Creating and managing assessments can take a significant amount of an educator’s time. From writing questions and preparing quizzes to grading submissions and transferring results into learning management systems, the assessment process often involves several disconnected steps.
Asseska was built to explore how artificial intelligence and workflow automation could simplify that process while keeping educators in control of assessment decisions.
The Problem We Wanted to Solve
Traditional assessment workflows often require lecturers to move between multiple systems. Questions may be created manually, student responses collected in another platform, grades reviewed separately, and final scores transferred into an LMS.
The challenge was not simply generating questions with AI. The larger goal was to create a connected assessment workflow that could support quiz creation, deployment, grading, lecturer review, and LMS integration.
Building the AI Quiz Generation Workflow
Asseska allows educators to provide a topic or learning objective and use AI to generate assessment questions. The generated questions can then be reviewed and edited before being used.
This approach treats AI as an assistant rather than removing the educator from the process. Lecturers retain the ability to review generated content and determine what should ultimately be included in an assessment.
Automating the Grading Process
Objective questions can be evaluated automatically, while AI can assist with evaluating subjective responses. Results are surfaced through the platform so lecturers can review grading outcomes and identify submissions that may require additional attention.
A grading queue and centralized results dashboard help keep the workflow manageable rather than treating AI output as the final authority.
Connecting With Existing Academic Workflows
A major design goal was to avoid forcing institutions to replace tools they already use. Asseska is designed to integrate with learning management systems such as Canvas so assessment results can fit into existing academic workflows.
This allows the platform to operate as an additional layer of automation around assessment rather than requiring an institution to rebuild its entire learning environment.
What We Learned
AI is most valuable when it solves a clearly defined workflow problem.
Educators should remain part of the review and decision-making process.
Integration with existing systems is critical for adoption.
AI-generated output requires structured validation and error handling.
A good AI product requires much more than simply connecting an application to an AI model.