Practical Strategies in
Blended Learning
Lessons Learned from the
Master’s of Instructional Science & Technology (MIST)
Bude Su, PhD.
Karen Wisdom, M.A.
California State University – Monterey Bay
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Cohort-based
Blended Learning
16-months
One face-to-face (F2F) weekend per semester
The MIST Program
http://itcd.csumb.edu/master-science-ist
To offer an engaging,
collaborative, and
technology-intensive
graduate program for
working professionals
The Challenge
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Individual (Isolated) Study
“Students Should Know This!”
The Faculty ‘Vacuum’
Research thesis
What Didn’t Work!
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Learning contract
Tech and writing support
Strategic grouping
Linking multiple cohorts
Capstone project
Outcome portfolio
Collaborative faculty
Availability and flexibility
Advisor Board and industry connection
Annual assessment
Successful Strategies
I understand that I will need to devote
16+ hours a week
My family also understands I will need
to devote 16+ hours a week
Learning Contracts
The Contract
• Writing
• Technology
Provide Support
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Diversity – the Spice of Life
Build Group Chemistry
‘Common Enemy’
Communicate the
Importance of ‘Group’
Strategic Grouping
• A Shared Learning Experience
• “So that’s a Capstone!”
• Mentoring
• “What should I expect?”
• “How did you do that?”
• “Which prof should I avoid?”
Linking Multiple Cohorts
• Term I
• Look at previous cohorts’ work
• Pitch ideas
• Term II
• Preliminary proposal
• Sketch out the project
• Term III
• Full Proposal
• continue project development
• Term IV
• Complete design and development
• Testing and evaluation
The Capstone
• Start in term I
• Update toward the end of
each term
• Major assignments and
deliverables
• Course level reflections
• Program reflection video
Outcome Portfolios
• Bi-weekly Meetings
• Know Your
Students!
• Regular
Communication
• Program Level
Involvement
Connected Faculty
• The Software
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Skype
Adobe Connect
Google Hangout
Social Networking Sites
• Scheduling Flexibility
Accessibility and Flexibility
• Once a year
• Professional from related fields
• Suggestions
• Curriculum
• Recruitment
• Career pathways and interns
Advisory Board
• University requirement
• Student learning outcome
assessment
• Involve all faculty in the program
• Assessment rubrics
• Random sampling of student
work
• Each sample reviewed by
multiple faculty
• Analysis and report
• Recommendations
• Implementation
Annual Assessment
• Track student activities in CMS
• Access/Engagement level (# of file/pages viewed)
• Correlate CMS data with course grade
• r=.53 (# of viewed/click vs. course grade)
• r=.42 (forum vs. course grade)
• Access time
• Virtual office hour
• Work schedule
Data Analytics
Questions?