| title | Facilitator Guide |
|---|
In-Person:
- Tables for 4-6 people (collaborative seating)
- Wall space for posting flipchart sheets
- Supplies: markers, sticky notes, timer, flipchart paper
- Name tags with first names only
Virtual:
- Pre-configured breakout rooms (4-5 people each)
- Shared collaboration tool (Miro, Jamboard, or Padlet)
- Polls/surveys ready in platform
- Chat moderation plan
- You're a guide, not a guru: Your science expertise gives you credibility, but participants' experiences drive learning
- Embrace productive discomfort: Some activities may feel unfamiliar - that's intentional
- Model vulnerability: Share your own collaboration challenges when appropriate
Say: "Raise your hand if you've ever been part of a research collaboration that felt effortless and productive." [Pause for hands] "Keep your hand up if you've been part of one that was frustrating or unproductive." [Usually more hands go up]
Transition: "Today we're going to unpack why some collaborations soar while others struggle, using evidence from the science of team science itself."
Data to Share:
- 2007 study of 19.9 million papers showed teams produce higher-impact research
- Nobel Prize data: 42% of physics prizes since 2000 went to collaborations
- NIH success rates higher for multi-PI grants in many programs
Discussion Prompt: "What drives this trend toward collaboration in your field?"
Listen for: Complexity of problems, resource needs, interdisciplinary requirements, technology demands
Bridge: "But collaboration isn't automatically better - it has to be done well."
Common Failure Modes (present as bullets on slide):
- Coordination loss: Too much time spent organizing, not enough creating
- Social loafing: Some members contribute less in group settings
- Groupthink: Pressure for consensus stifles critical thinking
- Process conflict: Disagreements about how to work together
- Goal misalignment: Different objectives or success metrics
Facilitator Note: Don't dwell on failures - this sets up the solution-focused content ahead.
The IMPACT Framework:
- Interdependence: Members need each other to succeed
- Motivation: Shared purpose and individual engagement
- Processes: Clear workflows and communication protocols
- Abilities: Complementary skills and expertise
- Culture: Trust, psychological safety, inclusion norms
- Tools: Infrastructure for collaboration and data sharing
Facilitator Tip: This framework threads through the entire training - refer back to it throughout.
Instructions to Give: "Think of a research collaboration you've been part of - current or recent. Rate it on these six dimensions using a 1-5 scale, where 1 is 'major weakness' and 5 is 'major strength.' Be honest - this is for your learning."
Dimensions to Rate:
- Clear shared goals: Everyone understood what we were trying to achieve
- Complementary expertise: Team had the right mix of skills and knowledge
- Effective communication: Information flowed well, meetings were productive
- Equitable participation: All voices were heard, contributions were valued
- Conflict resolution: We handled disagreements constructively
- Resource sharing: Data, materials, and tools were accessible to team members
Facilitator Actions:
- Walk around, but don't look over shoulders
- Give 1-minute and 30-second warnings
- Model reflection by jotting your own notes
Instructions: "Form groups of 4-5. Each person shares:
- One area where your team was strongest (highest score)
- One area that was most challenging (lowest score)
- Don't name the team or people - focus on the dynamics"
Your Role:
- Visit each group briefly, listen for patterns
- Note common strengths and challenges on your notepad
- Prepare to synthesize themes in debrief
Listen for These Patterns:
- Strengths: Often include shared excitement about the problem, clear expertise divisions, strong PI leadership
- Challenges: Frequently communication breakdowns, unclear roles, data sharing difficulties, conflict avoidance
Process:
- "What themes did you hear in your groups about team strengths?"
- "What about common challenges?"
- Capture responses on flipchart/screen
- "Great - we're going to address many of these challenges directly in our time together"
Transition: "Let's start with one of the most commonly cited issues: communication."
Say: "In that last activity, how many groups mentioned communication as a challenge?" [Show of hands] "Communication issues aren't just annoying - they're expensive. MIT research shows that poor communication costs organizations an average of $62.4 million per year."
Present Framework: "Effective team communication has four essential elements - the 4 C's:"
Clarity | Cadence | Channels | Culture
"Let's unpack each one with some science behind it."
Research Basis: Hackman's research on team design shows that clarity of purpose and process predicts team success better than member characteristics.
Practical Application:
- Meeting agendas with time allocations
- Decision logs (what was decided, by whom, when)
- Action items with owners and deadlines
- Shared glossaries for technical terms across disciplines
Discussion Prompt: "What happens in your experience when roles or expectations aren't clear?"
Listen for: Duplicated work, missed deadlines, conflict, frustration
Research Basis: Gersick's punctuated equilibrium model shows teams need regular check-ins to maintain momentum and adjust course.
Practical Framework:
- Daily/Weekly: Tactical coordination (brief, operational)
- Bi-weekly/Monthly: Strategic review (longer, reflective)
- Quarterly: Relationship maintenance (team building, big picture)
- As-needed: Crisis management (rapid response protocols)
Key Point: "Consistency matters more than frequency. Better to have monthly meetings that always happen than weekly ones that get cancelled."
Research Basis: Media richness theory - different types of information need different communication channels.
Channel Selection Guide:
- Face-to-face/Video: Complex discussions, sensitive topics, brainstorming
- Phone: Quick decisions, relationship building
- Email: Documentation, detailed information sharing, non-urgent items
- Chat/Slack: Quick questions, coordination, social connection
- Shared documents: Collaborative creation, version control
Common Mistake: "Using email for everything. Email is terrible for discussions but great for decisions."
Research Basis: Google's Project Aristotle found psychological safety was the #1 predictor of team performance.
Edmondson's Definition: "A shared belief that the team is safe for interpersonal risk-taking."
Observable Behaviors:
- People ask questions without fear of appearing ignorant
- Mistakes are discussed openly as learning opportunities
- Disagreement is expressed respectfully and directly
- Different perspectives are actively sought
Key Insight: "This doesn't mean being 'nice' all the time - it means being direct and kind simultaneously."
Form Teams: "Count off 1-5, find your number group. You're going to create a communication charter that a real research team could use."
Materials: Provide charter template, example excerpts, channel decision tree
Instructions to Teams: "Imagine you're starting a 2-year collaborative research project. Create a communication charter addressing these areas:"
Charter Elements:
- Communication Values (3-4 core principles)
- Meeting Rhythms (frequency, duration, purpose of different meeting types)
- Channel Guidelines (what goes where, response time expectations)
- Decision-Making Process (how choices get made, who has input vs. final say)
- Conflict Resolution (steps for handling disagreements)
Your Role as Facilitator:
- Circulate between teams
- Ask clarifying questions: "How would this work in practice?" "What if someone doesn't follow this?"
- Keep energy up with time calls
- Look for innovative approaches to highlight
Common Sticking Points and Responses:
- "This is too rigid" → "Think of it as a default, not a rule. You can always deviate with agreement"
- "Our team is different" → "Absolutely - customize this to your context"
- "We don't have time for all these meetings" → "What's the cost of poor coordination?"
Process:
- Teams pair up and exchange charters
- Each team provides feedback using this structure:
- One strength: What works well in this charter?
- One question: What needs clarification?
- One suggestion: How could this be improved or strengthened?
Feedback Guidelines to Share:
- Be specific rather than general
- Focus on workability, not personal preferences
- Ask questions if something is unclear
Your Role:
- Monitor feedback quality - intervene if it's too vague or harsh
- Help teams stay on time
- Note particularly creative solutions for later sharing
"Take the feedback you received and make one concrete revision to your charter."
Why This Matters: Teams that practice giving and receiving feedback in low-stakes situations do better when conflicts arise.
Say: "Communication helps teams work day-to-day, but governance determines how teams make big decisions and handle authority. Let's look at what research tells us about structures that actually work."
Key Distinction:
- Management: Day-to-day operations, task coordination, resource allocation
- Governance: Decision rights, accountability structures, conflict resolution, strategic direction
Why It Matters: "Many teams focus only on management and wonder why they struggle with bigger decisions."
Core Principle: Different people lead different aspects based on expertise and interest.
Research Support: Pearce & Conger's studies show distributed leadership increases team performance in knowledge work.
Structure Example:
- Scientific Leadership: Domain expert guides research direction
- Operational Leadership: Project manager handles logistics, timelines
- External Leadership: Senior person manages stakeholder relationships
- Innovation Leadership: Creative thinker drives new approaches
Pros: Leverages expertise, develops multiple people, reduces single points of failure Cons: Can be confusing if roles aren't clear, may slow some decisions
When It Works Best: Diverse, highly skilled teams with complex projects
Core Principle: Leadership rotates based on project phase or expertise needs.
Real Example: "In the Human Genome Project, different institutions led different phases based on their comparative advantages."
Structure Example:
- Phase 1: Data collection led by field research expert
- Phase 2: Analysis led by computational specialist
- Phase 3: Dissemination led by policy expert
Pros: Matches expertise to needs, develops multiple leaders Cons: Requires smooth handoffs, can create discontinuity
Core Principle: Clear hierarchy with democratic input mechanisms.
Research Support: Tannenbaum & Schmidt's leadership continuum research shows this balances efficiency with engagement.
Structure Example:
- Principal Investigator: Final decision authority, external accountability
- Advisory Council: Representative input from all stakeholder groups
- Working Groups: Delegated authority for specific domains
Decision Process:
- Working groups develop recommendations
- Advisory council provides input and alternatives
- PI makes final decision with transparent rationale
Pros: Clear accountability, incorporates diverse input, efficient Cons: Can feel top-down if not implemented well
Core Principle: Hub-and-spoke coordination across autonomous units.
Real Example: "Think of how the Large Hadron Collider collaboration works - thousands of scientists across hundreds of institutions."
Structure:
- Central Coordination Hub: Manages overall project, standards, resources
- Autonomous Nodes: Independent teams with specific responsibilities
- Liaison Roles: Boundary spanners who connect nodes
Pros: Scales to large collaborations, maintains autonomy Cons: Complex coordination, potential for fragmentation
Key Success Factor: Strong coordination mechanisms and shared standards
Four Scenarios - Assign One Per Team:
-
Multi-institutional Clinical Trial
- 5 medical centers, 200 patients, 3-year timeline
- Regulatory compliance requirements, patient safety critical
- $2M budget, industry sponsor
-
Interdisciplinary Data Analysis Consortium
- Computer scientists, social scientists, domain experts
- Large shared dataset, multiple research questions
- Different publication norms across disciplines
-
International Field Research Collaboration
- Teams from 4 countries, remote field sites
- Equipment sharing, varying resource levels
- Different institutional policies and cultures
-
Industry-Academic Partnership
- University researchers + company R&D team
- Proprietary data concerns, different timelines
- Academic freedom vs. commercial interests
Instructions to Teams: "Design a governance structure for your scenario. Address these key elements:"
Governance Elements to Address:
- Leadership Structure: Who has authority for what decisions?
- Decision-Making Process: How are key choices made?
- Conflict Resolution: What happens when people disagree?
- Resource Allocation: How are shared resources managed?
- Credit and Recognition: How are contributions acknowledged?
Deliverable: Create a visual representation (flowchart, org chart, process diagram) that shows your governance model.
Your Facilitation Approach:
- Visit each team twice during the 15 minutes
- First visit (5-7 min): Check understanding, clarify scenario details
- Second visit (10-12 min): Push thinking with questions:
- "What happens if this person leaves the project?"
- "How do you handle a major disagreement using this structure?"
- "Where might this break down under pressure?"
Common Challenges and Responses:
- Teams default to simple hierarchy → "What are the downsides of that approach for this scenario?"
- Teams create overly complex structures → "How would new team members understand this?"
- Teams ignore the human dynamics → "What about trust, communication, relationships?"
Process:
- Teams post their governance designs around the room
- Everyone walks around and reviews all designs
- Each person gets 2 dot stickers to vote for:
- Most innovative approach
- Most practical for real implementation
Debrief Questions:
- "What patterns do you see across the designs?"
- "What creative solutions surprised you?"
- "What would make these governance models actually work in practice?"
Ask: "How many of you have been part of a collaboration where data sharing was seamless and easy?" [Few hands usually go up]
Say: "Data sharing is often the biggest practical barrier to effective collaboration. Let's look at frameworks that make it work."
Present Framework: "The FAIR principles were designed for open science, but we need to extend them for collaborative team science."
FAIR Principles:
- Findable: Team members can locate relevant data and resources
- Accessible: Appropriate permissions and access protocols exist
- Interoperable: Data works across different systems and analyses
- Reusable: Clear documentation enables future use
The '+' Addition:
- Secure: Privacy, confidentiality, and compliance protections
Common Problem: "The data exists somewhere, but no one can find it when they need it."
Solutions:
- Central registry of all project datasets with descriptions
- Consistent naming conventions for files and versions
- Metadata templates that everyone uses
- Search functionality within shared repositories
Quick Example: "Instead of 'Analysis_final_v3_JMS.xlsx', use '2024-03-15_participant-survey_cleaned_smith.xlsx'"
Key Principle: "Default to open within the team, closed to the outside, with explicit exceptions."
Access Levels:
- Full Access: Core team members, can read/write/modify
- Analysis Access: Can download and analyze, cannot modify originals
- Metadata Access: Can see what exists, request specific datasets
- No Access: Sensitive data with special restrictions
Implementation Tools:
- Cloud platforms with granular permissions (Google Drive, Box, institutional systems)
- Version control systems (Git for code, specialized tools for data)
- Access logging for sensitive data compliance
Common Failure: "Everyone saves data in their preferred format, nothing works together."
Best Practices:
- Agreed-upon file formats for different data types
- Standard variable naming across datasets
- Common coding schemes for categorical variables
- Documentation templates that everyone uses
The Documentation Imperative: "If you can't understand the data 6 months from now, no one else will either."
Essential Documentation:
- Data collection protocols and any changes over time
- Variable definitions and coding schemes
- Quality control procedures and known limitations
- Analysis scripts with comments explaining logic
Scenario: Multi-site study examining social media use and mental health outcomes among adolescents. Site A (major university) has collected data from 500 participants. Site B (smaller college) wants to access this data for secondary analysis.
Roles (5 people per group):
- Site A Principal Investigator: Collected the data, protective of participants
- Site B Researcher: Wants access for legitimate secondary research
- Site A Compliance Officer: Responsible for legal/ethical compliance
- Site B IRB Representative: Must ensure ethical standards
- Data Manager: Technical expert on security and systems
Key Constraints:
- Data includes sensitive mental health information
- Participants consented to "research by the study team and approved collaborators"
- Site A IRB approval required for data sharing
- Site B has different data security infrastructure
Instructions to Groups: "You have 15 minutes to negotiate a data sharing agreement. You must address these issues:"
Required Agreement Elements:
- What data can be shared? (raw data, processed data, aggregate data only?)
- Access controls: How will Site B access and store the data?
- Permitted analyses: What research questions can Site B pursue?
- Publication rights: How are publications handled? Authorship?
- Security requirements: What technical safeguards are needed?
- Compliance verification: How is adherence to agreement monitored?
Your Facilitation Strategy:
- Let tensions emerge naturally - don't smooth over disagreements too quickly
- Intervene only if discussion becomes personal or completely stuck
- Note common sticking points for debrief discussion
- Watch for creative solutions that balance competing interests
Common Sticking Points You'll Observe:
- Site A wants extensive oversight, Site B wants autonomy
- Publication timelines and approval processes
- Technical security requirements vs. practical constraints
- What happens if Site B violates the agreement
Debrief Questions:
- "What was hardest to negotiate? Why?"
- "What solutions did you find for balancing protection with access?"
- "How did the different perspectives (PI vs. compliance vs. IRB) create tension?"
- "What would make this process easier in real life?"
Key Learning Points to Draw Out:
- Start data sharing conversations early in collaboration planning
- Different stakeholders have legitimate but competing concerns
- Technical solutions can resolve some trust issues
- Clear agreements prevent bigger conflicts later
- Templates and institutional support make negotiations faster
Transition: "Data sharing is often where issues of fairness and inclusion become most visible. Let's talk about building teams where everyone can contribute effectively."
Research Foundation: "Three key findings from team performance research:"
- Diverse teams outperform homogeneous teams on complex problems (Page 2007)
- But diversity alone isn't enough - inclusion practices determine whether diversity helps or hurts (Nishii 2013)
- Small changes in process can have big impacts on who participates and how (Woolley 2010)
Key Insight: "Diversity is about composition. Inclusion is about behavior."
Surface-Level Diversity:
- Demographics: gender, race, age, nationality
- Disciplinary backgrounds
- Institutional affiliations
- Career stages
Deep-Level Diversity:
- Thinking styles (analytical vs. intuitive)
- Work preferences (individual vs. collaborative)
- Communication styles (direct vs. indirect)
- Risk tolerance (conservative vs. experimental)
Why This Matters: "Surface-level diversity is what we see first, but deep-level diversity often drives the performance benefits."
Allport's Contact Theory: Under the right conditions, contact between different groups reduces bias and improves collaboration.
The Right Conditions for Research Teams:
- Equal status within the collaboration context
- Common goals that require interdependence
- Intergroup contact in cooperative (not competitive) settings
- Authority support for collaborative norms
Practical Application: "This means actively creating opportunities for different team members to work together as equals on shared objectives."
Strategy 1: Structured Brainstorming
- Problem: Extroverted team members dominate idea generation
- Solution: Silent brainstorming → individual sharing → group building
Strategy 2: Devil's Advocate Protocols
- Problem: Pressure for false consensus
- Solution: Assign someone to argue alternative perspectives
Strategy 3: Multiple Communication Channels
- Problem: Some people don't speak up in meetings
- Solution: Combine verbal discussion, written input, and one-on-one check-ins
Strategy 4: Bias Interruption
- Problem: Unconscious biases affect evaluation of ideas and contributions
- Solution: Structured evaluation criteria, diverse review panels
Strategy 5: Cultural Bridge-Building
- Problem: Different professional cultures have different norms
- Solution: Explicit discussion of differences, negotiated team norms
Instructions: "Think about a current or recent research collaboration. Rate how well the team does on each inclusion indicator using a 1-5 scale."
Inclusion Indicators:
- Diverse representation in leadership and decision-making roles
- Equitable participation in meetings and discussions
- Multiple communication styles are accommodated and valued
- Different perspectives are actively sought on important decisions
- Cultural differences are acknowledged and leveraged as strengths
- Bias mitigation strategies are used in evaluation and selection processes
- Conflict resolution addresses both task and relationship issues
- Recognition and credit are distributed fairly across contributions
Facilitator Notes:
- Walk around but maintain privacy
- Notice if people seem stuck - offer to clarify any indicators
- This should be reflective, not judgmental
Partner Assignment: "Find someone you don't know well or haven't worked with closely."
Conversation Structure: Round 1 (3 minutes each person): Share assessment results
- Which areas scored highest? What makes those work well?
- Which areas scored lowest? What barriers do you see?
- Don't problem-solve yet - just understand each other's situations
Round 2 (4 minutes total): Collaborative action planning
- Choose 2-3 priority areas for improvement
- Brainstorm specific, actionable strategies
- Consider: What would you try first? What support would you need?
Facilitation Approach:
- Circulate to listen for innovative ideas
- Help pairs stay focused on actionable steps
- Note themes for whole-group debrief
Common Challenges and Responses:
- "Our team is already pretty inclusive" → "That's great! What could you share with other teams?"
- "These problems are too big for me to solve" → "What's one small experiment you could try?"
- "I'm not in a leadership position" → "What can you influence from your current role?"
Reality Check: "Research on training effectiveness shows that without deliberate implementation support, people use about 10% of what they learn in programs like this."
Why Implementation Fails:
- Return to urgent daily pressures
- Lack of organizational support
- Trying to change too much at once
- No accountability mechanisms
Pilot Approach: "Pick one practice, try it with one team, for one month."
Examples of Good Starting Points:
- Communication: Implement structured agendas for one regular meeting
- Governance: Create decision logs for one ongoing project
- Data sharing: Establish naming conventions for one shared folder
- Inclusion: Try silent brainstorming in one team meeting
Why This Works: Small wins build confidence and demonstrate value before scaling up.
Simple Metrics for Team Effectiveness:
- Efficiency: Meeting satisfaction scores, time to decision
- Innovation: Number of new ideas generated, creative solutions adopted
- Relationships: Trust levels, conflict resolution speed
- Outcomes: Progress toward goals, quality of deliverables
The Learning Mindset: "Expect that your first attempts won't be perfect. The goal is to learn and improve, not to implement flawlessly."
Scaling Principles:
- Adapt, don't just adopt: What works for one team may need modification for another
- Build champions: Find early adopters who can help spread practices
- Create systems support: Templates, training, and infrastructure
- Address resistance: Understand and respond to legitimate concerns
Common Scaling Mistakes:
- Mandating practices without buy-in
- Ignoring context differences
- Moving too fast without solidifying early wins
Instructions: "Complete this action plan for yourself. Be specific and realistic."
Template Elements:
-
One thing I'll stop doing in my research collaborations
- Example: Stop sending unclear emails that require multiple follow-ups
-
One thing I'll start doing within the next 30 days
- Example: Create a communication charter for my current project team
-
One practice I'll advocate for in my existing teams
- Example: Propose using structured brainstorming for our next planning meeting
-
My accountability partner from this session
- Name and contact information of someone who will check in with you
-
Check-in date to assess progress
- Specific date within 60 days to review how implementation is going
-
One resource I need to make this work
- Example: Template for data sharing agreements, support from my department chair
Facilitator Role:
- Circulate to answer questions and provide encouragement
- Help people make their commitments specific and measurable
- Connect people who might be good accountability partners
Process: "Would anyone like to share one commitment with the group? This can help with accountability."
Why This Works: Public commitments have higher follow-through rates.
Facilitation Tips:
- Don't pressure anyone to share
- Celebrate creative or ambitious commitments
- Note themes across commitments
- Send thank you email with session materials
- Share contact information for accountability partnerships
- Provide resource links and templates
- Brief survey on implementation attempts
- Virtual "office hours" for questions
- Share success stories and challenges
- Follow-up survey on sustained practice changes
- Advanced workshop for graduates
- Community of practice formation
Symptoms: Quiet groups, minimal discussion, brief activity outputs Interventions:
- Use smaller groups (3-4 people)
- Provide more structure and specific prompts
- Model vulnerability by sharing your own experiences
- Use anonymous input methods (sticky notes, digital polls)
Symptoms: Comments like "This is just common sense" or "We need to focus on the science" Responses:
- Lead with data and evidence
- Connect to concrete research outcomes
- Share failure stories from high-profile collaborations
- Acknowledge their expertise while highlighting collaboration complexity
Symptoms: Activities running long, content blocks getting rushed Solutions:
- Use visible timers for all activities
- Give time warnings (5 minutes, 2 minutes, wrap up)
- Have abbreviated versions of activities ready
- Cut content, not activities - the practice is more valuable
Symptoms: Same people speaking repeatedly, others withdrawing Interventions:
- Use structured turn-taking ("Each person shares one idea")
- Redirect: "Thank you, John. Sarah, what's your perspective?"
- Address privately during breaks if necessary
- Use written activities to balance participation
Symptoms: "That research doesn't apply to our field/situation" Responses:
- Ask for specific context that makes it different
- Find research from their discipline if possible
- Focus on principles rather than specific practices
- Invite them to test and report back
Symptoms: Platform crashes, connectivity issues, lost materials Preparation:
- Have low-tech backup plans for all activities
- Test technology multiple times before session
- Prepare printed materials as backup
- Designate a tech support person if possible
- Flipchart paper and markers
- Sticky notes (multiple colors)
- Timer (visible to all participants)
- Name tags
- Handout packets for each participant
- Laptop and projection capability
- Slide deck loaded and tested
- Activity templates in shared folder
- Collaboration platform set up and tested
- Contact information collection method
- Evaluation survey ready to deploy
- All activities have non-digital versions
- Key content available in handout form
- Alternative room arrangements considered
- Contact information for technical support