In L&D, we call this, "Tuesday". Conflicting data is part of the job, whether it occurs in a needs analysis or an evaluation of a learning experience. Investigate, ask probing questions, get to the root of the issues at hand. It's important to remember that a lot of this material-specific feedback stems from immediate emotional response, and you're not obligated to act on all feedback, but you should review it. Remember: your goal is to improve performance and/or address gaps. If THOSE criteria have been satisfied through further evaluation, it may not be necessary to weigh the emotional responses so heavily. e.g. I hated a lot of my military training, but it still helped me do the job.

First, identify patterns in the feedback — are there common themes? Prioritize comments that enhance clarity, engagement, and learning outcomes. When creative elements clash with learner comprehension or objectives, consider adapting the design while retaining the essence of your ideas. Test your changes on a small scale before rolling them out. Flexibility and continuous refinement allow for innovation without compromising learning effectiveness. #eLearning

To navigate conflicting feedback in e-learning course design, focus on balancing creativity with learning outcomes. Prioritize feedback that aligns with instructional goals and enhances learner engagement. Identify common themes in the feedback to make data-driven decisions, while maintaining the course's core vision. Incorporate iterative testing with diverse user groups, ensuring that creativity serves pedagogy, not just aesthetics. Flexibility and a learner-first approach will help in refining the course effectively.

Let's be honest - A/B testing is rarely practical in reality. It's usually too difficult to isolate one item in a broad system as causation, and it takes too long for performance results to be measurable. Generally speaking, if feedback is around "bells and whistles", aka "clicky clicky bling bling" then remove the distractions and leaver learners to concentrate on the content. Use Mayer's Principles of Multimedia Learning to filter the feedback as that will often highlight which objections are known poor practice.