Expert vs Novice Information Scientists

What's the difference between a professional information scientist and a student information scientist? How does a student evolve as an information scientist? How can teachers help students develop as information scientists?

This page addresses the following questions: What's an expert?, What are the characteristics of experts?, and What are learner-centered teaching strategies?.

What's an expert?

An expert has a high degree of proficiency, skill, and knowledge in a particular subject. Experts are able to effectively think about and solve information problems. They see patterns in information and are able to identify solutions. Moving from novice to expert involves much more than simply developing a set of generic skills and strategies. Experts develop extensive knowledge that impacts the way they identify problems, organize and interpret data, and formulate solutions. Their approach to reasoning and solving information problems is different than a novice.

In their report, How People Learning: Brain, Mind, Experience, and School, Bransford, Brown, and Cocking (1999) identified key principles of experts' knowledge and their potential implications for learning and instruction:

1. Experts notice features and meaningful patterns of information that are not noticed by novices.
2. Experts have acquired a great deal of content knowledge that is organized in ways that reflect a deep understanding of their subject matter.
   
3. Experts' knowledge cannot be reduced to sets of isolated facts or propositions but, instead, reflects contexts of applicability: that is, the knowledge is "conditionalized" on a set of circumstances.
4. Experts are able to flexibly retrieve important aspects of their knowledge with little attentional effort.
5. Though experts know their disciplines thoroughly, this does not guarantee that they are able to teach others.
6. Experts have varying levels of flexibility in their approach to new situations.

What are the characteristics of experts?

Early research by DeGroot (1965) found that experts perceive and understand stimulus differently from novices. He asked chess masters and beginners to think aloud as they played chess games. DeGroot hypothesized that masters would think through all the possible moves (breadth of search) and countermoves (depth of search), while beginners would not. He found that both experts and novices explored the possibilities. However the chess masters considered moves that were higher quality than beginners.

DeGroot concluded that knowledge acquired through experience enabled the masters to recognize meaningful chess configurations and identify the strategic implications. In other words, experts were able to see patterns and connections not evident to novices.

Much research has focused on the characteristics of experts. A few results are highlighted below:

• Glaser (1992) noted that although there is no substitute for life experiences it is possible to help students move toward thinking like math and science experts. Experts can effectively organize knowledge around key concepts, respond to context, and self-regulate their focus.
• Ericsson and Charness (1994) found that experts spend many hours each day studying and practicing. They vary their methods and explore new strategies for self-improvement. This quantity and quality in practice is reflective of expert behavior.
• Zimmerman and Risemberg (1997) found that experts plan their efforts using powerful strategies and then self-observe. For example, they might use a concept map for organizing information. They self-evaluate their performance based on their goals focusing on the effectiveness of particular strategies rather than ability attributions.
• Wineburg (1998) focused on the importance of the metacognitive aspect of expert work. When observing how historians study historical texts, he found that experts rely heavily on self-questioning and self-monitoring.
• Cleary and Zimmerman (2000) found that experts differ from novices in their ability to self-regulate. For example, experts know when to apply knowledge at crucial times during performance. Novices tend to learn reactively rather than with forethought and planning. Experts tend to set personal goals for themselves rather than comparing themselves to others.

Based on the growing body of research, the following attributes of experts can be identified. Experts:

• Pose useful questions to themselves throughout the process
• Identify relevant information and ignore irrelevant information
• Respond to context and select information to address specific needs
• Recognize meaningful patterns and connections in information
• Organize knowledge around key principles and concepts
• Self-regulate their time and efforts including goal setting, time management, self-evaluation, self-motivation
• Self-motivate through varying their methods of study and practice
• Remain flexible in thinking adapting to changing needs

What are learner-centered teaching strategies?

Although we don't expect our students to become expert information scientists, they can begin developing and applying the strategies used by professionals. According to Thompson, Licklider, and Jungst (2003), "a learner-centered approach to developing expertise requires purposeful and specific instruction that builds student capacity in these arenas". They stress that learner-centered teaching strategies should:

• contribute to the breadth and depth of content knowledge
• assist students in learning how to organize knowledge around major concepts and principles
• enhance retention and retrieval
• contribute to student development of metacognitive abilities, among other things.

Meaningful learning occurs when students are able to see the relevance of knowledge and skills and can apply these for successful problem solving. According to Mayer and Wittrock (1996) transfer is the ability to use what was learned to solve new problems, answer new questions, or facilitate learning new subject matter.

Based on our knowledge of the differences between novices and experts, how do we help student information scientists develop the necessary repertoire of knowledge and range of skills and strategies? Consider some of the following key areas:

• Core Concepts and Experiences - learners need a foundation of knowledge, background information, examples, resources, and varied experiences related to their topic organized around the big ideas
• Task Analysis - learners must develop an understanding of the problem or key questions and be able to prioritize and focus on the key issues
• Pattern Recognition - learners must be able to structure information in meaningful ways and see the how ideas are connected
• Metacognition - learners must be aware of their thinking and flexible enough to adapt to changing needs
• Self-regulation - learners must be able to control their thinking and actions

 

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