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

The MIST Program Cohort-based Blended Learning 16-months One face-to-face (F2F) weekend per semester

The Challenge To offer an engaging, collaborative, and technology-intensive graduate program for working professionals

What Didn’t Work! Individual (Isolated) Study “Students Should Know This!” The Faculty ‘Vacuum’ Research thesis

Successful Strategies 1.Learning contract 2.Tech and writing support 3.Strategic grouping 4.Linking multiple cohorts 5.Capstone project 6.Outcome portfolio 7.Collaborative faculty 8.Availability and flexibility 9.Advisor Board and industry connection 10.Annual assessment

Learning Contracts 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

The Contract

Provide Support Writing Technology

Strategic Grouping Diversity – the Spice of Life Build Group Chemistry ‘Common Enemy’ Communicate the Importance of ‘Group’

Linking Multiple Cohorts A Shared Learning Experience “So that’s a Capstone!” Mentoring “What should I expect?” “How did you do that?” “Which prof should I avoid?”

The Capstone 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

Outcome Portfolios Start in term I Update toward the end of each term Major assignments and deliverables Course level reflections Program reflection video

Connected Faculty Bi-weekly Meetings Know Your Students! Regular Communication Program Level Involvement

Accessibility and Flexibility The Software Skype Adobe Connect Google Hangout Social Networking Sites Scheduling Flexibility

Advisory Board Once a year Professional from related fields Suggestions Curriculum Recruitment Career pathways and interns

Annual Assessment 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

Data Analytics 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

Questions?