A selection from How Learning Works:
7 Research-Based Principles for Smart Teaching.
Susan A. Ambrose, etal*
What is going on in these stories?
The instructors in these two stories believe that their students have the skills and knowledge necessary to perform well on the assigned tasks, yet their students' performance is disappointing, and neither instructor knows why. What is happening in each case that can help explain why these students fail to meet their instructor's expectation?
In fact, the tasks these instructors have assigned may require more from students than the instructors realize, and their students may be less prepared than their instructors assume. In the first story, for example, Professor Solomon expects the quality of group projects to be higher than the quality of individual projects because there are more people "to share the work and generate ideas." This seems like a reasonable assumption and is one that many instructors make. However, it is predicated on the expectation that students will know how to work effectively in groups. In fact, successful teamwork requires not only content skills and knowledge, but also an additional and qualitatively different set of process skills, such as the ability to delegate tasks, coordinate efforts, resolve conflicts, and synthesize the contributions of group members. When students possess the process skills necessary to manage the particular challenges of teamwork, the quality of work they produce in teams may indeed surpass the quality of the work they do individually. But when students lack these key component skills, it can seriously impede their performance.
Professor Kozol's students, in contrast, appear to have the necessary component skills. They have taken classes in and apparently mastered fundamental movement, voice, and speech skills. Yet when assigned a task that requires these skills, their performance is characterized by mistakes and omissions. Why? There are several possible explanations. First, although students have come to Professor Kozol's class with a solid grounding in movement, voice, and speech, they practiced these skills in classes targeting each skill area separately. Consequently, they may not have had sufficient practice using the complete set of skills in combination—especially while acting out an entire scene. If so, it is not the component skills they lack, but rather the ability to integrate them effectively.
Another possible explanation is that Professor Kozol's students did not recognize the relevance of phonetic transcriptions and vocal warm-ups—practices they had learned in previous courses—to the task they were assigned in her class. They may have failed to make this connection if their understanding of the underlying function of these practices was superficial or if they associated them entirely with the contexts (voice and speech classes) in which they had originally learned them. If so, the problem was not that students lacked component skills or that they were unable to integrate them successfully, but that they could not transfer them successfully to a new context and apply them appropriately.
What Principle of Learning is at Work Here?
As the stories have suggested, tasks that seem simple and straightforward to instructors often involve a complex combination of skills. Think back to when you learned to drive. You had to keep in mind a sequence of steps (adjust the mirrors, apply the brakes, turn the key in the ignition, put the car in reverse, check the rear view mirror, release the brake, press the accelerator), a set of facts (traffic rules and laws, the meaning of street signs, the functions of the car's controls and gauges), and a set of skills (accelerating smoothly, parallel parking, performing a three-point turn). You also had to learn how to integrate all of these component skills and knowledge, such as checking your mirror and moving into another lane. Finally, you had to recognize the appropriate context for certain knowledge and skills, such as adapting speed and braking behavior when driving on icy or clear roads.
To an experienced driver, driving is effortless and automatic, requiring little conscious awareness to do well. But for the novice driver it is complex and effortful, involving the conscious and gradual development of many distinct skills and abilities. A similar process exists in the development of mastery in academic contexts, as describe in the following principle.
Principle: To develop mastery, students must acquire component skills, practice integrating them, and know when to apply what they have learned.
Mastery refers to the attainment of a high degree of competence within a particular area. That area can be narrowly or broadly defined, ranging from discrete skills (using a Bunsen burner) or content knowledge (knowing the names of all U.S. presidents) to extensive knowledge and skills within a complex disciplinary domain (for example, French theater, thermodynamics, or game theory). For students to achieve mastery within a domain, whether narrowly or broadly conceived, they need to develop a set of key component skills, practice them to the point where they can be combined fluently and used with a fair degree of automaticity, and know when and where to apply them appropriately (see figure below).
The Elements of Mastery
Ironically, expertise can be a liability as well as an advantage when it comes to teaching. To understand why, consider the model of mastery by Sprague and Stuart (2000) illustrated in this figure
As illustrated in the diagram above, novice students are in a state of unconscious incompetence, in that they have not yet developed skill in a particular domain, nor do they have sufficient knowledge and experience, they advance to a state of conscious incompetence, where they are increasingly aware of what they do not know and, consequently, of what they need to learn. As their mastery develops, students advance to a state of conscious competence wherein they have considerable competence in their domain, yet still must think and act deliberately and consciously. Finally, as students reach the highest level of mastery, they move into a state of unconscious competence in which they exercise the skills and knowledge in their domain so automatically and instinctively that they are no longer consciously aware of what they know or do. As this model suggests, while competence develops in a more-or-less linear way, consciousness first waxes and then wanes, so that novices (in stage one) and experts (in stage four) operate in states of relative unconsciousness, though for very different reasons.
It is easy to see why novices lack conscious awareness of what they do not know, but less obvious why experts lack conscious awareness of what they do know. Research on expert-novice differences helps to illuminate the issue, however. Experts, by definition, possess vastly more knowledge than novices, but they also organize, access, and apply their knowledge very differently.
- Experts organize knowledge into large, conceptual "chunks" that allow them to access and apply that knowledge with facility1
- Immediate recognition of meaningful patterns and configurations based on previous experience, experts are able to employ shortcuts and skip steps that novices cannot2
- Because experts have extensive practice in a narrowly defined area (planning a problem-solving strategy or critiquing a theoretical perspective), they can perform with ease and automaticity tasks that are much more effortful for novices3
- Experts link specific information to deeper principles and schemas and are consequently better able than novices to transfer their knowledge across contexts in which those principles apply4
These attributes of expertise are an obvious advantage when instructors are working within their disciplinary domains, but they can be an obstacle to effective teaching. For example, the way instructors chunk knowledge can make it difficult for them to break a skill down so that it is clear to students. Moreover, the fact that instructors take shortcuts and skip steps with no conscious awareness of doing so means they will sometimes make leaps that students cannot follow. In addition, the efficiency with which instructors perform complex tasks can lead them to underestimate the time it will take students to learn and perform these tasks. Finally, the fact that instructors can quickly recognize the relevance of skills across diverse contexts can cause them to overestimate students' ability to do the same.
When expert instructors are blind to the learning needs of novice students, it is know as expert blind spot5 To get a sense of the effect of expert blind spot on students, consider how master chefs might instruct novice cooks to "sauté the vegetables until they are done." "cook until the sauce is a good consistency," or "add spices to taste." Whereas such instructions are clear to chefs, they do not illuminate matters to students, who do not know what "done" entails, what a "good consistency" is, or what spices would create a desired taste. Here we see the unconscious competence of the expert meeting the unconscious incompetence of the novice. The likely result is that students miss vital information, make unnecessary mistakes, and function inefficiently. They may also become confused and discouraged. Although they might muddle through on their own, it is likely that they will learn with optimal efficiency or thoroughness.
As instructors (tutors), we are all susceptible to expert blind spot. However, we can reduce the problems it poses for student learning by becoming more consciously aware of three particular elements of mastery that students must develop:
- the acquisition of key component skills
- practice in integrating them effectively
- knowledge of when to apply what they have learned
*(Michael W. Bridges, Michele DiPietro, Marsha C. Lovett, & Marie K. Norman)
1. (Chase & Simon, 1973b; Chase & Ericsson, 1982; Jiedubger & Abdersibm 1990)
2. (DeGroot, 1965; Anderson, 1992; Chase & Simon, 1973a; Koedinger & Anderson, 1990; Blessing &Anderson,
3. (Smith & Chamberlin, 1992; Lansdown, 2002; Beilock, Wierenga, & Carr, 2002)
4. (Chi, Feltovich, & Glaser, 1981; Larkin et al., 1980; Boster & Johnson, 1989)
5. (Nickerson, 1999; Hinds, 1999; Nathan & Koedinger, 2000; Nathan & Petrosino, 2003)