CPM Media Selection Process and Potential Future Software Capabilities 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 – 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), 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