How mentorAI Integrates with Blackboard

mentorAI is an AI-driven educational platform that can be installed in Blackboard Learn using the LTI 1.3 Advantage standard. Once set up, students and instructors launch mentorAI activities directly from their Blackboard course (with single sign-on and secure context sharing). When a user clicks a mentorAI link in Blackboard, the system initiates an OIDC login redirect to mentorAI. After authenticating, Blackboard generates an LTI launch request by posting a signed JWT (id_token) back to mentorAI. This JWT contains the user’s identity, role (student or instructor), course and resource IDs, and other launch context. mentorAI verifies the token (using Blackboard’s public JWKS) and then displays the requested content (for example, an AI tutor chat or assignment) to the user. Under the covers, Blackboard and mentorAI exchange only the agreed fields via OAuth2 and JWTs, so no extra credentials are needed by students. In practice, this means a student clicks “Launch mentorAI” and is immediately in the AI assistant interface (no separate login), while the instructor sees the activity appear as a normal course item. Behind the scenes, mentorAI can also sync class data and grades. Using the LTI Names and Roles provisioning service, mentorAI can request the current roster and roles for the course – so it knows all enrolled students and who is the instructor. Likewise, mentorAI can use the LTI Assignment and Grade services (Score Service) to create or use a gradebook column and post student scores. Blackboard then records these scores in the Grade Center column tied to the mentorAI placement. By default those grades are auto-posted to students, though mentorAI can set the gradesReleased flag to delay visibility if desired. All of these exchanges use LTI’s OAuth2-based APIs, ensuring secure, standards-compliant data flow. Instructors can embed mentorAI throughout their course via LTI Deep Linking. From the Blackboard content editor, an instructor can “Add External Tool” or use the mentorAI content picker (if configured). This launches a deep-linking session: mentorAI presents a selection UI where the instructor chooses one or more AI-driven modules or resources. mentorAI then returns corresponding links or iframe embeds back to Blackboard, which appear in the course outline or page. For example, an instructor might select a “Study Tips Chatbot” or an AI-generated quiz from the mentorAI interface; Blackboard then places that item into the module just like any other content. Students can later click those embedded mentorAI items and engage with them without ever copying URLs or entering extra passwords. In effect, mentorAI activities live inside Blackboard course content.

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Key integration highlights:

• LTI 1.3/OIDC Launch & JWT Security: mentorAI is registered as an LTI 1.3 tool provider. Blackboard initiates an OpenID Connect login, then sends a signed JWT (id_token) containing the launch details (user, course, link) to mentorAI. No user credentials are exposed; the token is validated by mentorAI using Blackboard’s public keys. This provides secure single sign-on.

• Deep Linking Content Embedding: With Blackboard’s Deep Linking support, instructors browse mentorAI’s library within a dialog and add selected AI activities to their course.This means mentorAI content can be embedded in modules, assignments, or discussions as just another course resource (users never leave Blackboard to access it).

• Roster Sync (Names & Roles): mentorAI uses the LTI Names and Role Provisioning API to retrieve the current course roster (all enrolled students, instructors, and their roles). This ensures mentorAI knows who’s in the class (for grouping, reports, etc.) without requiring manual roster uploads.

• Grade Passback (LTI Score Services): If a mentorAI activity is graded, the tool employs LTI’s Assignment & Grade services to return scores. mentorAI obtains an OAuth2 token (from Blackboard’s token endpoint) and POSTs each student’s score. Blackboard then auto-accepts these into the Grade Center column for that MentorAI placement. (By default grades are immediately visible to students, but mentorAI can control release with the gradesReleased attribute.)

• Flexible Tool Placement: Administrators can expose mentorAI in different ways – for instance as a Course Content tool or a Deep Linking content tool. Instructors see mentorAI listed in the “Build Content” or “Tools” menu. No secret URLs or keys are needed by instructors; they simply click “mentorAI” by name to launch it.

• Seamless User Experience: Because mentorAI uses LTI, users enjoy a cohesive experience. Students click a mentorAI link and immediately interact with the AI tutor (no additional login). Instructors add mentorAI items just like any other course resource. All data (submissions, scores, etc.) flow through Blackboard’s normal channels, so mentorAI feels like a native LMS feature.

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Detailed Integration Workflow

1. Register mentorAI as an LTI 1.3 Tool: A Blackboard administrator goes to *Administrator *▶ *LTI Tool Providers* and chooses “Register LTI 1.3/Advantage Tool.” They enter mentorAI’s registration info (issuer, OIDC Login URI, Redirect URIs, public JWKS URL, etc.) as provided by MentorAI’s documentation. This establishes the security “contract.” Blackboard then provides an Issuer URL and Client ID (application ID) back to mentorAI, along with an OAuth2 token endpoint to use for LTI services. 2. Configure Placements: After registration, the admin creates tool *placements*. For example, they may add a Deep Linking Content Tool placement (allowing instructors to browse mentorAI content) or a Course Content Tool placement (appearing in the *Build Content* menu). In each placement, the admin can enable grading. When grading is enabled, Blackboard knows to accept mentorAI’s scores into the Grade Center. These placements make mentorAI appear in the course tool lists and menus for instructors. 3. Instructor Embeds mentorAI Content: In a course, the instructor adds mentorAI just like any LTI tool. For deep linking, they might click “Add Content ▶ External Learning Tools” and choose mentorAI, which opens mentorAI’s UI. Here the instructor selects AI-driven modules or assignments to include. mentorAI returns one or more content item descriptors to Blackboard (via an LTI Deep Linking response). Blackboard places these links/embeds into the course page or module. For a course content tool placement, the instructor could also click “Build Content ▶ mentorAI” directly, which launches mentorAI for content selection. In all cases, mentorAI content ends up inserted into the Blackboard course. 4. User Launch & LTI Handshake: When a student or instructor clicks a mentorAI item in Blackboard, the LTI launch begins. Blackboard first redirects the browser to mentorAI’s OIDC endpoint (including a login_hint, target_link_uri, etc.). mentorAI validates the request (often via a 3rd-party login flow) and then posts back to Blackboard’s authentication URL with response_type=id_token. Blackboard receives this and then constructs the LTI launch request: it creates a signed JWT (id_token) containing claims such as iss (issuer), aud (client ID), sub (user ID), roles, context, and the target_link_uri. Blackboard auto-submits this JWT to mentorAI’s launch URL via an HTML form POST. mentorAI verifies the JWT signature (using the kid in the header and Blackboard’s JWKS) and ensures the state matches to prevent CSRF. Once verified, mentorAI reads the payload: it knows exactly which user launched, in which course, and which mentorAI resource or activity to show. 5. mentorAI Session: mentorAI loads the requested AI activity or chat. It uses the user’s role from the launch to customize the interface (for example, an instructor might see editing options while a student sees an interactive assignment). The user interacts with the AI tutor or completes the task. Throughout this session, mentorAI can call the Blackboard services it needs via OAuth2. For example, mentorAI can fetch the course roster by calling the Names & Roles API (using the access token obtained from Blackboard). This might be used for class-wide reports or group assignments. 6. Grade/Score Return: If the mentorAI activity is graded, mentorAI uses the LTI Gradebook services. It takes the line item (either declared via deep linking or created via the *LineItems* service) and posts a score to the corresponding Result endpoint for each student. To do this, mentorAI first requests an OAuth2 access token from Blackboard (using the OAuth2 Token URL from step 1). With the token, it calls the LTI Score Service endpoint and sends the score JSON (including userId and scoreGiven). Blackboard verifies the token and saves the score into the gradebook column associated with that mentorAI placement. By default, Blackboard automatically displays the returned score to the student. mentorAI can include the gradesReleased=false flag to hold scores for instructor review if desired. This ensures all grading flows back into Blackboard without manual export or upload. 7. User Experience & Completion: Finally, students see their mentorAI assignment or activity in Blackboard just like any other. The grade (and any feedback) appears in the Grade Center. Instructors can view reports in mentorAI’s interface and know that those records align with Blackboard’s roster. Because the entire exchange uses LTI 1.3/OIDC and OAuth2, all transfers are secure and standards-based. In effect, mentorAI becomes a native part of the course content: no extra logins or separate accounts are needed, and data like grades and enrollments stay synchronized. Students click *launch*, get the AI-powered tutoring or assessment, and move on – everything feels integrated in the Blackboard environment

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Conclusion

This end-to-end workflow shows how mentorAI’s Blackboard integration delivers a seamless experience: instructors simply place mentorAI links in their courses, and students access advanced AI learning tools without leaving Blackboard. At the same time, institutional data flows (user identity, enrollments, scores) are managed automatically via LTI 1.3 Advantage, giving both convenience and security. Learn more at [https://ibl.ai](https://ibl.ai)