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OSN: Curriculum Development using Skill & Behavior Levels

The Dreyfus skills model provides a powerful conceptual framework for the development of courses. The model is introduced here with an expansion to include both skills and behaviors.
General Information

The following description is adapted from Bridges and Lau (2006).

The potential number of skills and methodologies required to be an ethnobotanist can be overwhelming, particularly if you are expected to be highly trained in each activity. Perhaps it is unrealistic to demand high proficiency in all activities. If so, is there a way that we can systematically identify the attainment of skill levels in ways that help us discuss appropriate types of proficiency? For example, there is a vast difference between someone who has learned how to use a GPS receiver to determine the latitude and longitude of a collection location and someone who understands the differences between using the latitude-longitude and UTM models. Does everyone need to understand the location models, or are there times when a tool is useful just for simple data collection?

Dreyfus & Dreyfus (1986) proposed a five-stage skill acquisition model to describe the general skill acquisition process that people undergo when they begin to learn and then master a new skill. They argue that the progression from novice to expert is dependent on the individual’s scope of perception and experience with the task at hand. Their model was developed based on recurrent learning patterns observed during skill-acquisition research involving airplane pilots, chess players, automobile drivers, and adult learners of a second language. Their five stages are termed 1) novice, 2) advanced beginner, 3) competent, 4) proficient, and 5) expert. They observed that at each stage, an individual becomes familiar with a skill by continually performing a series of activities. The first two stages rely heavily on following a set of rules pertaining to the technical aspect of the skill. The third stage is transitional in that a person begins to take on more responsibilities by becoming involved in the decision making process of projects that utilize the skill. People who have attained the fourth and fifth stages are making decisions without being consciously aware of their applying the rules learned during the first and second stages. The last two stages essentially separate a person from being a follower of rules to an effective decision maker.

The skills and behaviors levels are generally characterized as stages with the following attributes:

Novice: Follows the rules, requires specific rules for specific circumstances, and takes no responsibility other than following the rules.

Advanced Beginner: Expanded view of situations in which the skill is applied, begins to transfer rules to related situations, still makes decisions based on rules, and does not experience personal responsibility.

Competent: Senses that the number of rules is becoming excessive, begins to organize rules by developing principles, starts developing information on the relative importance of particular rules, and begins to experience responsibility relative to decision-making resulting from the application of rules.

Proficient: Problems are solved intuitively based on extensive previous experience, sees the “whole picture,” and applies conscious decision-making by formulating a plan of action.

Expert: Doesn’t go through the normal processes but intuitively senses what should be done, often without the need for analysis.



References

Bridges, K. W. and Y. Han Lau. 2006. The Skill Acquisition Process Relative to Ethnobotanical Methods. Ethnobotany Research & Applications 4: 115-118.

Dreyfus, H.L. & S.E. Dreyfus. 1986. Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer. Free Press.
Example: Quantitative Ethnobiology

The following notes illustrate the strategy for defining the large objectives (Field Data Collection, Data Handling, etc.) for a curriculum area (Quantitative Ethnobiology) and then resolving these into details for the five skill and behavior levels (Novice, Advanced Beginner, Competent, Proficient and Expert).

Implementation of the ways to move students up the skill and behavior levels will vary, often considerably, from course to course and between institutions. This framework provides concrete conceptual categories while permitting instructors to choose instructional strategies that best meet their students’ needs.

There is no implication that a student who is an “Advanced Beginner,” for example, in one curriculum area will be an “Advanced Beginner” in the other areas.

Note that, in general, skills from lower levels are included in higher levels.

Field Data Collection

Novice 
  • Follows directions with little understanding of the link to scientific questions. 
  • Uses instruments with trust and fails to do calibration and common-sense verification. 
  • Obtains information with experimental designs provided by others. 
  • Generally over or under samples with no regard for the principles of sampling. 
  • Has no awareness of the need for permits and permissions. 
  • Often records data in ways that are ambiguous. 
Advanced Beginner
  • Understand the need to collect data to answer specific scientific questions. 
  • Handles most instruments with confidence, including basic maintenance. 
  • Uses basic experimental design (e.g., control and experimental groups) principles. 
  • Samples with some consideration of sample size requirements. 
  • Relies on other people to obtain the necessary permits and permissions. 
  • Records data clearly. 
Competent
  • Understands the equipment needed to make measurements and the general limitation of the equipment. 
  • Calibrates equipment prior to use. 
  • Uses minimal-sampling techniques when possible. 
  • Applies common-sense comparisons of new data with existing equivalent data. 
  • Knows the value of good experimental design and uses this to plan data collection procedures. 
  • Optimizes the organization of data so that analyses proceed efficiently. 
  • Works within a strong ethical framework. 
Proficient
  • Optimizes the data collection by using best-practices instrumentation. 
  • Calibrates instruments prior to data collection and after data collection. 
  • Monitors data collection for outliers. 
  • Quickly exploits new data collection opportunities by quickly analyzing new data. 
  • Applies innovative sampling techniques. 
  • Anticipates the process of permits and permissions and secures cooperation well in advance of the field activities. 
  • Produces analysis results promptly and shares these with all collaborators. 
Expert
  • Organizes data collection programs that efficiently resolve key scientific questions. 
  • Creates data workflows that streamline all aspects of the data collection process. 
  • Monitors the data collection process so that it runs effectively. 
  • Builds networks of collaborators among who data and interpretations are freely shared. 
  • Supports the development of indigenous data collection and analysis systems. 
Note: the skills and behaviors for the following objectives are not specified here; they do follow the general pattern shown above.

Data Handling


Novice
Advanced Beginner
Competent
Proficient
Expert

Statistical Basics

Novice
Advanced Beginner
Competent
Proficient
Expert

Visualizations

Novice
Advanced Beginner
Competent
Proficient
Expert

Designing, Conducting and Analyzing Surveys

Novice
Advanced Beginner
Competent
Proficient
Expert

Finding Patterns

Novice
Advanced Beginner
Competent
Proficient
Expert

Mapping

Novice
Advanced Beginner
Competent
Proficient
Expert

Presentations

Novice
Advanced Beginner
Competent
Proficient
Expert