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6 Training Strategies to Accelerate Expertise from Sternberg’s Model of Intelligence


6 training strategies from Sternberg to accelerate expertise

This article presents 6 training strategies to accelerate expertise based on the postulations from Sternberg’s (1999) model of expertise development.


How to accelerate expertise? I have written couple of posts on this topic. See my posts: Accelerated Expertise with Mentoring and Tough CasesWhat Does 9 Famous Training Models Say About Accelerating Expertise?, and 70:20:10 framework: 9 guidelines to accelerate time-to-competence of workforce (Part-1). In each of the posts, I highlighted the need to find solutions to accelerate expertise. Among several models for training design, the “Developing Expertise” Model by Sternberg (1999) is quite useful to define the training strategies. The main feature of this model is that it postulated that ‘expertise’ is trainable – however, required correct orchestration of the training strategies.

What is Sternberg’s Model of Expertise?

Sternberg presented a model of developing expertise have five key elements:

  • Metacognitive skills,
  • Learning skills,
  • Thinking skills,
  • Knowledge and
  • Motivation.

Fundamentally Sternberg’s model is based on cycling and interactions of several skills together to achieve expertise. The core philosophy is that Motivation is believed to drive metacognitive skills which in turn activate learning and thinking skills, which then provide feedback to the metacognitive skills, enabling one’s level of expertise to increase (Sternberg, 1985). The declarative and procedural knowledge acquired through the thinking skills and learning skills also contribute toward acquisition of expertise.

6 training strategies to accelerate expertise from Sternberg's model

6 components of Sternberg’s Model explained

Sternberg explains following contributing elements that lead to the development of expertise:

1) Metacognitive skills.

Metacognitive skills are people’s ability to self-regulate their learning. Sternberg (1985, 1986) specified seven metacognitive skills are particularly important:

  • problem recognition, problem definition,
  • problem representation,
  • strategy formulation,
  • resource allocation,
  • monitoring of problem-solving, and
  • evaluation of problem-solving

The important postulation of this model is that all of these skills are modifiable and trainable (Sternberg, 1986, 1988; Sternberg & Spear-Swerling, 1996).

2) Learning skills.

Learning skills helps an individual to attain the knowledge. Sternberg specifies two kinds of learning skills: explicit and implicit ones. Explicit learning is what occurs when we make an effort deliberately to lean something whereas the implicit learning is one which we pick incidentally without any systematic effort. Selective coding, selective filtering and distinguishing relevant vs. non-relevant are learning skills which are again trainable with appropriate training.

3) Thinking skills.

Sternberg (1997a) emphasizes three kinds of thinking skills which attribute to developing expertise through training.

  • Critical (analytical) thinking skills include analyzing, critiquing, judging, evaluating, comparing and contrasting, and assessing.
  • Creative thinking skills include creating, discovering, inventing, imagining, supposing, and hypothesizing.
  • Practical thinking skills include applying, using, utilizing, and practicing (Sternberg, 1997b).

4) Knowledge skills.

Sternberg specified two types of knowledge important to acquire expertise:

  • Declarative knowledge refers to ‘knowing that’ like facts, concepts, principles, laws, and the like. Declarative knowledge is further represented by Anderson on revised Blooms’ taxonomy as
    • factual knowledge (knowledge of basic elements and knowledge of specific details of various elements) and
    • conceptual knowledge (interrelationship of basic elements within a large structure that makes them work together. Example knowledge about classification, principle of operations, theory, models and structures).
  • Procedural knowledge, on the other hand, is ‘knowing how’ like procedures and strategies. Sternberg et al. (1995) place big importance on procedural knowledge. Anderson et. al (2001)’s revised Blooms’ Taxonomy further defines procedure knowledge as knowledge of subject-specific skills and algorithms, knowledge of techniques and methods, knowledge of determining criteria for when to use appropriate procedures

5) Motivation:

Motivation has been categorized into two kinds:

  • Achievement motivation (McClelland, 1985; McClelland, Atkinson, Clark, & Lowell, 1976) referring to people’s tendency to seek moderate challenges and risks to achieve accomplishments.
  • Competence motivation refers to persons’ beliefs in their own ability to solve the problem at hand (Bandura, 1977, 1996).

Sternberg postulates that expert develops competence motivation that helps them solve the difficult tasks in their domain. It can be inferred that competence and achievement motivation can be instilled through managed successes during a training course.

The novice works toward expertise through deliberate practice but motivation is the key to practice. Practice for expertise requires an interaction of all five of the key elements. At the center, driving the elements is motivation (Sternberg, 1999). Sternberg (1999) states that “Eventually, one reaches a kind of expertise, at which one becomes a reflective…practitioner of a certain set of skills. People thus cycle through many times, on the way to successively higher levels of expertise”.

6) Context:

All of these processes are affected by, and can, in turn, affect, the context in which they operate. Sternberg asserts that context also plays an important role in success at gaining expertise faster. The learning environment and its ability to provide the relevant context to the learner play a big role in gaining proficiency (Caterjon et al., 2006).

6 Training Strategies derived from Sternberg’s Model to Accelerate Expertise

Sternberg’s  research postulations can be used in following ways:

1. Design thinking based curriculum to accelerate critical, creative and practical thinking skills

Thinking is core skills to gain expertise. Research has proven that experts and highly skilled individuals use their mental schema to their advantage. The key to a well-developed mental schema is an ability to think from different angles. For years training practitioners have a particular challenge in designing curriculum which develops higher order thinking. The key to the thinking based curriculum is designing “discussions” in the lesson plan.

  • To develop critical thinking into the curriculum, make sure course is designed as participant-centered with lots of reflection exercise and emphasis on why and cause-n-effect.
  • Hands-on procedures with emphasis on situational and conditional context will help build practical thinking skills.
  • A participant-centered course should allow plenty of activities allowing participants to come up with new ways to a given problem. This will help to build creative thinking skills.

2. Integrate managed challenges and managed successes in the assessment to enhance motivation

Training course primarily should be focused on assessment, both formative and summative. However, if the target is to accelerating skill acquisition then assessment needs to be dealt from a different angle. Assessments can range from challenging questions to solving actual problems or scenarios. Care should be taken to define the sequence of challenge correctly. This is key to build achievement motivation through progressive successes of the learners throughout the course. The goal of these challenges should be to give the progressive ability to the individual to solve and gain confidence which leads to competence motivations.

3. Develop the scenarios with noise and signal to induct good learning skills

In the real-world, the situations are presented as complex mixtures of noise and signals. Those are associated with a reasonable amount of noise (irrelevant information but it makes learning about the phenomenon difficult). It is important to teachability to disseminate noise from signal in order to gain expertise. A training course should include good activities which address both explicit and implicit learning skills.

4. Build solid foundation declarative and procedural knowledge in the course

Sternberg emphasized the importance of declarative and procedural knowledge. According to revised Blooms’ Taxonomy by Anderson et. al (2001), declarative and procedural knowledge is acquired through cognitive processes like remembering, understanding, applying, analyzing, evaluating, creating. Training course to build expertise. Note that some of these processes are also the underlying mechanism of critical thinking. Again, critical thinking and practical thinking skills are the mental processes through which knowledge is understood and disseminated and grown further. Training technique here is to ensure that factual, conceptual and procedure knowledge is presented and discussed with participants from the various cognitive mechanism. For example: while teaching aerodynamics, the content can address the definition and core principles which can be extended by presenting a problem to participants and have them analyze the data. This can further be re-positioned to give them a system with an issue and asking them to evaluate the root cause and then fix it. By doing so, factual, conceptual and procedure knowledge get solidified through all cognitive processes at various levels.

5. Incorporate reflections on strategies and self-monitoring

A training program for expertise development not only focuses on providing training on using and applying declarative and procedural knowledge but also to help participants to form their own strategies and approaches and monitor their progress to problem-solving. This area, known as metacognitive knowledge has been the focus of many research studies. Two individuals with exactly same skills may simply differ in effectiveness just because they differ in how they monitor their problem-solving progress, how they use metacognitive strategies towards problem-solving. That is one of the key differentiation an expert has over a novice. Training design tip here is that design range of problems/scenarios in your training course and drive participants to apply various strategies in different situations, different conditions, and different contexts. That’s how you can develop their metacognitive strategies and improve self-knowledge.

6. Design environment close to realistic situation

Context plays a great role in accelerating expertise. Care should be taken to provide the challenges as real as possible. According to research, if learners are given real problems as opposed to fabricated, they tend to pay more attention and put all their efforts to solve the same. If you are designing a car repair course, then better you simulate the actual car workshop environment in the class, Yet better you conduct the course in an actual car workshop. Reality drives motivation. Simulation-based training is one method among others to build a realistic environment.

Stay tuned for more insights.


Interested readers can check out following links to expand their understanding of Sternberg’s model of expertise:

Abilities Are Forms of Developing Expertise

Intelligence as developing Expertise

Metacognition, abilities, and developing expertise: what makes an expert student?


Attri, RK (2017), ‘6 Training Strategies to Accelerate Expertise from Sternberg’s Model of Intelligence’, [Blog post], Speed To Proficiency Research: S2PRo©, Available online at <https://www.speedtoproficiency.com/blog/6-training-strategies-to-accelerate-expertise-from-sternbergs-model/>.

protected for plagiarism


  1. Sternberg, R. (1999). Intelligence as Developing Expertise. Contemporary educational psychology, 24(4), 359–375. http://www.sciencedirect.com/science/article/pii/S0361476X98909985?via%3Dihub
  2. Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge Univ. Press. 
  3. Sternberg, R. J. (1986). Intelligence applied. Orlando, FL: Harcourt Brace College.
  4. Sternberg, R. J. (1988). The triarchic mind: A new theory of human intelligence. New York: Viking–Penguin.
  5. Sternberg, R. J., & Spear-Swerling, L. (1996). Teaching for thinking. Washington, DC: APA Books.
  6. Sternberg, R. J. (1997a). Successful intelligence. New York: Plume.
  7. Sternberg, R. J. (1997b). Thinking styles. New York: Cambridge Univ. Press.
  8. Sternberg, R. J., Wagner, R. K., Williams, W. M., & Horvath, J. A. (1995). Testing common sense. American Psychologist, 50, 912–927.
  9. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 181–215.
  10. Bandura, A. (1996). Self-efficacy: The exercise of control. New York: Freeman.
  11. McClelland, D. C. (1985). Human Motivation. New York: Scott, Foresman.
  12. McClelland, D. C., Atkinson, J. W., Clark, R. A., & Lowell, E. L. (1976). The achievement motive. New York: Irvington.
  13. Anderson, L.W., Krathwohl, D.R, Airasian, P.W., Cruikshank, K.A., Mayer, R.E, Pintrich, P.R., Raths, J., Wittrock, M.C. (2001), A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives, Complete Edition, Pearson

Image Credits: CC0 attribution by Kinenori @Pixabay

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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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