some of the future posts. Readers are encouraged to read my research paper that describes the concept of total eco-system to accelerate proficiency, the fundamental premise of which is combining all the three approaches together. See my research paper MODEL OF ACCELERATED PROFICIENCY IN THE WORKPLACE: SIX CORE CONCEPTS TO SHORTEN TIME-TO-PROFICIENCY OF EMPLOYEES. Combining various approaches together to accelerate proficiency also means, there cannot be such sharp boundaries between training and on-the-job experience. Both components have to work together. Training intervention needs to be restructured in such a way to build a portion of desired proficiency right during training to uplift the exit level proficiency of employees. On the other hand, organizations need to implement several non-training strategies alongside training strategies, to embed on-the-job experience and formal training together. One needs to come up with different ways to incorporate on-the-job experience in the formal training structure itself or situate training into the day-to-day work on the job. Striking the balance between formal training and on-job-experience in a reasonable period is one of the several central issues in the study of time-to-proficiency. Further, on-the-job experience needs to be designed, monitored and mentored accurately.
In your context, how do you accelerate proficiency? Do share your thoughts.
All the graphs used in this blog are copyright to Raman K. Attri.