Accelerated Expertise

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Practice and Feedback

It is generally held in the learning literature that distributed practice leads to better learning than massed practice.

A number of researchers have found that randomized practice schedules that make practice more difficult during acquisition (i.e., random practice) delay the rate of acquisition of each task but increase learning in subsequent tests of retention.

When learning a skill that is knowledge or reasoning-intensive, the learner benefits from having the time to think back on their poor performance and cogitate on what was done right, what was done wrong, and what might be done differently in the future. Immediate outcome feedback can prevent such post-task cogitation and thus not contribute to an increase in proficiency or the improvement of metacognitive skills (thinking about one’s own reasoning strategies).

While feedback is able to guide the learner toward the correct behavior, it can also inhibit performance in the long run in other ways (Schmidt, 1991). If feedback is too frequent, it blocks important information processing activities. Furthermore, if there is too much feedback, it becomes part of the task itself, and no longer serves the function of reflection and organization of information.

Type 2 domains are ones in which the principal task goals involve predicting individual or aggregate human behavior (Shanteau, 1992), but they are also domains in which feedback is minimal to non-existent, or is often significantly delayed. Domain-dependence is a very important consideration for any training program aimed at accelerating the achievement of proficiency.

Experts learn more from their mistakes than from what they get right.

domain specialists who are intrinsically motivated often seek out corrective feedback that allows them to perceive their errors

The more highly experienced and motivated domain practitioners seek feedback from coworkers. When everything works the way it is supposed to, one is less likely to receive feedback about what did not work or what might have been done better. As such, experts seek out corrective feedback, feedback pointing out targets for improvement. Cognitive Flexibility/Transformation Theory (see Chapter 11) suggests that feedback should help the learner transcend the inclination to invoke a knowledge shield (i.e., rationalize away a misunderstanding), and un-learn concepts or notions that incorrectly simplify their understanding of the domain.

It is possible for feedback to be continuous. That is, the learning environment provides continual displays of performance indicators. This is called “dynamic assessment.”

Lack of feedback is argued to be the reason that it is hard to qualify professionals in some domains (e.g., clinical psychologists) as experts.

In terms of learning, a number of authors have elaborated on the idea of pushing the boundaries of the proximal zone of development (Vygotsky, 1978)—in other words, developing training and practice regimens aimed at reaching a level of performance just beyond that which is currently attainable (see Ericsson, Whyte & Ward, 2007). When operating at these boundaries of performance, the probability of failure inevitably increases. Counter-intuitively, error-laden training is very characteristic of the most expert performers in their field.

They serve as ways to explore the coordination space and as feedback that helps identify and isolate specific aspects of one’s knowledge, skills, strategies and mental models that need adjustment and/or refinement. As individuals progress through stages of development they typically become better at detecting and correcting their own errors and developing metacognitive strategies for monitoring their own performance (Ericsson & Ward, 2007; Schmidt & Bjork, 1992) and so error-related information plays a central role in improving performance further.

Accelerated Learning in Business

A general theme in the field of knowledge management is that learning on the part of corporate employees might be accelerated through social networking. One reason is that information sharing is believed to help in the prevention of decision errors

Social networks derived by sociometric analysis (who talks to whom, who shares information with whom, who asks questions of whom) can show where the corporate knowledge and expertise lies within the organization

There is ample evidence that social networking tools and capabilities (blogs, Facebook, Twitter, etc) can help people escape organizational bottlenecks and can rapidly connect people with common interests and problems.

Though this is all plausible, the benefits are anecdotal and there is a paucity of research demonstrating actual “learning acceleration” other than collections of organizational success stories that show business success (i.e., “the efforts paid off…”) but not actual learning.

reasoning relies heavily on the understanding of high-level goals and context. Training that focuses on those should engage workers’ knowledge and skill.

Challenging the workers invokes their tacit knowledge, and the need for teamwork forces the workers to express and communicate tacit knowledge. This method conforms to the notion of developing expertise through working through years of “tough problems.” The fundamental mechanism is the same; i.e., developing deeper mental models of the domain through trial and error cycles of experience.

Demonstrations of Accelerated Learning Using Decision-Making Exercises

The DMX trainer provides information about a critical event, asks the candidate to make a prediction about some unifying variable, shows the actual data, and then continues requesting predictions and providing feedback as the scenario unfolds. The issue is not whether the person can generate an accurate prediction from the start. Rather, the issue is how quickly the person improves. The best people will revise their mental models to improve their predictive accuracy based on what they can learn.

Trainees are presented scenarios that consisted of a map or diagram plus a one-page description of events thus far, unexpected continuations, and the challenge to forge a decision on the spot. These exercises are intended to be played in groups, with a facilitator, but they can also be played on an individual basis. As the participants walk through the re-creation of a tough-case decision situation, they can be fed information as needed, or as it would unfold in actual situations (but time-compressed). Note that these exercises differ from decision-making games in that there is no single best or good solution. Rather, the participants must navigate through trade-offs. While not having single “best” answers, exercises can be formed on the model of the simple game. In this form the decision exercises are easy to play, can be played fairly quickly, are technologically simple, have simple rules, are flexible and adaptable, and are very transportable—they should be capable of being played in a lunchroom or during travel layovers. Each exercise is simple because it focuses on only one or a few particular key concepts, principles, or lessons learned.

Exercises come from personal experiences, which are described as narratives. Exercises are formed around specific experiences and their context. Exercises are not based on general or typical situations. “We need context in order to exercise our intuition.”

For developing instructional cases, domain practitioners are generally able to identify and recall previously encountered tough cases. In addition, managers can often see where staff members repeatedly struggle with some type of judgment or decision. Both the practitioner and the manager can recount personal experiences. From these, one can create a timeline for the described event, and for each key decision in the event, a list of the information requirements of the decision maker.

Decision exercises have the following components: (1) Background information describing and perhaps explaining the current situation and its origins; (2) A narrative description of the scenario itself, taking the form of a compelling story that builds to a climax—a dilemma—putting the participants on the hot seat, forcing them to make a decision to resolve the situation; (3) Some sort of visual representation that accompanies the narrative (diagram, map, etc).

Team exercises often involve an energetic exchange of opinions. The actual decision is less important than the thinking that goes into it. The decision exercise is a vehicle for triggering the decision-making process and then allowing individuals to reflect on it or discuss it with others. Exercises can be used to build a familiarity and mutual understanding within a team, so team members know more about how others are likely to react to certain types of situations.

Having the decision games center around real issues meant that the decision games were directly relevant to their work and provided a way to make sense of problems that were troubling them. They even decided they could bring the games to upper management to help them articulate their frustrations.

Klein (2004) claims that Decision-Making Exercises can help individuals broaden and enrich their mental models; establish relationships among concepts and cases; appreciate the importance of critical cues and patterns; fill in the gaps in their experience base; learn ways to better handle uncertainty; practice resolving conflicting goals; learn how to spot leverage points for constructing new options; learn how to detect and anticipate problems; understand situations from alternative perspectives; practice allocating limited resources; acquire technical knowledge more quickly by putting it in a practical context; and practice giving directions or presenting clear statements of assessments or intentions.

Demonstration of Accelerated Learning Using Engagement-Based Training: The “Think Like a Commander” Program

In the TLAC program, trainees work through a dozen or so scenarios in simulated compressed time, making decisions about deployment of assets, visualizing the battlefield and coping with contingencies as the scenario unfolds. They are coached in how experts look at problems and how the adversary would think about the problems. Trainees are encouraged to work intensively on the problems, and thus we might say this training represents highly motivated “practice with zeal.” The TLAC training can involve scaffolding by a trainer, or it can be conducted by trainees without the benefit of such scaffolding. The TLAC method is thus similar to Klein’s DMX method.

the training leads to significant improvement in the ability to rapidly analyze a tactical situation in order to identify the critical information needed for tactical decision-making. They demonstrated that TLAC training improved the ability of officers

The maxim “train as you fight” has risen to such a level of familiarity in the U.S. Army that the value of the notion goes almost unquestioned; that is, that the best training method is to “just do it” in a realistic environment. Yet studies of the development of expertise clearly indicate that “as you fight” meaning performing in fully realistic simulated battles is neither the most effective nor efficient method of developing expertise. Such “performances” can help a novice become acquainted with applying military knowledge and can reinforce existing knowledge in an experienced person, but will not in and of themselves lead to the development of expertise. In many fields where expertise has been systematically studied, including chess, music, and sports, development beyond intermediate level requires large amounts of deliberate practice

Characteristics of effective scenario-based and engagement-based training

The scenarios are tailored to learners (individual and/or group), depending on level of achievement, preparedness, or other factors. 
Scenarios are created from lessons learned. 
Scenarios are created based on empirical knowledge about how highly proficient workers apprehend problems. 
Scenario training assumes high intrinsic motivation of the trainee to work hard, on hard problems. 
For any given level of training, the scenarios are tough. They are novel to the learner, challenging them in ways described by Cognitive Flexibility Theory and Cognitive Transformation Theory (see above). 
Typically there is some daunting adversary, such as a superior or more capable opposing agent or force. 
The trainee is challenged to learn to think like the adversary. 
The fidelity is as high as needed. (In order: desktop exercises using paper and pen, virtual worlds presented on computer monitors, virtual environments, very high fidelity simulators, simulated villages.) 
Scenarios mimic the operational context. 
There is a designed-in ability for observers to record and measure what happened. 
The observers are experts. 
There are multiple reviews, not just one single “after action” review (although the latter is highly effective). 
Reviews provide both outcome and process feedback. 
Reviews include retrospection and the analysis of decision processes, emotional state of mind, teamwork, mental projection to the future, and other macrocognitive processes. 
The goal is for trainees to acquire strategic knowledge, adaptability and resilience.

Summary

Domain practitioners who achieve high levels of proficiency provide technical judgment to speed decision making in time-critical events.

They provide resilience to operations by resolving tough problems, acting prudently byjudgment rather than by rule, and anticipating future demands with replanning. High proficiency individuals exercise effective technical leadership in ambiguous or complex situations, often by communicating subtle features that other people will not see until they are pointed out. It typically takes years of experience for professionals to master their domain. Reasons for this include domain complexity and the need for extended and continuing practice at rare and difficult cases.

Training
Training is generally more effective if the initial learning is about domain concepts and principles and not just specific details of tasks and procedures.
Training at advanced levels (training to perform in dynamic and complex domains where tasks are not fixed) is generally more effective if it involves extensive practice on realistic examples or scenarios (problem-based learning).
Training has to balance giving and withholding of outcome and process feedback to achieve optimal learning at different stages of advancement.
Training at intermediate and advanced levels benefits significantly from experience at challenge problems or cases; the “desirable difficulties.” Short-term performance might suffer, but longer-term gains will emerge. 
Mentoring is valuable and critical for advanced learning, because it provides opportunities to receive rich process and outcome feedback as learners encounter increasingly complex problems. However, mentoring is not always necessary in advanced stages of learning. 
Training using intelligent tutoring systems and serious games (virtual reality systems) can be highly effective. 
Training that is based on a dynamic, context-sensitive, and situation-specific model derived from cognitive task analyses of expert performers is more effective than legacy training programs.

Transfer

Initial learning that is more difficult can lead to greater flexibility and transfer; when learners are initially exposed to simplifications of complex topics, serious misunderstandings can remain entrenched and interfere with or preclude deeper, more accurate understandings. 
Transferring a skill to new situations is often difficult but can be promoted by following a number of training principles: employing deliberate practice, increasing the variability of practice, adding sources of contextual interference, using a mixed practice schedule, distributing practice in time, and providing process and outcome feedback in an explicit analysis of errors.

Retention and Decay

Significant decay can occur even within relatively short time frames (days to weeks) for any form of skill or learned material. Although there can be differential decay of memory versus skill, decay is generally greatest shortly after a hiatus period begins, and levels out thereafter. For example, pilots know that most skill loss occurs within the first year, and then skill decay slows marginally after that. 
The best predictor of skill retention at the end of a hiatus is the level of performance achieved (including overlearning) just prior to the hiatus. The greater the degree of overlearning, the more that the decay curve gets “stretched out.” 
Performance that requires appreciable coordination between cognitive skills and motor skills is most substantially degraded (again, using piloting as an example, instrument flying skills deteriorate more than basic flying skills). 
Periodic practice during periods of hiatus should commence not long after the hiatus begins. Periodic practice can promote retention over long intervals. 
Retention during hiatus is better if the same practice task is not repeated, but is interspersed with other job-related tasks within practice sessions. 
The variable having the greatest impact on performance after a retention interval is the similarity of the conditions of the training (acquisition) and work (retention) environments. To promote retention, there should be substantive and functional similarity of the job tasks and job environment with the retention tasks and task environment.

Teams

Individuals who are more proficient at solving problems related to the team’s primary goals (team task work) place a high value on cooperation and engage in more work-related communication (teamwork). Thus, training in the achievement and maintenance of common ground will enhance team performance. 
In high-performing teams, team members develop rich mental models of the goals of the other team members. Training that promotes cross-role understanding facilitates the achievement of high proficiency in teams. 
High-performing teams effectively exchange information in a consensually agreed-upon manner and with consistent and meaningful terminology, and are careful to clarify or acknowledge the receipt of information. Training that promotes such communication facilitates the achievement of high proficiency in teams. 
Experienced teams efficiently exchange information, and may actually communicate overtly less than teams that are not high performing. 
Experience while team membership changes can facilitate the acquisition of teamwork skills. 
The question of performance decay in teamwork skills due to hiatus is an open subject for research. 
Training for accelerated team proficiency, like training for individuals, benefits from problem or scenario-based practice using realistic and complex scenarios (e.g., serious games, simulated distributed mission operations).

Key ideas of Cognitive Flexibility Theory
Learning is the active construction of conceptual understanding.
Training must support the learner in overcoming reductive explanation. 
Reductive explanation reinforces and preserves itself through misconception networks and through knowledge shields.
Advanced learning is the ability to flexibly apply knowledge to cases within the domain. Therefore, instruction by incremental complexification will not be conducive of advanced learning. Therefore, advanced learning is promoted by emphasizing the interconnectedness of multiple cases and concepts along multiple dimensions, and the use of multiple, highly organized representations.

Empirical ground 
Studies of learning of topics that have conceptual complexity (medical students). 
Demonstrations of knowledge shields and dimensions of difficulty. Demonstrations that learners tend to oversimplify (reductive bias) by the spurious reduction of complexity. 
Studies of the value of using multiple analogies. 
Demonstrations that learners tend to regularize that which is irregular, which leads to failure to transfer knowledge to new cases. 
Demonstrations that learners tend to de-contextualize concepts, which leads to failure to transfer knowledge to new cases. 
Demonstrations that learners tend to take the role of passive recipient versus active participants. 
Hypothesis that learners tend to rely too much on generic abstractions, which can be too far removed from the specific instances experienced to be apparently applicable to new cases, i.e., failure to transfer knowledge to new cases. 
Conceptual complexity and case-to-case irregularity pose problems for traditional theories and modes of instruction. Instruction that simplifies and then complicates incrementally can detract from advanced knowledge acquisition by facilitating the formation of reductive understanding and knowledge shields. 
Instruction that emphasizes recall memory will not contribute to inferential understanding and advanced knowledge acquisition (transfer).

Additional propositions in the theory 
Advanced knowledge acquisition (apprentice-journeyman-expert) depends on the ability to achieve deeper understanding and apply it flexibly. 
Barriers to advanced learning include complexity, interactions, context-dependence, and illstructuredness (inconsistent patterns of concepts-in-combination). 
Cognitive flexibility includes the ability to mobilize small, pre-compiled knowledge structures, and this “adaptive schema assembly” involves integration and updating, rather than just recall. 
Active “assembly of knowledge” from different conceptual and case sources is more important in learning (for domains of complexity and ill-structuredness) than retrieval of knowledge structures. 
Misconceptions compound into networks of misconceptions. 
Misconceptions of fundamental concepts can cohere in systematic ways, making each misconception easier to believe and harder to change. 
Representations with high interconnectedness will tend to serve as “misconception-disabling correct knowledge.” 
Cognitive flexibility is the ability to represent knowledge from different conceptual and case perspectives and construct from those an adaptive knowledge ensemble tailored to the needs of the problem at hand.

Key ideas of Cognitive Transformation Theory

Core syllogism Learning consists of the elaboration and replacement of mental models. 
Mental models are limited and include knowledge shields. 
Knowledge shields lead to wrong diagnoses and enable the discounting of evidence.

Therefore learning must also involve unlearning.

Empirical ground and claims 
Studies of the reasoning of scientists/ Flawed “storehouse” memory metaphor and the teaching philosophy it entailed (memorization of facts; practice plus immediate feedback, outcome feedback). 
Studies of science learning showing how misconceptions lead to error. 
Studies of scientist and student reactions to anomalous data. Success of “cognitive conflict” methods at producing conceptual change.

Additional propositions in the theory 
Mental models are reductive and fragmented, and therefore incomplete and flawed. 
Learning is the refinement of mental models. Mental models provide causal explanations. 
Experts have more detailed and more sophisticated mental models than novices. Experts have more accurate causal mental models. 
Flawed mental models are barriers to learning (knowledge shields). 
Learning is by sensemaking (discovery, reflection) as well as by teaching. 
Refinement of mental models entails at least some un-learning (accommodation; restructuring, changes to core concepts). 
Refinement of mental models can take the form of increased sophistication of a flawed model, making it easier for the learner to explain away inconsistencies or anomalous data. 
Learning is discontinuous. (Learning advances when flawed mental models are replaced, and is stable when a model is refined and gets harder to disconfirm.) 
People have a variety of fragmented mental models. “Central” mental models are causal stories.

Cognitive Transformation Theory argues for the importance of “unlearning”—experiences that force people to lose faith in their mental models so that they can move to the next level. The implication is that high levels of proficiency are achieved when the practitioner has an ability to lose confidence in an existing mental model.

Can this be done by starting again at first principles and critically thinking to a correct mental model of the world? - August 01, 2022 @ 9:09 PM

The core syllogism of the CFT-CTT merger

1. Learning is the active construction of knowledge; the elaboration and replacement of mental models, causal stories, or conceptual understandings. 
2. All mental models are limited. People have a variety of fragmentary and often reductive mental models. 
3. Training must support the learner in overcoming reductive explanations. 
4. Knowledge shields lead to wrong diagnoses and enable the discounting of evidence. 
5. Reductive explanation reinforces and preserves itself through misconception networks and through knowledge shields. Flexible learning involves the interplay of concepts and contextual particulars as they play out within and are influenced by cases of application within a domain.

Therefore learning must also involve unlearning and relearning.

Therefore advanced learning is promoted by emphasizing the interconnectedness of multiple cases and concepts along multiple conceptual dimensions, and the use of multiple, highly organized representations.

How do we avoid reductive explanations/mental models. Compression strikes again. This is probably why ELI5 works well because it forces you out of reductivism thinking. But how do we get better at ELI5 - August 01, 2022 @ 9:19 PM

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