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CPM Media Selection
Process and Potential
Future Software
Capabilities
Danette Likens
AIM Team
4 April 2012
It doesn't matter how sound
the media strategy if the
design strategy is flawed
NETCINST 1500.6 – FEA Guidance
including Media Selection
• Manual process utilizing Excel spreadsheets
and complex algorithm
•
Lacks scientific support
•
Not user friendly
•
Ambiguous in media selection /
recommendation process
•
Easily manipulated
•
Subjective input
•
Creates excessive workload for user
Proposed Process
• Simple and scientifically supported model
• Meets the needs of N9 media selection and
media evaluation tasks
• Utilizes data elements already captured in CPM
(no additional workload on the user)
• Current input is subjective – proposed input is
objective
• This approach will solidify the process and
remove possibility of manipulating data to justify
the desired media strategy
Proposed Process
(contd)
Elements used in the media selection criteria
could:
• Be used to explore and validate emerging
technologies for inclusion as viable media
options
• Cross multiple platforms not yet explored
• Be used to guide assessment of learning
outcomes (Bloom, 1942)
Data Elements & Supporting
Theory
•
•
•
•
•
Knowledge Proficiency Level (KPL) (Bloom’s
Taxonomy) (Bloom, 1956)
Skill Proficiency Level (SPL)
Verb (Domains of Learning) (Gagné, 1972)
Content Type (Clark, 2007)
Cognitive Level (Clark, 2007)
How it Works
The learning domain is determined based on the Verb
used in the task (Cognitive, Affective, Psychomotor)
(Gagné, 1972)
• Although some verbs may cross domains, those
utilized tend to be repetitive within a job to
show a process, procedure, principle, concept, or
fact based training element
• Combining the Content Type with the Learning
Domain defines the learning context without the
use of the objective, conditions, or standard
(Gagné, 1972; Bloom, et al, 1956)
How it Works
(contd)
•
•
Adding elements from the Cognitive Level
ensures proper media delivery mode is
selected and further delineates alternate
choices without having to populate and
analyze large amounts of data per task
Adding the KPL and SPL level to the verb
domain and content type lends to the level
of interactivity needed to adequately train
or perform
Process Description
•
CPM aggregates data elements for each module,
lesson, section giving recommended strategy for
each
•
Media strategy tables are used to direct system to
media recommendation (see handout)
•
An overarching recommendation is provided for
the course.
•
Potential / estimated reduction in efficacy (based
on primary learning domain) will display for
alternate or less recommended media
Example
•
•
If all sections within a lesson are best as CBT,
the lesson recommendation would be CBT.
If 3 out of 5 sections are CBT and 2 are ILT,
blended would be recommended for the
lesson with alternates for total CBT and/or
total ILT
Potential reduction in efficacy displays for
alternate solutions (based on learning
domain)
Validation
•
Assessment data should be utilized as part of the
overall design strategy to validate outcomes
(Bloom, 1942)
•
Testing results can validate transference of
knowledge as well as KPL/SPL, allowing
detection/identification of faults within the
curriculum design strategy
•
Post course assessments and Fleet feedback can
validate Return on Investment (level 3 & 4)
(Kirkpatrick, 1998)
Questions?
References
Bloom B. S. (1956). Taxonomy of educational objectives: The cognitive
domain. New York: David McKay.
Bloom, B. S., Englehart, M. D., Furst, E. J., Hill, W. H., Krathwohl, D. R. (1956).
Taxonomy of educational objectives book 1: Cognitive domain. Longman,
NY: Longman.
Bloom, B. S. (1942).Test reliability for what? Journal of Educational
Psychology, 33(7), 517-526.
Clark, R. C. (2007). Developing technical training (3rd ed.). San Francisco:
Pfeiffer
Gagne, R. (1972). Domains of learning. Interchange 3(1), 1-8.
Kirkpatrick, (1998). Evaluating training programs: The four levels. San
Francisco: Berrett-Koehler