AI Assistant Instructions
Hi Everyone, I wonder if someone can help me with the AI Assistant. I'm looking to develop a UK level 2 course in Adult Social Care using the AI Assistant. I know all the units that must be included and the learning outcomes and assessment criteria for each of those units. Can I just provide that information to the AI Assistant and then it generates the content for those learning outcomes and assessment criteria? From what I can see, all I can do is provide the context of the course and then the AI Assistant determines the LOs based on that context. I have to cover everything as part of the qualification specification, so the course needs to reflect that content, not what the AI Assistant thinks it should be. Hopefully I've explained that clearly enough? Thanks in advance for your responses 😀AI Image Creation
Images requested by me from AI repeatedly fail to adjust to multiple efforts at phrasing image creation instructions in different ways each time. Also my expectations of what I consider common images in the everyday world don't seem to be used as a basis for the creation of the AI images at all. I am happy to give you specific examples after I receive your first reply.Can the AI Assistant implement character limits in CC segments?
Hello, Articulate community! Just wondering if the Storyline or Rise AI Assistant can implement character limits in CC segments. Our team abides by DCMP guidelines, which advise no more than 32 characters (including spaces) and a max of two lines per segment. I haven't tried asking the AI Assistant this myself, but if this capability exists in Storyline and/or Rise, can anyone recommend an effective prompt to use to achieve these results? If this feature doesn't yet exist, could I submit a feature request for future versions of SL and Rise? Thanks much in advance. :)Add Reasoning Prompts to Rise 360 Scenario Blocks
I’d love to see Rise 360 add optional reasoning prompts inside the existing scenario block. The current scenario interaction is useful for presenting a situation, letting learners choose a response, and showing feedback. But in many workplace scenarios, the learning value is not only in the final answer. It is in how the learner interprets the situation before deciding what to do. An optional reasoning step could help designers create scenarios where learners pause and think through the situation before selecting a response. For example, before choosing an answer, the learner could respond to prompts like: ✅ Signal What information actually matters? 🧭 Context What background details help explain the situation? ⚠️ Noise What information might distract from the real issue? 🔎 Verify What should the learner check before deciding? This could be especially useful for customer service scenarios, safety decisions, compliance judgment, leadership conversations, troubleshooting workflows, operational readiness, and manager enablement. A few possible features: Optional reasoning prompt before answer choices Sortable information cards Confidence rating before submitting Coaching-style feedback Debrief screen that explains the reasoning behind the best choice AI Assistant support for drafting reasoning prompts and feedback This would make the existing scenario block more useful for judgment practice, not just answer selection. Curious if others would use this. Would reasoning prompts be more helpful as part of the existing scenario block, or as a separate Rise interaction type?Feature Request: Support XLIFF Import into Localization Course Stacks
The new Localization and Course Stack features in Rise 360 are a significant step forward for managing multilingual learning experiences. The ability to maintain a single course with multiple language variations greatly simplifies administration, updates, and governance. However, many enterprise organizations rely on established localization workflows that use Translation Management Systems (TMS) such as Smartling, Phrase, MemoQ, Trados, and others. These systems contain years of translation memory, approved terminology, and linguistic review processes that are critical for maintaining quality, consistency, and cost efficiency across global content. Currently, organizations must choose between: Using Course Stacks and translating within Articulate's localization workflow, or Maintaining external XLIFF-based translation processes and managing separate language courses. This creates a barrier to adoption for enterprise customers who would otherwise benefit from Course Stacks. Suggested Enhancement Allow course stack language versions to be populated through XLIFF import in addition to Articulate's native translation workflow. Example workflow: Author creates a source-language Rise course. Author creates a Course Stack and adds target languages. Author exports XLIFF files for each language. Translations are completed in the organization's preferred TMS. Completed XLIFF files are imported directly into the corresponding language versions within the Course Stack. Future course updates can continue to use standard XLIFF round-trip workflows while maintaining the benefits of a single Course Stack. Benefits Enterprise Adoption Many large organizations cannot abandon existing localization infrastructure, translation memory, and vendor workflows. Supporting XLIFF import would make Course Stacks viable for enterprise-scale deployments. Reduced Translation Costs Translation memory can be leveraged for previously translated content, reducing both translation costs and review effort. Higher Translation Quality Organizations can continue using approved terminology databases, linguistic QA processes, and professional review workflows. Easier Course Maintenance Teams gain the administrative advantages of Course Stacks without sacrificing established localization practices. Increased Platform Stickiness Supporting enterprise localization workflows would make Rise 360 a stronger solution for global organizations managing content in multiple languages. Summary Course Stacks solve an important content management challenge, but the lack of XLIFF integration limits adoption among organizations with mature localization programs. Supporting XLIFF import and export directly within Course Stacks would allow enterprise customers to leverage both modern multilingual course management and their existing translation ecosystems.
