Assessment of Social Annotation Tools Hypothesis and Perusall

Project Summary & Background

Social annotation is a collaborative means of shared thinking and collective markup. With digital social annotation, users engage directly with the material, usually within the margins of a document. While most commonly used for digital documents, social annotation can also include the markup of images, videos, and audio files. It allows readers to share their thoughts and questions and discuss points of interest or confusion in order to deepen their understanding, foster community and connection, and support critical reading skills.

Academic Technology Initiatives (ATI) undertook an assessment of two solutions that have emerged as leading tools in the digital annotation space: Hypothesis and Perusall. The assessment sought to understand how faculty at CU Boulder have integrated the tools into their courses to enhance teaching and learning as well as the level of usage of both tools. 

Approach 

The ATI team conducted a review of each tool's features and limitations. We also met with faculty users to understand how they have integrated them into their assignments and grading workflows. Finally, we analyzed campus usage levels and vendors’ pricing models to help determine whether either tool should be adopted as an OIT-supported resource.        

Findings

Although both tools enhance collaborative reading and engagement, they differ in how they integrate with the learning management system (LMS). Hypothesis functions as an LTI integration within the LMS. The integration adds an annotation sidebar to Hypothesis-enabled readings that are assigned in a course. Instructors can access student annotations via Canvas’ Speedgrader. Hypothesis recently launched an autograding feature that simplifies the grading process by automatically calculating grades based on the number of notes or annotations. Instructors then have the option to sync the grades with the Canvas gradebook.

In contrast, the Perusall LMS integration launches a separate Perusall platform in which students and instructors access assignments and grades. Grading is enabled automatically for courses with at least 15 students. A machine learning algorithm allows instructors to assign scores based on the quality and quantity of students’ engagement. Instructors can specify their scoring preferences and rubrics by modifying the automatic scoring settings in their Perusall course. While AI could help scale grading workflow, student use of AI tools can complicate authentic engagement with annotations and discussions.

Analysis of Hypothesis and Perusall usage from Fall 2021 through Spring 2025 revealed the following average adoption rates:

• Hypothesis: 0.3% of Canvas courses, 0.9% of Canvas users
• Perusall: 0.6% of Canvas courses, 1.6% of Canvas users

Conclusion

While faculty reported that Hypothesis and Perusall helped increase engagement, foster community, and streamline grading practices, the examination of campus usage revealed adoption rates that are too low for consideration as a centrally-supported OIT resource. We will continue to monitor usage patterns and will gauge interest in these and other technology offerings in our biennial AT survey. Should there be a significant increase in usage or interest, we will consider a more extensive assessment of these tools.      

Project Participants