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Current interest in enhancing
student learning in engineering is widespread. Because the curriculum
has a major effect on what students learn, design and implementation
of curricular programs is a high priority for innovative engineering
colleges. The Foundation Coalition (FC) incorporates several
strategies to: (a) reform engineering curricula, (b) increase
student performance, and (c) evaluate reform with appropriate,
authentic assessment. This document provides case studies of
diverse institutions in the FC and showcases examples of how
assessment and evaluation data have been used to facilitate
curricular decision-making.
What is
assessment and evaluation?
Assessment is defined as data-gathering strategies, analyses,
and reporting processes that provide information that can be used
to determine whether or not intended outcomes are being achieved.[1]
Evaluation uses assessment information to support decisions on
maintaining, changing, or discarding instructional or programmatic
practices.[2] These strategies can
inform:
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The nature and extent of learning,
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Facilitate curricular decision making,
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Correspondence between learning and the aims
and objectives of teaching, and
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The relationship between learning and the environments
in which learning takes place. [3]
Why should
you care about assessment?
Assessment of student learning can be used for several purposes.
Student learning studies can be used to communicate learning achievement
for specified outcomes, for example, EC 2000 Criterion [3],
to provide learning evaluation to the student and the teacher, to
motivate the student, and to reinforce classroom strategies that
work well and target those warranting further investigation.
In addition to monitoring student learning, assessment can be used
to examine program efficacy. Such assessment can indicate the degree
of success of a program after its completion or can be ongoing during
a program to foster continuous improvement. Programmatic assessment
can be used to manage projects and communicate project outcomes,
evaluate the effectiveness of institutional programs, and determine
direction of future processes to improve the program over time.
How do you get data?
Quantitative studies yield numerical data that give a topical
view of program impact. Data collection may involve pretests and
posttests on course material, surveys, observations, or analysis
of institutional data such as grades, enrollment trends, retention,
and graduation rates. Quantitative data provide useful summaries
of what is happening in a program and can disclose patterns, anomalies,
and relationships. However, quantitative data do not necessarily
indicate why. Qualitative studies accommodate individual subjectivity
and detail and thus delve deeper into the social context behind
student performance, attitudes, and behaviors. The study of social
change frequently involves qualitative research because of its
focus on the social context and patterns. Qualitative research
aims to define meanings and actions in particular contexts, to
show how meanings and actions are organized, and to interpret
patterns in light of broader social contexts and similar settings.
For qualitative studies, researchers observe or interact and talk
with participants about their perceptions through individual interviews,
focus groups, and document collection.
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Resources
- Gagne, R.M., L.J. Bridges, and W.W. Wagne, 1998.
Principles of Instructional Design. Orlando, FL: Holt,
Rinehart and Winston, Inc.
- Hanson, G., and B. Price, 1992. Academic Program
Review. In M.A. Wjitley, J.D. Porter, and R.H. Fenske (eds.).
The Primer for Institutional Research. Tallahassee: Association
for Institutional Research.
- Satterly, D., 1989. Assessment in Schools.
Oxford, UK: Basil Blackwell Ltd.
- Hake, Richard R., 1998. Interactive-engagement
vs. traditional methods: A six-thousand-student survey of
mechanics test data for introductory physics courses. American
Journal of Physics 66:64–74.
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©
2001 Foundation Coalition. All rights reserved. Last modified
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