Identificación de requisitos para el producto

Novices not only have more sparse knowledge organizations compared to experts, but the basis for their organizational struc- tures also tends to be superfi cial. This affects their ability to remember and use what they learn effectively (Chi & VanLehn, 1991 ; Hinsley, Hayes, & Simon, 1977 ; Ross, 1987, 1989 ). Chi and colleagues (1989) demonstrated this in a study in which they asked physics novices and experts to group various problem descriptions into categories. The novices grouped problems accor- ding to the superfi cial “ looks ” of their diagrams — for example, putting all the problems with pulleys in one group and all the

problems with ramps in another group. This way of organizing the different problems around surface features did not refl ect the structural relationships among problems, and thus did not facili- tate successful problem solving for the novices. In contrast, the experts in this study organized the problems based on deeper and more meaningful features, such as the physical laws involved in solving each problem. Moreover, when talking through the ratio- nale for their groupings, the experts revealed that sorting each of these problems into a category naturally triggered in their minds the solution template for how “ problems like this ” are solved. Thus, the experts ’ organizations were based on a set of deep fea- tures that directly related to how they would go about solving the problems.

Experts ’ ability to classify information in more meaningful — and thus more practically useful — ways than novices is linked to their ability to recognize meaningful patterns. For example, DeGroot (1965) conducted a landmark study in which he showed novice and master chess players a chess board midgame and asked them to generate possible next moves. While both masters and novices considered a roughly equivalent number of possible moves, there were signifi cant differences in the quality of plays they considered: novices tended to choose from among a seem- ingly random set of options, whereas experts spent their time weighing the pros and cons of a very select set of high - quality moves. From the large amount of research on chess expertise (see also Gobet & Charness, 2006 ; Chase & Simon, 1973a, 1973b ), it is clear that this difference stems from experts ’ vast experience analyzing chess situations and assessing possible strategies. As the result of this experience, they possess a highly developed knowl- edge organization that allows them to immediately recognize meaningful board confi gurations and zero in on a set of high - quality moves.

Indeed, experts ’ ability to see and instinctively respond to patterns not only helps them solve problems but also enhances their memory. Further research on chess has shown that experts can glance at a chessboard from a particular chess game situation and then take an empty board and replicate the exact positions of fi fteen or more of the pieces they just saw (Chase & Simon, 1973a, 1973b ). This is not a result of superior memory, but rather a refl ec- tion of the deep and intricate set of relationships they can see among pieces and that they automatically use during play. This ability among experts to immediately recognize and respond to patterns is not limited to chess but has been demonstrated among experts in many domains (Egan & Schwartz, 1979 ; Lesgold, et al., 1988 ; Soloway, Adelson, & Ehrlich, 1988 ). In one study, for example, skilled electronics technicians and novices were briefl y shown symbolic drawings of complex circuit diagrams and then asked to reconstruct the drawings from memory (Egan & Schwartz, 1979 ). The experts were able to reconstruct a far greater number of elements in the diagrams, even after seeing them for just a few seconds. The researchers attributed this superior recall to two things: the experts ’ ability to successfully characterize the entire diagram (as “ some kind of power supply, ” for example) and also to identify parts of each drawing that corresponded to recogniz- able features, such as amplifi ers. They were then able to perceive the visual information from the diagrams in terms of these mean- ingful confi gurations and use that knowledge organization to help them remember what they had seen.

In addition to organizing their knowledge around meaning- ful features and patterns, experts have the benefi t of fl exibly using multiple knowledge organizations. A paleontologist ’ s knowledge of dinosaurs, for example, would not be organized around a single organizational hierarchy, but rather would include an interwoven web of classifi cations and connections based on geological age, habitat, eating habits, relation to modern - day reptiles, strategies

for self - protection, and so on. Likewise, a historian could draw on his or her knowledge in a way that is organized around theories, methodologies, time periods, topic areas, historical fi gures, or combinations of these. Novices, on the other hand, tend not to have as many alternative organizations to tap into. This difference between novice and expert representations is illustrated in the second story at the beginning of this chapter. As an expert in his fi eld, Professor Patel moves fl exibly among multiple ways of rep- resenting the human body, such as according to body system and according to common functions or higher - order principles. Thus, Professor Patel can use his knowledge in multiple ways, tapping into different knowledge organizations according to the need. His students, however, are more limited.

Obviously, developing the kinds of meaningfully connected knowledge organizations that experts possess takes time and experience. Most of our students are far from attaining that level of expertise. However, even novice students learn and remember more when they can connect information in meaningful ways. In one study that helps to illustrate this point, Bradshaw and Anderson (1982) asked college students to learn various facts about historical fi gures. They found that students learned the most when they were presented with facts that could be meaning- fully related to one another. In other words, it was easier for stu- dents to learn and retain multiple facts with a causal dimension (for example: Isaac Newton became emotionally unstable and insecure as a child, Newton ’ s father died when he was born, and Newton ’ s mother remarried and left him with his grandfather) as compared to a single, isolated fact. However, students only showed this advantage when there was a relationship among the multiple facts that allowed students to make meaningful connections. Thus, the learning advantage did not apply when the multiple facts were unrelated (for example: Isaac Newton became emotion- ally unstable and insecure as a child, Newton was appointed

warden of the London mint, and Newton attended Trinity College in Cambridge). Research has also shown that there are instruc- tional approaches that can help students organize their knowl- edge meaningfully around deep, rather than superfi cial, features of the domain. For example, studies have shown that when stu- dents are given problems that are already solved and are asked to explain the solution to themselves — thereby focusing on the prin- ciples that guide the solution — they are better able to solve new problems (Chi et al., 1989 ). Research also suggests that guiding students through a process of analogical reasoning helps students to see past superfi cial similarities and instead focus on deeper connections and relationships (for example, Gentner, Loewenstein, & Thompson, 2003 ; McDaniel & Donnelly, 1996 ). Similarly, when students are presented with and analyze contrasting cases, they are better prepared to learn from a lecture or reading assignment (Schwartz & Bransford, 1998 ). By engaging in such processes, students tend to build more effective knowledge organizations and learn and perform more effectively.

Implications of This Research One implication of this research is to realize that, as experts in our domain, we may orga- nize our knowledge in a way that is quite different from how our students organize theirs, and that our knowledge organization plays a signifi cant role in our “ expert performance. ” Given that students are likely to come up with knowledge organizations that are superfi cial and/or do not lend themselves to abstraction or problem solving, this suggests that, at least initially, we need to provide students with appropriate organizing schemes or teach them how to abstract the relevant principles from what they are learning. In addition, it means that we need to monitor how stu- dents are processing what they are learning to make sure it gets organized in useful ways.

WHAT STRATEGIES DOES THE

RESEARCH SUGGEST?

The following strategies offer ways for instructors to assess their own knowledge organizations relative to students ’ and help stu- dents develop more connected, meaningful, and fl exible ways of organizing their knowledge.

Strategies to Reveal and Enhance