http://taloe.up.pt http://taloe.up.pt Improving learning outcomes assessment in Engineering Education Rita Falcão Universidade NOVA de Lisboa ENAEE Members Forum 2017, Leuven 18NOV17 The European Commission support for the production of this publication does not constitute endorsement of the contents which reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.
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http://taloe.up.pthttp://taloe.up.pt
Improving learning outcomes
assessment in Engineering
Education
Rita Falcão
Universidade NOVA de Lisboa
ENAEE Members Forum 2017, Leuven18NOV17
The European Commission support for the production of this publication does not
constitute endorsement of the contents which reflects the views only of the
authors, and the Commission cannot be held responsible for any use which may
be made of the information contained therein.
http://taloe.up.pt
Before…
ASSESSMENT
LEARNING
OBJECTIVES
What will we teach our students?
CONTENT
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Why change?...
▪ Demand for new skills and competences
▪ Mobility and recognition
▪ Quality approach and accreditation
THE FOCUS IS ON
THE STUDENTS!
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What should the students learn?
ASSESSMENTLEARNING
OUTCOMES
What do we
hope students will learn?
How do we know what
students have learned?
ALIGNMENT
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Learning Outcomes
Learning outcomes are statements of what a learner
is expected to know, understand and/or be able to
demonstrate after completion of learning.
(AHELO - Assessment of Higher Education Learning
Outcomes by OECD)
Assessment
Assessment: Any procedure used to estimate student learning for whatever purpose.
(Brown et al)
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Alignment
Statement of the
intended LO
Teaching and
Learning activities
Learning Outcome
Assessment tasks
Alignment: The level of
correspondence
between objectives,
instruction and
assessment.
(Anderson et al)
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Simple problem…?
Learning Outcomes
Assessment
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(STOLEN FROM THE PRESIDENT)
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Learning Outcomes in Engineering
▫ EUR-ACE: European quality label for engineering degree
programmes
▫ ABET: Accreditation Board for engineering and Technology
Similar work – LOs in Engineering / Bloom“Defining the Outcomes: A Framework for EC-2000” by Mary Besterfield-Sacre et al.
ABET b - An ability to design and conduct experiments, as well as to analyze and interpret data
Designing experiments 1.1 Can recognize applicable analytical models, possible simulators (e.g. physical, digital, continuous, other format), testing apparatus, databases, models, etc. 1.2 Can identify applicable theory and recognize the past history 1.3 Can describe different measurement techniques and alternatives based on cost, etc. 1.4 Gives examples of possible disruptions that may occur while conducting experiment that could affect experimental data 1.5 Can discuss laboratory/experimental protocols 1.6 Understands the need for proper units 1.7 Can indicate how existing theory/history differs/complements current question 1.8 Can select the variables in questioned (controllable, level of variation, impact with other variables) 1.9 Identifies the constraints and assumptions for the experiment -cost, time, equipment 1.10 Can construct an appropriate hypothesis or problem statement 1.11 Can select appropriate equipment, test apparatus, model, etc. for measuring variables in question 1.12 Aware of orderliness and integrity of data 1.13 Can use existing theory/history to design an experiment 1.14 Chooses the measure(s) of effectiveness by which the outcome or the alternative will be evaluated – cost, quality, value, time to complete, feasibility 1.15 Formulates the control and evaluating alternatives of the experiment 1.16 Develops contingency plans 1.17 Apply constraints and assumptions into experimental design 1.18 Determines the data that are appropriate to collect 1.19 Specifies and justifies the assumptions given test conditions 1.20 Predicts experimental uncertainties 1.21 Seeks information for experiment from multiple sources 1.22 Accepts the limitations and extensions that an experiment built can be used to represent the system Conduct experiments 2.1 Aware of measurement errors in instrumentation, human, environment 2.2 Anticipates and minimizes experimental disruptions via pilot study 2.3 Acknowledges possible disruptions to existing surroundings and operations 2.4 Uses appropriate measurement techniques to collect data 2.5 Facilitates use of modern data collection techniques (computer for data logging) 2.6 Follows ethical protocols when collecting data 2.7 Documents collection procedures such that experiment may be repeated 2.8 Anticipates and minimizes data errors via pilot study Analyse data 3.1 Can select and explain different methods of analysis (descriptive and inferential) and depth of the analysis needed 3.2 Can identify different audiences and their analysis/summary needs 3.3 Can identify artifacts/confounding elements that may result 3.4 Uses appropriate tools to analyze data 3.5 Selects and uses appropriate, self-explanatory graph formats for data 3.6 Prepares analysis such that results can be replicated 3.7 Can apply statistical procedures 3.8 Investigates possible artifacts with a balance of costs associated with the analysis 3.9 Organizes information into meaningful categories
