Using Observations to Improve the Course#
Tags continuous-improvement feedback data iterative enhancement course-design documentation quality-assurance
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Using this pattern#
The Collecting Observations pattern establishes a systematic approach for continuous improvement through structured feedback collection and analysis. Rather than relying on general impressions or anecdotal feedback, this pattern creates a data-driven framework that transforms session observations into actionable insights.
Course delivery is a complex, dynamic process where subtle details can significantly impact learning effectiveness. Without systematic observation, valuable insights are often lost, and improvement efforts may be misdirected. This pattern addresses several key challenges:
How to systematically capture and analyze course delivery effectiveness
When to implement improvements based on collected feedback
How to ensure consistent quality across different facilitators and producers
Ways to maintain course relevance over time
The observation pattern is particularly valuable during critical phases of the course lifecycle, such as launching new content, training new delivery team members, or adapting materials for different audiences. It provides the evidence base for validating learning effectiveness and identifying specific areas where design or delivery modifications would have the greatest impact.
Form#
The observation pattern follows a streamlined four-phase cycle based on the OODA Loop (Observe, Orient, Decide, Act). This structure provides a clear pathway from initial observation to meaningful improvement, ensuring that feedback translates into enhanced course quality.
1. Record (Observe)
The foundation of effective improvement is careful documentation of what actually happens during course delivery. This phase focuses on capturing observations in a structured format that facilitates later analysis. Using consistent templates helps ensure that observations are comparable across different sessions and delivery teams.
Each observation should include relevant context and impact, noting not just what happened but why it matters for learning effectiveness. Tagging observations by category (e.g., timing, engagement, technical issues) creates a taxonomy that supports pattern recognition across multiple sessions.
Evidence and metrics provide objective anchors for subjective impressions, helping distinguish between isolated incidents and systemic issues that warrant deeper attention.
2. Review (Orient)
Individual observations gain significance when examined collectively. Periodic reviews bring together observations from multiple sessions to identify patterns, trends, and connections that might not be apparent in isolation.
This analytical phase involves synthesizing related observations to understand underlying causes rather than just addressing symptoms. Considering the broader context helps determine whether an observation reflects a design issue, a delivery challenge, or an environmental factor.
Mapping dependencies between observations reveals how different aspects of the course interact, which is crucial for designing comprehensive improvements rather than piecemeal fixes.
3. Prioritize & Plan (Decide)
Not all potential improvements deliver equal value. This phase evaluates each opportunity based on its impact on learning effectiveness and the effort required for implementation.
Setting clear implementation priorities ensures resources are directed toward changes that will provide the greatest benefit. Synthesizing related issues allows for more efficient solutions that address multiple observations simultaneously.
This planning stage moves beyond identifying problems to designing comprehensive solutions that address root causes. Creating detailed action plans with clear responsibilities and timelines transforms insights into actionable improvements.
4. Implement & Validate (Act)
The ultimate value of observation comes through implementation. Executing planned changes based on observation data creates a feedback loop that validates the effectiveness of the observation process itself.
Testing the effectiveness of changes confirms whether they address the original observations and produce the intended improvements. Documenting outcomes creates institutional knowledge about what works and what doesn’t.
Gathering feedback about the changes helps refine them further, and adjusting as needed ensures continuous improvement of both the course and the observation process itself.
Design roles#
The observation pattern involves multiple roles, each contributing different perspectives and expertise to the improvement process. These roles may be performed by different individuals or combined depending on team size and structure.
Delivery Team
The delivery team serves as the primary source of observations, with direct experience of how the course design functions in practice. Their responsibilities include using structured templates to record observations during and immediately after sessions, providing clear context for what they observe, and documenting specific evidence rather than general impressions.
They play a crucial role in tagging and categorizing observations to facilitate later analysis, and in documenting both qualitative and quantitative aspects of the session experience. Their proximity to the actual delivery makes their observations particularly valuable for understanding the practical implications of course design decisions.
Course Designers
Course designers transform raw observations into design insights. They conduct regular review sessions to analyze observation patterns across multiple deliveries, identifying both common themes and outlier experiences that might reveal important design considerations.
They work to understand how different elements of the course design interact by mapping contextual factors and dependencies between observations. Their expertise in learning design helps them interpret delivery observations in the context of learning theory and best practices, synthesizing findings into a coherent picture of how the course design performs in practice.
Decision Makers
Decision makers evaluate improvement opportunities and allocate resources for implementation. They assess the relative priority of different potential improvements based on impact and effort, creating a roadmap for implementation that reflects strategic priorities.
They design comprehensive solutions that address root causes rather than symptoms, plan implementation details including timelines and responsibilities, and establish clear success criteria for evaluating whether changes achieve their intended purpose.
Implementers
Implementers bring improvements to life, executing the changes designed in previous phases. They conduct testing to validate the effectiveness of changes before wider implementation, document the results to create institutional knowledge about what works, and gather feedback from delivery teams and participants about the impact of changes.
They report outcomes back to decision makers and course designers, creating a feedback loop that informs future improvement cycles. Their practical experience with implementing changes often reveals important insights about the feasibility and effectiveness of different improvement approaches.
Examples and resources#
Our observation practice has evolved through experience, resulting in several common variations and supporting resources that help teams apply the pattern effectively in different contexts.
Common variations
Different aspects of course delivery require different observation approaches. Participant engagement level tracking focuses on indicators of attention, interest, and active participation, helping identify which course elements most effectively engage different audience types.
Time management effectiveness monitoring documents where sessions run longer or shorter than planned, revealing opportunities to refine timing estimates or adjust activity scopes. Activity completion rate documentation tracks whether participants successfully complete exercises within the allocated time, providing insights into activity design and instruction clarity.
Learning outcome achievement assessment gathers evidence of whether participants demonstrate the intended knowledge or skills following specific course components. Technical challenge reporting documents platform issues, connectivity problems, or tool limitations that impact the learning experience.
Templates and materials
To support consistent observation practices, we’ve developed standard observation forms that prompt observers to document specific aspects of session delivery. Feedback collection templates guide the gathering of participant insights in formats that facilitate analysis and comparison across sessions.
Analysis frameworks help review teams identify patterns and relationships between different observations. Sample completed patterns provide models of effective observation documentation, and best practice guides offer guidance on what to observe and how to document findings in ways that support meaningful improvement.
Practical examples
Through practical application, we’ve refined specific observation methodologies for different aspects of course delivery. Group dynamics observation methods help capture how participants interact with each other and the facilitator, revealing insights about engagement and learning experiences.
Question pattern documentation tracks the types, frequency, and content of questions asked during sessions, often revealing gaps or unclear elements in course materials. Energy level tracking approaches monitor participant and facilitator energy throughout sessions, identifying potential pacing issues or engagement challenges.
Setup and requirements#
Implementing the observation pattern requires thoughtful preparation and clear processes. Before beginning, teams should develop and prepare templates that prompt observers to document specific, relevant information while minimizing the documentation burden during delivery.
Appropriate documentation tools should be set up and tested to ensure they’re readily accessible during sessions. These might include digital forms, collaborative documents, or specialized observation software depending on team resources and preferences.
Establishing a regular review cycle creates structure for the observation process, ensuring that observations translate into improvements rather than accumulating without action. The frequency of reviews should balance the need for timely insights with the practicalities of team availability and the volume of observations generated.
A clear observation collection process helps delivery team members understand what to observe, when to document their observations, and how to format their documentation for maximum usefulness. Documentation methods should strike a balance between comprehensiveness and practicality, capturing sufficient detail while remaining feasible during the busy period of course delivery.
Analysis procedures guide how observations are reviewed, categorized, and synthesized into actionable insights. These procedures should include guidance on identifying patterns, determining root causes, and designing comprehensive solutions that address underlying issues rather than just symptoms.
Additional design factors#
Implementation Considerations
Several factors influence how effectively the observation pattern can be implemented in different contexts. Template adherence affects the consistency and comparability of observations across different sessions and delivery teams. Clear, user-friendly templates with appropriate guidance increase the likelihood of consistent documentation.
Review scheduling must balance the need for timely insights with practical constraints on team availability. Regular, scheduled reviews create accountability and ensure the observation process maintains momentum.
Priority conflicts may arise when multiple improvement opportunities compete for limited resources. Clear criteria for evaluating impact and effort help teams make informed decisions about where to focus improvement efforts.
Resource constraints affect how many improvements can be implemented simultaneously and how comprehensive those improvements can be. Teams should be realistic about capacity and prioritize improvements accordingly.
Testing thoroughness influences how confidently teams can implement changes based on observations. More thorough testing reduces the risk of unintended consequences but requires greater resources.
Feedback collection from those affected by changes provides crucial validation of whether improvements achieve their intended purpose. Building feedback mechanisms into the implementation process creates ongoing learning opportunities.
Documentation gaps can undermine the value of the observation process if important information isn’t captured or isn’t accessible when needed for decision-making. Regular audits of documentation completeness help identify and address these gaps.
Design Evolution
The observation pattern itself should evolve based on experience and changing needs. Pattern refinement processes allow teams to adapt the observation approach based on what they learn about what works in their specific context.
Template evolution ensures that observation documentation captures the most relevant information as course design and delivery contexts change. Regular review of template effectiveness helps identify opportunities for refinement.
Documentation improvements address challenges or inefficiencies in how observations are recorded, stored, and accessed. As teams gain experience with the observation pattern, they often discover ways to streamline documentation while maintaining or enhancing its value for improvement efforts.
Improvement process#
The observation pattern itself should be subject to continuous improvement. Teams should periodically evaluate the effectiveness of their observation practices and identify opportunities to enhance them.
See Continuous Improvement (CI) for additional details on how the observation pattern fits within the broader continuous improvement framework.
References#
Related Patterns: