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5 E-learning Strategies To Accelerate Time to Proficiency in Complex Cognitive Skills At workplace


E-learning strategies to accelerate time to proficiency in complex cognitive skills

This research study reports 5 powerful e-learning strategies that can accelerate time to proficiency in complex cognitive skills: Experience-rich multi-technology mix, Time-spaced micro-learning content, Scenario-based contextualization, On-demand performance support systems, and Optimally sequenced e-learning path.

Accelerating time to proficiency of the workforce is a crucial business goal. E-learning has made big waves in past one decade. Therefore, it is imperative to investigate contributions or role of e-learning towards accelerating time to proficiency of the workforce, particularly for accelerating complex cognitive skills. On that subject, back in June 2016, I presented a paper titled “E-learning Strategies at Workplace That Support Speed to Proficiency in Complex Skills” at International Conference on E-learning (ICEL), Kuala Lumpur. In that paper, I presented a conceptual model of sub-section of my overall findings related to e-learning theme from my doctorate research (“practices and strategies to accelerate time to proficiency of employees at the workplace”). I will briefly describe that conceptual model and major themes that emerged from my research in this post.

State of e-learning

There is no consensus on what e-learning is and what it is not. e-learning definition changes with endless possibilities every new electronic technology bring for driving learning  (Kahiigi et al., 2008). Long back computer based training was deemed as e-learning while in most recent time virtual reality is considered to be a new face of e-learning. No doubt that e-learning has emerged as one of the most attractive and cost-effective solutions with the flexibility to support self-paced learning which can be delivered geographically to any place on the earth. 2014 survey by Elearningindustry.com reported that over 47% of the Fortune 500 companies now use some form of educational technology and corporations value e-learning as the second most valuable training method which saves business at least 50% cost when they replace traditional classroom training with e-learning (Pappas, 2013). According to ASTD 2014 State of the Industry Report, 38% of the training is delivered using technology-based solutions. The report also cited an IBM report stating that companies employing eLearning have potential to boost productivity by 50%. According to their estimates, every 1$ spent on e-learning results in $30 productivity (ASTD, 2014). However, there is some caveat to these trends. Organizations have not been able to harness the power of e-learning fully beyond one-way informational content. There are some examples of highly interactive e-learning solutions which boast of delivering complex cognitive knowledge and skills in any kind of complex job.

How does e-learning develop complex cognitive skills?

Jobs are becoming increasingly complex in the workplace. A task as simple as ‘calling a customer’ has now become over-complex with considerations like ability to hold the client’s attention, cultural and situational sensitivity to customer’s surroundings, ability to connect and relate with customer’s needs not just in business sense but in socio-cultural sense too, ability to think through options and be able to research certain information for customer. Karoly & Panis (2004) emphasize the changing nature of workplace requires non-routine cognitive skills. Complex cognitive skills require a different kind of design or approach. It is a general belief that face-to-face instructor-led and on-the-job mentored training have proven potential to develop complex skills in the workplace as well as in educational or training provider’s settings.

Some researchers proposed some specific e-learning strategies which have shown some promise to shorten time-to-proficiency in complex skills. For example, the early studies by Gott and Lesgold (2000) in military settings showed that 25 hours of scenario-based simulation on the computer accelerated the expertise of 2 years technicians in diagnosing electrical faults in aircraft as equivalent to those holding 10 years of experience. Towards modern day e-learning, Dror, Schmidt, and O’Connor (2011) advocated an approach of ‘Technology Enhanced Learning’  to facilitate the acquisition of complex cognitive and hands-on skills commonly used in the medical domain using technology to create challenging interactions (p. 293). Another strategy, ‘Problem-based curriculum’ has shown evidence in triggering “active processing” in learners, a key component to accelerate complex skill acquisition (Clark and Mayer, 2011). For example, Hinterberger (2011) used problem-based learning to teach computer science in “digital laboratory” settings to allow learners to acquire skills through the application of software in solving physical problems or phenomenon. On similar lines, Clark and Mayer (2013) advocated that scenario-based e-learning has the potential to accelerate expertise at the workplace by stating that, “Unlike real-world experience, scenario-based e-Learning scenarios not only compress time but also offer a sequence and structure of events designed to guide learning in a controlled manner.” Arnold et al. (2013) demonstrated that a sequence of cases through e-learning resulted in rapid expertise development of highly complex decision-making in novice-level financial professionals. In the recent time, computer-based simulated games (another form of e-learning) has shown great potential in accelerating development of complex knowledge and skills in topics like cell biology, aviation, transportation, military and business management (Higgins, 2015).

However, e-learning’s ability to deliver highly complex cognitive skills have come under scrutiny many times. It appears that it fails to deliver results when designers get into a trap of using principles meant for simpler skills to design e-learning for complex skills. I am sure many of you may have seen that happening. Reality is revealed by Wulf & Shea (2002) in their study who argued that “principles derived from the study of simple skills do not generalize to complex skill learning” (p.185). They further emphasized that complex skills indicate the need to approach the learning of complex and simple skills differently. For example, learning simple skills profits from an ‘increase in load’ whereas the learning of complex skills requires ‘reduction in load’.

Many researchers have even questioned whether or not e-learning is a plausible media to deliver complex cognitive skills. E-learning also gets questioned about its ‘stickiness’ or effectiveness in transferring skills to the workplace, particularly for complex skills. Sims, Burke, Metcalf, & Salas (2008) state that “In fact, a common criticism of e-learning is that face-to-face courses are directly transferred to an electronic format with the assumption that the courses will be equally effective and accepted by trainees.” (p. 24)

The point here is that e-learning targeted to develop highly complex cognitive skills need a different set of strategies. Lately, several researchers have proposed different strategies by which e-learning could be designed or administrated to develop complex skills of the learners. Here are some most common or popular ones:

Can e-learning accelerate time to proficiency?

With the pace of technology, the time-to-market pressures are changing demands on the workforce to acquire these complex skills at a faster pace. Though some of the above strategies or examples indicate that appropriate design could allow e-learning methods to help learner acquire complex skills, however, only a few of the research studies give some evidence or guidelines to design e-learning that could accelerate expertise or time-to-proficiency. Some industry figures substantiate the fact that e-learning holds the potential to accelerate proficiency. According to statistics reported by Pappas (2013) at Elearningindustry.com, e-learning cuts down the instruction time by 60%, increases information retention rates by 60% and compared to classroom learning, e-learning students are reported to have 60% faster learning curve. Though this evidence is mostly commercial in nature based on a limited set of surveys, the value of e-learning technologies, platforms, methods cannot be denied in regards to its ability to cut down training length, allow self-paced learning and reinforcement to traditional training methods (Dongsong, 2005; Clark and Mayer, 2011).

What e-learning strategies have proven to accelerate time to proficiency?

In this study 85 business experts from 7 countries and 42 industries participated in the research. 74 in-depth semi-structured interviews were conducted over the phone and using internet technologies. Participants were asked to provide a detailed account of a project case in which they implemented new strategies or solutions which led to a proven reduction in time to proficiency of employees. The responses corresponding to e-learning related solutions or strategies were extracted and analyzed using thematic analysis. The analysis of the themes revealed following five major e-learning strategies that hold strong potential to accelerate speed to proficiency.

1. Experience-rich and multi-technology mix
2. Time-spaced micro-learning content
3. Scenario-based contextualization of e-learning
4. On-demand electronic performance support systems
5. Optimally sequenced e-learning path

Based on the findings, a conceptual model was developed as shown in the figure. This conceptual model depicts the relationship among five e-learning strategies. A strong relationship between these strategies is seen. The way one strategy is implemented could significantly impact the effectiveness of the other strategies, by supplementing or complementing each other. Such interaction is shown by the bi-directional arrows in Figure 1. We hypothesize that time-to-proficiency of employees can be shortened if organizations develop a shorter chunk of content; contextualize it with real-world problems relevant to the workplace; sequence and organize the chunks in an optimally designed learning path; deliver each chunk virtually or online using several technologies, and making it available through electronic performance systems. Our recommendations are to implement all the 5 e-learning strategies to a certain degree to reap the fruits of accelerated proficiency.


E-learning conceptual model

[Conceptual model of e-learning for accelerated proficiency] 

5 e-learning strategies that support accelerating time to proficiency in the workplace

1. Experience-rich and multi-technology mix

Bower et al. (2015) had earlier predicted that “Ideally in the years to come, rich-media collaborative technologies will become so invisible that students and teachers interacting from different locations will feel as though they are in the same room” (p. 15). The findings in our study confirmed that by providing multiple experience-rich channels of information and content delivery to match learning styles of the diverse workforce, organizations could cut the time to readiness. Several tools and channels of information delivery were used to enrich the learning such as social media, remote presentations, real-time messengers, video portals, online books, peer-to-peer coaching, discussion forums, project work or fieldwork, etc. Latest technologies (like CISCO Telepresence, Google Hangout or YouTube streaming) offered powerful interactions virtually, rich experience and multiple channels of learning. In an earlier study, Sims, Burke, Metcalf, & Salas (2008) suggested blending several channels together “….a blended learning approach may be more effective than a training session that relies completely on one mode or strategy.” (p. 26). These channels extended interactions beyond instructor to the peers and others. Collectively, multiple channels provided several learning routes to employees, cutting overall time-to-proficiency significantly. Several participants mentioned that lending newer e-learning technologies can enrich virtual training sessions that allow multi-sensory interaction with the content and caters to different preferences and requirements of the learners. “….whereby using technology and making a combination of virtual and live classes…….has allowed it [accelerated learning] to scale more efficiently and happen in a faster time frame.” 


Experience-rich Multi-channel technologies

[Slide copyrights Raman K. Attri] 

2. Time-spaced micro-learning content

Data analysis shows that technology-driven virtual training sessions become more effective when those were split into shorter sessions, with each session focused on few learning outcomes at a time. Participants called this approach as ‘chunking’ or ‘segmenting’ or ‘microlearning’ or ‘bite-sized learning’. The chunking worked well when it was spaced over time. “…..So, one of the challenges that we confronted and resolved was why we don’t break down the eight-week course into what we call micro-learning courses.”  The spaced shorter sessions allowed appropriate reflection and practice required to learn a complex skill. Some of the benefits mentioned were: delivers learning in short chunks, reduces the cognitive load of a complex skill, gives a sense of achievement, provides the time needed to practice the complex skill, allows an opportunity to reflect, to cite a few. Such short chunked sessions have become important for e-learning modules as studies have shown that the attention spans of people have been reduced over the years, from 12 seconds in the year 2000 to 8 seconds in the year 2013 (Grovo, n.d.)These observations are supportive of other research studies. In a most recent study, van der Meer et al. (2015) reported that when a traditional lecture was replaced with bite-sized videos, over 45% of the students found learning useful and preferred this method. The second part of this strategy really is spacing the chunked sessions in time which provides the reinforcement or boost to the learners at regular intervals and therefore leads to better retention of skill or knowledge being learned as noted by several researchers (Birnbaum et al., 2013). The shorter e-learning sessions spaced out in time are not only effective but also could be a strategy to accelerate speed to proficiency.


Time-spaced microlearning

[Slide copyrights Raman K Attri – embedded image credits Grovo] 

3. Scenario-based contextualization of e-learning

The study findings showed that designing e-learning around real-job challenges could accelerate proficiency in highly complex skills. Such methods enabled students to solve real-world problems as opposed to memorizing abstract concepts and to trigger higher-order thinking. “…if they apply that knowledge in the case [scenario], then they are more likely to remember because they are actively using their knowledge and secondly and most importantly, it’s now tied to [the] context of use, so it’s more likely to be remembered and applied later on [at workplace].”  Some method cited by participants included {case based curriculum}, {problem-based e-learning}, {scenario-based simulation}, {simulated scenarios}, {gaming or gamification}, {strategic rehearsal} and variations thereof. Adding intentional or planned errors or bugs in the scenarios led to active involvement of learners and triggered deeper thinking when teaching complex skills. “that is letting students [to] struggle with something, try to solve something where  their chances are very low of succeeding and then when they get instructions on the material, they more than make up that time in terms of how well and how permanently they learn.” Thus, incorporating failures into learning added certain pressures and generated emotional involvement which in turn appeared to accelerate the speed toward proficiency. “… And those higher levels of emotional response are very, very key to embed the learning..…in fact emotions play a huge role in how we learn…” The emotional loading experienced by learners while solving real-life scenarios also helped in accelerating proficiency.  Real-life scenarios appear to trigger emotional loading and involvement in learners due to immediate relevance to the job and the consequences thereof. It is noted from previous research studies that emotional involvement and loading plays a big role in the effectiveness of online learning (Schuwirth, 2013). A similar observation was noted by DiBello, Missildine and Struttman (2009), Bjork (2013) and Clark and Mayer (2013) who confirmed that e-learning sessions designed using scenarios particularly by incorporating intentional failures may shorten the time-to-proficiency in complex skill.

In previous studies on these lines, Clark and Mayer (2013) introduced that if e-learning is designed around scenarios it enhances cognitively complex learning. Scenarios could be real cases or fabricated cases from real-life. The short or large scenarios employ the power of storytelling and bringing context in play. This simple term ‘scenario’ refers to various variations of problem-based e-learning, case-based e-learning, gamification of scenarios, simulated cases, and virtual reality-based games. Clark and Mayer (2013) advocated that scenario-based e-learning holds the potential to accelerate the expertise. They emphasize the use and importance of scenarios that: “By working through a series of job scenarios that could take months or years to complete in the work environment, the experience is compressed. In essence, scenario-based e-Learning is job experience in a box – designed to be unpackaged and stored in the learner’s memory. Unlike real-world experience, scenario-based e-Learning scenarios not only compress time but also offer a sequence and structure of events designed to guide learning in a controlled manner.”

Scenarios also trigger active learning in which learners are fully involved. Clark and Mayer (2011) specified eight strategies to develop effective e-learning, the most important one in the context of complex learning being ‘active processing’ suggested by 11 studies they analyzed. They stated that “People learn by actively processing information, which includes constructing mental models of learned information. Including relevant graphics is a powerful way to aid with active information processing.” (p. 65).  Dror, Schmidt, & O’connor (2011) introduced the strategies on ‘Technology Enhanced Learning (TEL)’ to facilitate the acquisition of complex cognitive and hands-on skills such as used in the medical domain through e-learning.  They argue that: “An effective way of achieving this is through challenging interactions that require the learners to take an active role in the training and learning experience. Technology can be a great tool in achieving this kind of training.” (p. 293).

Hinterberger (2011) demonstrated problem-based learning as a strategy to teach complex computer science skills in ‘digital laboratory’ settings to acquire skills which require the application of software in solving physical problems or phenomenon. Gamification has emerged as one of the recent advances in e-learning strongly believed to build and accelerate the experience in complex skills which otherwise are hard to encounter in real-life or are not feasible to simulate or practice in real-life (Higgins, 2015). For example, developing or accelerating skills of firemen to fight with fire in a real fire incident or accelerating skills of underground miners to respond to emergency protocols in the event of the fire. Such situations may require higher order complex cognitive skills like problem-solving, decision making or troubleshooting (Slootmaker, Kurvers, Hummel, & Koper, 2014). Use of simulated games is one of the highly talked about e-learning strategy holding potential to accelerate proficiency. In a research study, Sitzmann (2011) reported 20% higher confidence of learners after using computer-based simulation games, compared to classroom instruction which resulted in a higher transfer of knowledge and skills to the workplace. Dror, Schmidt, & O’connor (2011) highlighted the value of gaming as an e-learning strategy in complex skills training by stating that “Another element in which gaming can be an efficient technological tool is in training how to cope with unexpected events.” (p.294).


Scenario-based contextualization

[Slide copyright Raman K. Attri – embedded image credits: Bernardo Pina @ Produzindo.net]

4. On-demand electronic performance support systems

Another theme that was observed in this study was that organizations deployed more electronic performance support systems (EPSS) in place of or in augmentation of training. EPSS included mostly the electronics resources like online learning content, reference material, knowledge-base, procedures, mobile applications, decision-making software, etc. which according to participants can provide just-in-time training or just-in-time support. “Organizational learning moves from being a training event to which employees need to be invited, to something that happens automatically as employees seek assistance on-the-job from EPSS.” It was suggested that by taking the content out from instructor-led sessions and making it accessible through EPSS as self-paced learning activities to prepare the learners. “…So we will take the content out or that informational content and we’ll make it available so that people have access to that before they come to a course……” By doing so employees accessed the resources at their own pace, rather than at the pace of the instructor which significantly cut the time from proficiency cycle. This not only made good use of learner’s time while waiting for the instructor-led session, but it also allowed the formal training intervention to focus more on critical and complex hands-on skills.

Another finding of this research indicates that learners gained proficiency in content faster when they used or accessed content based on the need of the task at hand. So a conscious effort to remove unnecessary informational content from the training modules led to a shorter training time. However, the real value was making it available to learners through electronics performance support system (EPSS), another powerful e-learning strategy.

Such strategies are supported by previous research studies as well. While Gery (1991) advocates providing individualized online access to novices using EPSS instead of the information content-heavy training upfront, Nguyen (2006) points out that as one progresses from novice to expert, as training interventions go down, there should be an increase in the use of EPSS. While there is plenty of literature and research on EPSS, the present study provides grounds that appropriately designed EPSS could allow learner attain proficiency in several complex skills in a shorter time while doing their job and using EPSS. Arnold et al. (2013) demonstrated that an e-learning system designed around an expert system and case-based e-learning accelerated the expertise of new financial analysts providing highly complex decision making to business corporations.


On-demand Electronic Performance Support Systems

[Slide copyright Raman K. Attri]


5. Optimally sequenced e-learning path

Data analysis revealed that time-to-proficiency is significantly impacted by carefully sequencing the learning activities, tasks or assignments in a very efficient path, called ‘learning path’ or ‘learning pathway’. The essence of the strategy is “so the idea then is if you sequence those activities [….] over a period of time, you can pull together a whole sequence of activities and in effect what you’re doing is not waiting for the universe to provide them.” In the context of e-learning, activities included online courses, use of electronic resources, practice on PSS, other knowledge tools and range of other e-learning activities which when sequenced optimally is termed as e-learning path. The sequencing was made optimal by using some criteria like frequency of occurrence of the task (very frequent to rare), usage of the knowledge or skill (very often to hardly), the complexity of the task (simple to complex) and difficulty level of the problem (very simple to very hard).  It is also found that when business criteria like frequency, complexity difficulty of the task were used with the goal of attaining proficiency faster to sequences the e-learning modules, resources, activities and microlearning sessions, the result was an efficient and lean learning path. As noted in another publication, such sequencing in a ‘learning path’ played a pivotal role to reduce the time the learner takes to reach targeted proficiency (Attri and Wu, 2015a).

Participants said, “…if you can set up a way, a very systematic set of cases, a systematic set of experiences and organize those [cases] then you could speed up that process [of proficiency acquisition] because you need to have those experiences.” Further, by assigning time targets to each activity including online and e-learning activities the total time-to-proficiency could be estimated and tracked and then focused efforts could be made to shorten the time.  Previously, in the context of the complex jobs, Darrah (1996) showed the use of a sequence of organized activities in a computer manufacturing company while Hutchins and Palen (1997) explains it for a flight engineer’s role. This was seen an influential strategy towards accelerated proficiency.


Optimally sequenced e-learning path

[Slide copyright Raman K. Attri- embedded image credits: SecurityCompass and Learning Masters Blog]


Mindmap of Summary of E-learning Techniques

Key techniques I explained under each strategy is summarized in the mind map below.


e-learning strategies mindmap

[Copyright Raman K. Attri]


Interested readers can read the original research paper here: https://www.researchgate.net/publication/303802961.

To implement these strategies, an instructional design framework based on 4-phases of the proficiency acquisition cycle is discussed in another post: 9 Promising E-learning Curriculum Design Methods from Research To Accelerate Proficiency. 


  1. Attri, RK & Wu, W 2016, “E-learning strategies at workplace that support speed to proficiency in complex skills”, In M Rozhan and N Zainuddin (ed.), Proceedings of the 11th International Conference on E-Learning: ICEL2016, Kula Lumpur, 2-3 June, Academic Conference and Publishing, Reading, pp. 176–184, viewed 24 June 2017, https://www.researchgate.net/publication/303802961.
  2. Attri, RK (2018), ‘What is the meaning of Accelerating Speed To Proficiency or Accelerating Time to Proficiency?’, [Blog post], Speed To Proficiency Research: S2PRo©, Available online at <https://www.speedtoproficiency.com/blog/e-learning-strategies-accelerate-time-to-proficiency/>.

protected for plagiarism


  1. Arnold, V., & Collier, P. (2013). INCASE: Simulating Experience to Accelerate Expertise Development by Knowledge Workers. Intelligent Systems in Accounting and Financial Management, 20 (1), 1–21. https://www.researchgate.net/profile/Andrew_Vincent3/publication/236345885
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  3. Attri, R. K. & Wu, W. S. (2015). E-Learning Strategies to Accelerate Time-to-Proficiency in Acquiring Complex Skills: Preliminary Findings. Paper presented at E-learning Forum Asia Conference, Jun 2015. Singapore: SIM University.  Available from https://www.researchgate.net/publication/282647943.
  4. Birnbaum, M.S., Kornell, N., Bjork, E. L. and Bjork, R. A. (2013) Why interleaving enhances inductive learning: the roles of discrimination and retrieval. Memory & cognition [online]. 41(3), 392—402.  Available from https://dx.doi.org/10.3758/s13421-012-0272-7 and http://sites.williams.edu/nk2/files/2011/08/Birnbaum.Kornell.Bjork_.Bjork_.20131.pdf.
  5. Bower, M, Dalgarno, B, Kennedy, GE, Lee, MJ & Kenney, J. (2015). Design and implementation factors in blended synchronous learning environments: outcomes from a cross-case analysis. Computers \& Education, 86 (8), 1–17, http://linkinghub.elsevier.com/retrieve/pii/S0360131515000755.
  6. Clark, R. C., & Mayer, R. E. (2011). E-Learning and the science of instruction: proven guidelines for consumers and designers of multimedia learning (3rd ed.). San Francisco, CA: Jossey-Bass Inc., U.S. https://dx.doi.org/10.1002/9781118255971.
  7. Clark, R. C., & Mayer, R. E. (2013). Scenario-based e-learning: evidence-based guidelines for online workforce learning (1st ed.). United States: Wiley, John & Sons.
  8. Darrah, C. N. (1996) Learning and Work: An Exploration in Industrial Ethnography. New York, NY: Garland Publishing.
  9. DiBello, L., Missildine, W. and Struttman, M. (2009). Intuitive expertise and empowerment: the long-term impact of simulation training on changing accountabilities in a biotech firm. Mind, Culture, and Activity, 16(1), 11–31. Available from https://dx.doi.org/10.1080/10749030802363863 and http://wtri.com/wp-content/uploads/2015/06/Intuitive-Expertise-and-Empowerment1.pdf
  10. Dror, I., Schmidt, P., & O’connor, L. (2011). A cognitive perspective on technology enhanced learning in medical training: great opportunities, pitfalls and challenges. Medical Teacher, 33(4), 291–6. https://www.academia.edu/15432383/A_cognitive_perspective_on_technology_enhanced_learning_in_medical_training_Great_opportunities_pitfalls_and_challenges
  11. Dongsong Zhang (2005). Interactive Multimedia-Based E-Learning: A Study of Effectiveness. American Journal of Distance Education. 19(3), 149-162. http://www.anitacrawley.net/Resources/Articles/Interactive%20Multimedia-Based.pdf
  12. Gott, S. P., & Lesgold, A. M. (2000). ‘Competence in the Workplace: How Cognitive Performance Models and Situated Instruction Can Accelerate Skill Acquisition’, in R. Glaser (Ed.), Advances in instructional psychology, Erlbaum, Hillsdale NJ.
  13. Higgins, N. (2015). Gamification: Accelerating Learning (pp. 1–12). Kingston, Australia: KBR Training Solutions. Retrieved from https://kbrtrainingsolutions.com/
  14. Hinterberger, H. (2010). Problem-based E-Learning in Practice : Digital Laboratories Provide Pathways from E-Science to High Schools, in C Ho and M Lin (ed.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Association for the Advancement of Computing in Education (AACE), Chesapeake, pp. 1947–1954. http://www.editlib.org/p/39013/
  15. Gery, G. (1991) Electronic performance support systems. Tolland, MA: Gery Associates.
  16. Grovo. (n.d.) Bite size is the right size. Available from http://a1.grovo.com/asset/whitepapers/Grovo-BiteSize-Microlearning-whitepaper.pdf

A version of this post was originally published on Jun 6, 2015

Header image credits: Pixabay CC0 attribution

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Dr Raman K Attri

Hi!! I am Raman…

I am a performance scientist and a corporate learning leader working, writing, researching and speaking on speeding up learning, performance, expertise, and leadership. Follow me to the world of learning for the accelerated world.

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