In this research-based article, an instructional design model and 9 most promising e-learning methods are described which can be used to design a curriculum to accelerate proficiency at the workplace.
In a previous post ‘5 E-learning Strategies To Accelerate Time to Proficiency in Complex Cognitive Skills At workplace‘, I summarized 5 e-learning strategies to accelerate speed to proficiency of employees, particularly in learning complex cognitive skills from a research paper published I published in ICEL’2016 conference (here is the link to the research paper). While that post established a conceptual model of e-learning strategies which are shown to accelerate proficiency. However, designing a full start-to-end curriculum using those strategies require more guidance not fully covered in that post. This article will describe an instructional design model about how to put together a curriculum that is fully geared towards accelerating speed to proficiency. Then I will describe 9 most promising viewpoints or methods to implement 5 e-learning strategies discussed in the previous post and provide general guidance on how to develop curriculum using such methods.
The previous post explained all the 5 e-learning strategies in detail. The conceptual model described in that post is reconstructed with a meta question that is asked at each node to guide the instructional design. The 5 e-learning strategies are tied to each other in a closed loop and interact with each other seamlessly to accelerate proficiency in an integrated fashion. An e-learning curriculum would result in accelerated proficiency only of all of the 5 e-learning strategies are woven together. Here is the quick list of e-learning strategy and its corresponding meta question and is shown in Figure 1:
Acquisition of desired proficiency to do a job is explained here with a typical case and may not always be the rule for every job or every role. A typical journey of acquiring and maintaining proficiency in new job/role/skills is depicted as four phases by green solid lines in figure 2.
Phase1: Pre-instructor-led training (Pre-ILT) phase: In a typical scenario, at the workplace, a new hire is brought into the organization at time N0 with some base proficiency P0 (let’s assume) for the job. He is provided some on-boarding orientation. During this orientation, the new hire typically would read or undergo some organizational processes and not in particular about the job. Technically, the new hires are not learning specific skills of their job. There tends to be a “bench time” which may vary from one job to another. This bench period is from N0 to N1. This phase is termed as pre-instructor-led training (Pre-ILT) phase in the figure.
Phase 2: Instructor-led training (ILT) phase: Most technical organizations have job-specific training that is offered to the new employees. In most cases, this training is instructor-led/classroom-based training specific to imparting product knowledge, specific skills to do the job function and processing that are used during that job role. Usually, this period from N1 to N2 may be spread into multiple instructor-led training sessions, depending on nature of the job. Typically, a new employee could see a small uplift in his proficiency to do the new job to a level P1. This phase is termed as Instructor-led training (ILT) phase in the figure.
Phase 3: Post-ILT on-the-job learning phase: From there on, they are on the job, performing various activities with someone or independently. Some organizations tend to have parallel mentoring, coaching or on-the-job training to provide an individual more experience to do the job. With repeated assignments and involvement in various activities, an individual may learn at a certain rate and eventually reaches desired proficiency P3 defined for the job in time interval N6-N2. The total time, N6, taken by an individual to reach desired proficiency, called time to proficiency, may be very long depending on several factors. This phase is termed as Post-ILT on-the-job learning phase.
Phase 4: Sustain and maintain phase: If the individual is continuously engaged in job-specific assignments at a higher rate, he would maintain that level of proficiency. This is termed as sustain and maintain phase in the figure.
Now if the goal is to shorten this time to proficiency and accelerate the proficiency, then certain new strategies must be applied. Conceptually, there are three possibilities to achieve shorter time to proficiency if an individual is made to follow the path depicted by red dotted lines:
In particular, this post deals with how e-learning can be applied to shorten this time to proficiency. In a previous post, 5 e-learning strategies to do so were described. In one of my early research papers (see the link to E-Learning Strategies to Accelerate Time-to-Proficiency in Acquiring Complex Skills), I presented an investigation on a range of e-learning methods which have great promise towards implementing these 5 e-learning strategies. These methods likely to enable designers with more definitive guidance to develop a curriculum which could accelerate proficiency of learners. There is multiple evidence from various research studies supporting these methods. However, this post will attempt to explain the methods towards an efficient course design. The 5 e-learning strategies found during new research study are broken further into 9 methods which have been found very promising to implement these strategies.
Optimally Sequenced e-Learning Path:
Experience-rich Multi-Technology Mix:
Scenario-based contextualization of e-learning:
Time-Spaced Micro-Learning Content:
On-demand Electronics PSS:
From various research studies as well as results of my preliminary research findings, these 9 methods appear to align with 4 phases of proficiency acquisition as shown in figure 3. Some methods are more appropriate to implement right in the beginning during Pre-instructor-led training (Pre-ILT) phase, some are more important during ILT phase. Some methods are universal or global enough that those should be applied through all the four phases while some others have application and effectiveness only during Post-ILT phase. The figure depicts atypical suite of recommendations in regards to what methods are most appropriate in each phase. In any case, this a recommendation for more efficient curriculum. Some situation may demand methods like microlearning right from pre-ILT phase. The 9 methods are listed below:
As the first step well before learner’s training start, learning path should be designed. The concept of learning path is to eliminate redundant, irrelevant or wasteful activities in learning path by selecting most essential and relevant learning activities (e-learning or otherwise) required for a stated proficiency goal and then sequencing those through readily available resources and avenues (e-learning modules or otherwise) to achieve that goal in shortest possible time. The learning sequence I suggest here is not same as what the most academic literature portrays i.e. individualized or personalized learning path of a learner in reference to learning the material rather than gaining the proficiency. Williams and Rosenbaum (2004) demonstrate the use of learning path concept in many commercial settings. By approaching the sequence from a learner’s proficiency angle, a designer could map available e-learning modules in a path in optimal order of activities that shorten the time-to-proficiency.
When learners are provided with a head-start based on their prior learning, current skill assessment, and other experience; it could accelerate time-to-proficiency. A systematic profiling of learners needs to be done using smart technologies and such a profiling (or assessment) can be used to build an adaptive learning path to collectively shorten the journey to proficiency. A classic example of this strategy is Pearson Education’s MyITlab online e-learning system which performs an initial assessment on the learner and allows different ‘adaptive’ entry and exit points depending on current skills, knowledge or experience. Further, it conducts continuous assessment tied to learning outcomes and based on results dynamically select activities or modules in the learning path (Pearson Education, n.d.).
Though the blended model is not a new finding, it appears that leveraging blended e-learning based pre-work and homework strategically to supplement ILT sessions during pre-training and during ILT phase could accelerate time-to-proficiency. One of the approaches could be to design low complexity skills including informational content as a pre-training course to give head-start to learners. Then multiple e-learning modules are designed covering medium complexity skills as a bridge between consecutive ILT sessions. Highly complex skills are covered during ILT sessions which are spread over time. Self-guided homework assignments are designed to cover highly complex skills which require deeper thinking and reflection. Such reflective practices are considered to accelerate the skill transfer. E-learning path could be designed to put all the available modules in right sequence. Literature support effectiveness of blended learning approach (Sims et al., 2008). However, it appears that effectiveness of blended approach can be further enhanced when sequencing blended modules and ILT sessions in form of adaptive e-learning path. Also, the well-designed blended learning modules set up as pre-work in pre-training phase is instrumental to lift up the entry-level proficiency of learners into the formal ILT sessions.
As per Eades (2014), “Microlearning is a way of teaching and delivering content to learners in small, very specific bursts. The learners are in control of what and when they’re learning.” Some studies indicate that when traditional sessions are broken into microlearning sessions, it improves retention and far transfer (Hug, 2005, 2006; Lingg, 2014; Clark and Mayer, 2011; van der Meer et al., 2015). Blended e-learning sessions could be broken into microlearning. The short, quick, on-the-job instructor-facilitated sessions or short videos of not more than 4 minutes or so targeting one learning outcome at a time could effectively drive retention and absorption and hence speed to proficiency. This is based on research that attention span of people is reducing from 12 seconds in 2000 to 8 seconds in 2013 (Grovo, n.d.). Each learning outcome can be designed as a microlearning session and sequenced in an e-learning path to help learners progress in their proficiency in quick short steps. Typically each microlearning video or session is designed around one learning outcome, it is possible to leverage e-learning path approach to sequence the sessions by learning outcomes towards the desired proficiency during pre-training, during ILT, and during on-the-job learning phase to support the learners.
Several studies suggested that time-to-proficiency gets accelerated if learning happens in the context of the actual job or learning is contextualized. ‘Contextualization’ is to link the task at hand to the realist job environment and realistic challenges (Clark & Mayer, 2013). Cases or scenarios provide a rich context for learning. ‘Scenario’ refers to various variations of problems, cases, games, simulation, virtual reality etc. Some of the plausible ways to build a context in e-learning are to drive learners to analyze a real-life scenario; solve the stated problem; describe the root cause; recommend a solution; make a decision, or explore an option, etc. This contextualization approach is highly supported and advocated by leading researchers strengthening the preliminary findings (Lesgold, Lajole, Bunzo, & Eggan, 1988; Hinterberger, 2010; Dror et al., 2011; Sitzmann, 2011; Clark and Mayer; 2013; Higgins, 2015). Among all, Gott & Lesgold (2000) and Clark and Mayer (2013) established that various methods of real-life contextualization like scenario-based, simulation-based, case-based or problem-based e-learning and gaming or gamification could accelerate the expertise. Further, Arnold et al. (2013) demonstrated that using case-based contextualized approach, cases could be profiled based on complexity and skill levels and sequenced to reach to desire proficiency goal. This can be argued that adaptive e-learning path approach could be applied here to further accelerate the speed to proficiency. In general, the blended e-learning modules could be designed using scenarios or simulations to build the context in learning.
Higher order complex cognitive skills are typically non-linear in nature i.e. the problem space and approaches could be fuzzy and structured rules may not be applicable all the time. Hence one-way static e-learning may not work effectively. Several studies emphasize active participation as key to accelerating learning in complex skill acquisition. The studies have emphasized different elements of this strategies viz. learning by doing, learning through active processing and learning through active participation, non-linear thinking and decision-making etc. (Dror et al., 2011; Clark and Mayer, 2011). Further, there are some compelling evidence from research that active involvement and non-linear thinking strategy accelerates proficiency in traditional face-to-face settings (e.g. Fadde & Klein, 2012; Hinterberger, 2010; Klein, Hintze, & Saab, 2013; Phillips, Klein, & Sieck, 2004). This appears to be applicable to e-learning settings too. Using appropriate contextual methods like simulation or scenario-based approaches, it is possible to implement a strategy of active involvement and non-linear thinking through e-learning very effectively. Contextualized scenario-based learning strategy in various forms is basically a problem-solving process which drives learner’s active involvement in the learning and triggers the deeper non-linear thinking as well.
Today’s workplace challenges and consequences of quality of a task drive emotions in each task assigned to an individual because there are stakes involved in doing each task. This appears to impact their speed-to-proficiency at the workplace. Preliminary findings suggest that same kind of emotional involvement, emotional stakes or reactions in the learning sense of ‘what is on the line’ to accelerate time-to-proficiency. Far transfer & time-to-proficiency appears to have some link with emotional involvement and stakes during learning. Historically and traditionally ‘emotions’ have been kept out of so-called ‘dry and formal’ education system. Emotional involvement is an underrepresented area but several researchers have recognized the role of emotions in online learning (Dirkx; Hara & Kling, 2000; Shen, Wang, & Shen, 2009; Värlander, 2008). Most recently Trigwell, Ellis, & Han (2012) and (Schuwirth, 2013) demonstrated some positive relationship between emotions and learning effectiveness. Various studies provide some guidance on adding desirable errors (Bjork & Linn, 2006; Bjork, 2013) and rapid failure cycles in compressed time (DiBello, Missildine, & Struttman, 2009) which not only keep learners emotionally involved but also add stakes in the learning by integrating time pressure. If emotional involvement and stakes are designed properly in the e-learning modules using strategies of contextualization and rapid failure cycles, it could lead to an acceleration in time-to-proficiency.
CognitiveAdvisors (n.d) cites Elliott Masie defining nano-coaching as very short burst support, supported by mobile technology, enables frequent, short, targeted, asynchronous coaching interactions, and makes it easy for managers (or peers, or network of coaches or experts) to give timely feedback that supports employees job performance. This method of nano-coaching has the potential to accelerate skill acquisition by providing learners with the coaching in a timely fashion from ‘network of coaches’ at the ‘moment of need’ without having to browse through the piles of information. This allows the learner to reach out to experts or peers in no time. During any problem-solving process, continuous mentoring and coaching are warranted to help learner cross the hurdle with proper guidance. Recent publications have shown a good potential of mobile devices in providing just-in-time learning and nano-coaching (Bolton, 1999, Quinn, 2011). Since contextualized approaches use real-world settings to drive learning and that’s where a learner needs support, coaching and mentoring, it appears that both of these strategies could complement each other. Further, nano-coaching could leverage social interactivity strategies which prompt learning by doing and interacting with others. Nano-coaching opens up an additional channel for meaningful and purposeful interconnectivity.
Several training experts cited that acquisition of complex skills and knowledge gets accelerated by learning by doing with each other, discussions, conversations with peers and asking questions from experts (and even from peers). People learn faster from each other by doing with each other. In order to leverage this finding, design e-learning system which allows learners to connect and interact with anyone and everyone. A typical e-learning system may have some static offline interactions like discussion boards, blogging, commenting etc. but real-time and instant interactions at the moment of need are critical elements. An e-learning platform may leverage ‘social networking’ platforms but the focus is on ‘learning by socializing’ and ‘learning by connecting’. Such a system drives interactions and connectivity by learning outcomes.
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