Upcoming changes in Adobe Learning Manager

Often consume video content in long sequences.

Expect a curriculum‑style experience where the system clearly indicates the next episode/module.

Reinforces the guided nature of the journey.

Minimizes drop‑off between modules.

Learners must complete a strict sequence of modules.

Authors often disable TOC to avoid skipping.

Confirms to learners that they are following the correct sequence.

Makes it less likely that they misinterpret the Next action and exit early.

Updated labels and responsive behavior ensure navigation remains understandable without relying on tiny close icons or hidden controls.

This is important for customer education, gig workers, or frontline learners who may access content in short sessions on mobile devices.

The Zoom Connector now allows more than one VILT session at the same date/time to be created from ALM.

The scheduling logic no longer enforces a “one Zoom meeting at a time” constraint at the account/connector level.

Administrators and authors can configure overlapping VILT sessions (for example, regional classrooms, parallel tracks, or repeated sessions for different partner groups) without workarounds.

Zoom meetings are now created using the instructor’s email address, instead of the Zoom super admin email.

Each instructor’s Zoom account can host its own meetings in parallel with other instructors, subject to the limits of the existing Zoom plan.

Only one instructor per meeting is still supported.

If an instructor’s email is later updated in Adobe Learning Manager, existing meetings remain associated with the original email used at creation.

Authors had to manually create Zoom meetings outside ALM and then paste the Zoom join URL into the course instance configuration.

This was error‑prone and did not benefit from connector features like attendance tracking.

All sessions can be created directly from the ALM UI using the Zoom Connector, even if they overlap in time.

Session lifecycle (creation/cancellation) continues to be managed centrally via integration.

Run multiple Zoom‑based virtual classrooms at the same time (for example, parallel tracks at a virtual summit, regional cohorts, or separate partner training sessions).

Avoid bottlenecks that previously forced admins to serialize sessions or rely on manual Zoom management.

Manual creation of Zoom meetings outside of Adobe Learning Manager.

Copy‑paste of Zoom URLs into each course instance for overlapping sessions.

Risk of mis‑configured links, wrong meetings being attached, or missed attendance tracking.

Each instructor can operate within their own Zoom license limits.

Organizations can use their existing Zoom provisioning model (one account per trainer, per BU, etc.) while still integrating fully with Adobe Learning Manager.

It avoids the single‑point bottleneck of using a shared super‑admin Zoom user for all sessions.

Configure multiple Zoom‑based sessions in the same time slot (for different tracks or topics).

Manage all of them as VILT modules under Adobe Learning Manager’s courses and Learning Paths.

Provide learners a unified experience while the connector handles all underlying Zoom meeting creation.

Run separate Zoom sessions for EMEA, APAC, and Americas at overlapping times to match local working hours.

Avoid forcing a single global time slot or manual Zoom setup for additional cohorts.

Schedule parallel onboarding sessions or role‑based breakouts (for example, separate Zoom rooms for developers, admins, and business stakeholders) in ALM.

Keep all sessions within ALM’s VILT model for reporting and compliance purposes, rather than partially transitioning to unmanaged Zoom meetings.

Learner app (course card or course details).

Administrator and author views when previewing as a learner.

See who authored the course, even when it is acquired via a shared catalog.

Avoid the generic and unhelpful “External Author” label.

The same course appears with consistent author branding across accounts.

The learner experience is aligned with expectations from the primary account (for example, seeing “Cloud Academy Team” instead of “External Author”).

A main account that owns the canonical courses, and

Peer accounts that acquire content via shared catalogs.

Shared courses now display the correct enterprise author’s name in peer accounts.

The enterprise’s internal support load is reduced because learners and local admins know who to contact.

The owning BU can be identified in the author field across all consuming accounts.

Local L&D admins can quickly see whether a course is maintained locally or by another BU, and collaborate accordingly.

The Learner LO APIs (for example, the endpoints that return learning objects to the learner experience and to external platforms) now include the LO expiry date (the auto‑retire date configured for that learning object).

This field is returned as part of the LO entity in responses such as:

• Get Learning Object (LO details).

• LO data used to populate learner home, catalog, and search results.

The field complements the existing completionDeadline that already exists at the instance level; the new field is specifically the LO‑level auto‑retire date.

search APIs or

search‑driven catalogs and suggestions to construct learner views.

Show “Expiring on {date}” or “Expiring soon” labels on course cards and detail pages.

Communicate with urgency more clearly, so learners prioritize training that is about to retire.

Highlight courses that are still valid vs. ones about to be retired.

Help learners avoid enrolling in trainings that will no longer be available or valid in the near future.

“By when must I finish this instance?” (completion deadline).

“Until when is this training offered?” (auto‑retire/expiry date).

Avoid learner confusion about whether a training is being phased out.

Drive learners toward the most current, long‑lived offerings.

Hide or de‑emphasize content that is close to retirement.

Build “Last chance to complete” campaigns.

Selecting a language.

Uploading the language‑specific file for that language within the same Job Aid entity.

Less confusion about which version to open.

Less risk of accessing out‑of‑locale or outdated copies.

Product reference sheets.

Process checklists.

Support playbooks

Product cheat sheets

Integration guides

Support workflows

Each partner sees the localized version without being forced to choose between language‑specific entries.

Marketing and enablement teams can manage one Job Aid per topic across all locales.

Cohort-based enablement program: In this program, each week unlocks a new module. The content for Week 1 is available immediately, while Week 2 is visible but cannot be started until a specified date. Week 3 follows the same gating process. Learners can see the entire learning path, but the system controls when they can actually begin each step.

Time‑bound product or campaign training: Marketing or product teams may create a training module that should only be accessed while a campaign is active or when a specific version of a product is still available. This designated start window ensures that learners don’t begin a module about a discontinued product version after the specified end time.

Assessment or exam environments: Organizations can open a module (such as a test) for a short, well‑defined window (for example, “you may start the exam anytime between 9:00 and 12:00 on a given date”). Learners cannot begin the exam outside that window, which supports fair scheduling across time zones and cohorts.

Sets the player language accordingly.

Launches the corresponding language variant of the module, when multi‑language content is configured.

Consistent language experience across systems: When a learner selects a language in the external portal, that choice is immediately reflected in ALM. This ensures that learners don’t face any mismatch between the language of the portal and the course. As a result, they won’t have to search for a language switch within the player.

Language‑specific reporting: In their platform, language selection is consistent with ALM, which enhances the accuracy of their analytics and learner tracking. This alignment also supports configurations where ALM’s own language controls are intentionally disabled or hidden in the Fluidic Player for specific courses. In these cases, the external platform serves as the single source of truth for language.

A significant use case involves large enterprises utilizing LTI-based integrations. Learners first enroll and select a language on the platform. They then launch ALM training sessions through LTI. With this enhancement, when a learner selects Spanish, the ALM module automatically opens in Spanish. This means that learners don’t need to adjust the language settings in ALM. Furthermore, language-based reporting remains consistent with what learners see and experience in ALM.

Another application is the delivery of headless course experiences within a customer or partner portal. In this setup, the portal may embed ALM content using an iframe, while all navigation and language user experience (UX) are managed outside of ALM. By utilizing custom LTI parameters, the portal can ensure the ALM player is displayed in the correct language and that any unnecessary user interface elements (such as the table of contents and navigation buttons) are hidden. This allows learners to perceive a single, cohesive application rather than a disjointed collection of tools.

This is beneficial for organizations that conduct large-scale training in multiple languages using another LMS or learning platform. They can standardize their use of that platform for managing learner profiles, selecting locales, and presenting catalogs. Meanwhile, ALM serves as a reliable content and tracking engine, respecting the language preferences and user interactions specified by the external system during each LTI launch.

The Reviewer (instructor or manager) evaluates the learner according to the configured checklist type:

• Selecting Yes/No.

• Choose scores on the defined scale.

The Checklist report is updated to include, for questions with different weightage:

• The maximum score for each question.

• The score achieved by each learner for that question.

Richer, more realistic assessments: Instructors can reflect real‑world priorities by giving more points to critical behaviors and fewer to minor ones, while still using a checklist workflow suited to observed or practical tasks.

Total‑score‑based pass/fail: Evaluations can be based on the overall percentage score, not just how many questions pass a threshold, aligning more closely with typical competency or grading schemes.

Better reporting: Updated checklist reports expose max score and achieved score per question, allowing program owners and quality teams to identify specific weak spots and refine training or evaluation guidance.

Enterprise skill assessments: Engineers are assessed via practical, scenario‑based checklists where certain diagnostic or communication steps must carry more weight than cosmetic or low‑risk steps. Weighted questions and total‑score pass criteria make these assessments more credible and predictive of real‑world performance.

Safety and compliance observations: In healthcare, manufacturing, or field service, critical safety steps can be given higher max scores, ensuring that missing a safety‑critical action has a larger impact on the total score than missing a minor procedural step.

Coaching and calibration: With max and achieved scores per question in the report, managers can see exactly where learners underperform and calibrate instructors on how to score consistently.

All learner‑facing modules (SCORM, PDFs, HTML, etc.) can be provided in multiple content languages, allowing learners to choose the language they prefer.

In a checklist module, reviewers (instructors/managers) evaluate learners based on the questions defined within that checklist.

Authors can now add checklist questions in all languages selected at the course level.

For each checklist:

• The author is expected to provide equivalent question text in every content language in which the course exists.

• Authors are responsible for ensuring that the meaning of each question is consistent across languages.

Reviewers will see checklist questions and evaluation UI in their selected content language.

When a question is evaluated in one language:

• The evaluation (score, Yes/No, status) is logically the same across all languages. It’s a single checklist with multiple language views, not separate checklists per language.

An administrator or reviewer running the report in each language sees the localized question names for that language.

The underlying responses and scores remain the same; only question labels are translated.

Better reviewer experience: Reviewers can work entirely in their own language, reading questions and recording evaluations without language barriers.

Regulatory and policy alignment: In regions with language equality requirements (for example, Dutch/French in Belgium), checklists can now meet the same standards as other learning materials, reducing compliance risk.

Consistent evaluation logic: While the text is localized, evaluation and scoring are shared across all languages, ensuring that results are comparable and centrally managed.

Multi‑country franchises that operate in multiple languages can deploy a single course and checklist while still providing localized reviewer experiences in each territory.

Any global enterprise with local instructors (for example, EMEA, LATAM, APAC) can have reviewers work in their local language while sharing the same global checklist design and reporting.

Evaluate a checklist for each learner, question by question.

View results and re‑evaluate learners who have failed.

Enable or disable commenting capability for reviewers.

Decide whether the reviewer’s name should be shown to learners along with comments.

Reviewers (instructors/managers) can add optional comments while evaluating a checklist.

They can choose whether comments are visible to learners, based on the checklist settings.

The Checklist report gains a new column for reviewer’s remarks, capturing the comment provided during evaluation.

Learners receive notifications (in‑platform and email) whenever a checklist evaluation occurs. These notifications include:

• The comment and

• The reviewer’s name, if those were configured to be visible.

Richer, coach‑like feedback: Numeric scores are supplemented with contextual remarks, making checklists a more effective tool for coaching, not just compliance.

Traceability and auditability: Organizations gain a persistent record of who evaluated whom, when, and what they said, which is important in regulated environments and high‑stakes roles.

Better learner engagement: Learners receive clear guidance linked to specific evaluations, which improves their understanding of expectations and subsequent steps.

Organizations with regulated environments can use comments to document clinical judgment or procedural feedback for staff who are being observed in the field.

Aviation and ground‑handling organizations can attach detailed notes on operational performance, safety practices, and customer‑facing behavior, turning a checklist into a structured debrief tool.

In mentoring and SME evaluation, instructors can capture nuanced observations that wouldn’t fit into a score alone, for example, “handled escalation well but needs to improve time management” or “excellent troubleshooting flow; missed a documentation step.”

Authors can configure attempts at course level (applied to all quiz‑bearing modules in the course) or at module level (per quiz module).

Attempts can be:

• A specific number (for example, 3 attempts), or

• Infinite attempts, controlled at LMS level.

When a learner consumes a module through the Fluidic Player and then closes the player or completes the module, that session is treated as a single LMS attempt.

Each LMS attempt is captured in the L2 quiz report as a new row.

When uploading content into the Content Library, authors can now indicate that a specific content file has multiple attempts embedded within it.

This is a per‑content setting that tells ALM to treat attempts defined inside the content as the source of truth.

The module will derive its attempts from the content, not from LMS MQA.

Learners will see one LMS‑level attempt only:

• The course overview and module view will not expose an LMS “re‑attempt” button for that module.

• Attempt handling (for example, re‑tries within the quiz) is governed by the content itself.

Each internal quiz attempt configured in the content appears as its own row in the L2 quiz report, like how LMS‑level attempts are represented today.

The format of each row remains the same as existing multi‑attempt rows in L2 reporting (same columns, structure, and semantics).

This gives a consistent reporting experience:

• Whether attempts are controlled by LMS MQA or by the content, the L2 quiz report shows one row per attempt.

Accurate attempt history for SCORM quizzes where attempts are controlled internally by tools like Articulate, without forcing LMS‑level MQA configuration on top.

Cleaner learner experience: for content‑controlled attempts, learners see a single slot at the LMS level and don’t need to interact with LMS re‑attempt controls; all re‑tries are handled within the quiz UI they already know.

Flexible architecture: Users can choose whether ALM MQA or content‑level attempts should drive behavior per module, depending on how their content was authored and how they prefer to manage attempts.

Consistent reporting model: downstream consumers of the L2 quiz report can treat each row as “one attempt,” regardless of where the attempt logic originates.

Organizations using Articulate SCORM can keep self-contained quiz logic within the SCORM package while achieving accurate attempt-level reporting in ALM without extra LMS configuration.

Organizations that use vendor-supplied SCORM content can avoid the need to modify or implement additional attempt and retry logic with LMS-level MQA.

Course instance enrollment,

Session attendance, or

Enrollment + attendance together

Instructors will be able to generate QR codes at the session level for:

• Enroll in instance: Learners scan to enroll into the instance that includes the current session.

• Mark session attendance: Learners scan during/after the session to record attendance for that specific session.

• Enroll in instance + mark session attendance : A combined QR for walk‑ins who are not yet enrolled and need their attendance marked in one step.

Instructors can export the QR codes they need based on the scenario (enrollment, attendance, or both).

Course name

Instance name

Session name

Instructor autonomy: Instructors no longer need to wait for admins to create QR codes. They can generate them directly for each session, improving agility and reducing coordination overhead.

Better classroom logistics: For walk‑in or on‑site audiences (such as field workers, shop‑floor staff, or external attendees), instructors can manage enrollment and attendance on the spot using QR codes.

Reduced admin workload: Admin teams can focus on configuration and governance instead of handling routine QR code generation requests for every session.

Organizations running large volumes of on‑site sessions (for example, product training for professionals) can empower instructors to print session‑specific QR codes that enroll and mark attendance with one scan.

In retail, manufacturing, and healthcare training, where learners often join sessions directly from the floor or without pre-enrollment, an “Enroll + Attendance” QR code can be placed at the door. This allows learners to self-serve their enrollment and attendance via their phones.

Training events for partners or customers allow the on-site trainer to easily adapt to changes in the room, additional sessions, or extra attendees without needing to consult the administrator for new QR codes.

Only the ALM TOC will be displayed on the left side of the player.

Captivate’s own TOC will be hidden when the module is played within ALM.

This removes duplication, ensures a single source of truth for navigation, and frees up screen real estate.

The ALM TOC will show green tick marks (or equivalent visual cues) indicating slide‑level completion.

As learners progress through Captivate slides, the ALM TOC reflects which slides have been completed, aligning with learner expectations for modern course players.

The player controls will adapt based on slide type:

• For video slides:

  • Show a time progress bar, reflecting video playback.

For non‑video slides:

• Display slide navigation controls (next/previous slide, etc.) instead of a non‑functional time bar.

  • This avoids showing irrelevant or non‑working controls on certain slide types.

The separate module navigation bar (ALM) and course navigation bar will be merged into a single, intuitive bar.

This unified navigation:

• Clearly distinguishes moving through the Captivate module vs. moving back to course/module level.

• Reduces confusion caused by multiple bars with overlapping purposes.

Notes will be linked to slide numbers rather than timestamps.

This change:

• Fixes export failures caused by missing or incorrect timestamps.

• Ensures notes can be exported consistently as PDFs, with a reliable mapping between notes and the slide context they belong to.

Cleaner, single‑player experience: Learners interact with one TOC and one navigation model, reducing confusion and cognitive load.

Accurate completion and progress indications: Slide‑level ticks and contextual controls help learners understand where they are and what’s left.

More robust note‑taking and exports: By tying notes to slides instead of fragile timestamps,users regain a reliable notes‑to‑PDF workflow, even with slide‑based Captivate content.

Preserved author workflow: Authors retain the simplicity of Captivate’s direct publish to ALM, while learners get a modern, integrated playback experience without extra authoring burdens.

Enablement programs that rely on Captivate for interactive simulations can deploy content into ALM, ensuring that navigation, completion tracking, and notes function consistently for learners.

Organizations using Captivate as their main content authoring tool can maintain one-click publishing and avoid confusing double TOCs and non-functional controls for learners.

Organizations that rely on notes exported from Captivate content in ALM (for coaching, compliance, or records) can access the following:

• Notes link correctly to slides.

• PDFs are generated as expected.