Knowillage Releases Adaptive Learning Development Tool for Canvas

Knowillage Systems has released Knowillage LEArning Path (LeaP), a personalized and adaptive learning development tool for the Instructure Canvas learning management system (LMS).

Knowillage LeaP is integrated with Canvas using the Canvas External Tools extensions, so teachers can use Knowillage LeaP to create personalized learning paths and assessments for their students using their existing course content and outcomes in Canvas along with openly available educational materials.

Knowillage LeaP uses a semantic engine that simplifies the process of mapping learning materials to objectives, according to the company. Teachers select the desired learning outcomes in Canvas. The Knowillage LeaP semantic engine then automatically selects relevant content from the existing materials, and the teacher can tweak the selection of materials as needed.

The tool offers pre- and post-tests to assess student mastery of material. Knowillage LeaP can then use those assessment results to deliver appropriate learning paths for each student. The test results themselves are recorded in the Canvas gradebook.

The Knowillage LeaP recommendation engine suggests the most effective learning paths through each course's materials, and its activity and feedback engines use objective results to identify the most effective learning materials and adapt the learning paths for each student.

According to a prepared statement from Bill Bilic, founder of Knowillage Systems, Knowillage LeaP "easily connects to existing platforms, uses existing content without the need to modify it, and delivers adaptive learning paths custom made for each student."

Key features of Knowillage LEArning Path include:

  • Creation of dynamic assessments using questions from the Canvas LMS;
  • Integration with Canvas gradebook;
  • Semantic engine that simplifies the process of mapping learning materials to objectives;
  • Support for importing questions into Knowillage LeaP;
  • Pre- and post-tests;
  • Adaptive learning paths based on student assessments;
  • Support for open educational resources; and
  • Support for internal or external assessment tools.

Further information about Knowillage LeaP is available at knowillage.com.

About the Author

Leila Meyer is a technology writer based in British Columbia. She can be reached at [email protected].

Featured

  • robot hand holding stacks of coins

    Designing AI Systems for Financial Aid

    Financial aid offices have been slow to adopt AI, risking technological stagnation at a critical early student touchpoint. Systematic AI integration can improve student experiences and strengthen institutional positioning.

  • digital brain with network connections

    Microsoft Moving to Internally Developed AI Models in Office Apps

    Microsoft is reportedly using its own in-house artificial intelligence models to handle some workloads in Excel and Outlook, offering new evidence that the company is moving its AI strategy beyond model development and into large-scale cost reduction.

  • woman

    AI Giants Back Nonprofit Focused on Workforce Transition

    The AI industry's biggest names are investing in more than just models and infrastructure — they're focusing on workforce readiness. OpenAI, Anthropic, Microsoft and Amazon are backing Raise US, a new nonprofit that aims to raise $1 billion to help American workers prepare for an AI-driven economy.

  • woman surrounded by virtual hologram icons

    Beyond AI Adoption: Designing Learning for an Age of Abundant Intelligence

    Higher education was designed for a world in which access to knowledge, expertise, feedback, mentorship, and authentic learning experiences were inherently scarce. By making many forms of intelligence increasingly abundant, AI is inherently redefining the existing paradigm.