Introduction and Invitation
Constructing resources for assessment and instruction related to the eleven student outcomes contained in Criterion 3 of the ABET Engineering Criteria requires contributions across the entire engineering community. If you have one or more resources (for example, helpful papers, survey forms, assessment materials, instructional materials) for assessment and/or instructional related to outcome b click here. Please indicate whether and how you would like your contribution to be acknowledged. Thanks for contributing the growing understanding of how we might help engineering students develop knowledge and skills that they will draw upon throughout their careers.
The first step in selecting assessment and instructional approaches for a learning outcome is to formulate learning objectives that support the outcome. Learning objectives describe expectations associated with the outcome in terms of expected and observable performances. Several researchers have already constructed learning objectives and these may provide worthwhile starting points for others.
A team of researchers (Larry Shuman, Mary E. Besterfield-Sacre, Harvey Wolfe, Cynthia J. Atman, Jack McGourty, Ronald L. Miller, Barbara M. Olds, and Gloria M. Rogers) working a NSF-supported project, Engineering Education: Assessment Methodologies and Curricula Innovation, used Bloom's Taxonomy to develop and organize a set of learning objectives for outcome 3b (desiging and conducting experiments and analyzing and interpreting data) . They developed learning objectives for the six levels of learning in Bloom's taxonomy for four different outcome elements:
- Designing experiments
- Conducting experiments
- Analyzing data
- Interpreting data
Felder and Brent  offer sample learning objectives for each of the four preceding outcome elements:
- Designing Experiments: Design an experiment to (insert one or more goals or functions) and report the results (insert specifications regarding the required scope and structure of the report). Variants of this objective could be used in traditional lecture courses as well as laboratory courses.
- Conducting Experiments: Conduct (or simulate) an experiment to (insert specifications about the goals of the experiment) and report the results (insert specifications regarding the scope and structure of the report).
- Analyzing Data: Develop a mathematical model or computer simulation to correlate or interpret experimental results (insert specifications regarding the experiment and the data). The results may be real data from a laboratory experiment or simulated data given to students in a lecture course.
- Interpreting Data: List and discuss several possible reasons for deviations between predicted and measured results from an experiment, choose the most likely reason and justify the choice, and formulate a method to validate the explanation.
McCreanor  described how faculty members in the School of Engineering at Mercer University constructed profeciencies for the same four outcome elements:
- Designing experiments: Develop a methodology which will produce high quality data that can be used to evaluate a specific process or parameter.
- Operate laboratory equipment appropriate to the course or discipline
- Demonstrate appropriate laboratory technique and etiquette, collect data
- Organize data
- Perform appropriate data manipulations and calculations
- Ppresent final data in an appropriate format
- Use good engineering judgement to determine if data is reasonable
- Draw appropriate conclusions from data,
Under construction (18 January 2005)
Under construction (18 January 2005)