A scalable approach for sizing learning and estimating student workload for adaptive higher-education courses

Abstract

Background

As higher-education providers unbundle programs into micro-credentials and other variable-credit offerings, educators need a way to convert credit points into balanced hours of teaching and learning. In Australia, this is complicated by the lack of a national conversion formula and the coexistence of units that may carry anything from a small to a large credit point (e.g., 1 to 24 credit points or the local equivalent). Working in a central educational-practice team charged with curriculum innovation and architecture, we were repeatedly asked:

• How many credit points—and corresponding hours—should we allocate to a given mix of learning and assessment activities?
• What guidance can we offer when a unit carries fewer credit points than our legacy subjects?
• How can we design stackable short courses that still meet university policy and external volume-of-learning requirements?

Aspiration and approach

To address the above needs, our aim was to create a scalable sizing framework and digital workload estimator that aligns credit points, assessment, and student effort while remaining adaptable across diverse credit systems. Drawing on sector guidelines, workload literature, and institutional policy, we produced step-by-step guidance for balancing scheduled hours, learner-directed study, and assessment effort. This guidance is hosted on SharePoint and was then turned to a lightweight digital tool called Student Workload Estimator (SWE)—which generates course workload maps visually and supports adaptable program structures.

Development snapshot

We began with a spreadsheet prototype that encoded word-to-time equivalences and assessment-load caps. In collaboration with the university’s evaluation specialist, this logic was rebuilt in a low-code platform using Microsoft Power App, maintaining security and version control. All formulas derive from an evidence-informed framework; full methodological detail will appear in a companion journal article.

Poster experience

The poster will visualise student workload estimator’s workflow, illustrating the underlying hour-allocation logic. Audience takeaways include:

• A visual map of the literature and guidelines that underpin the credit-to-hours formulas, plus a QR link to the full bibliography.
• An annotated diagram of the framework’s core components (baseline contact hours, task-to-time multipliers, assessment-load caps) with tips for local adaptation.
• A scan-to-watch demo video walkthrough of the SWE, plus downloadable templates and a facilitation guide for CP, ECTS, or contact-hour models.

Relevance to “Adaptable Learners” themes

The Student Workload Estimator provides educators a real-time visibility of workload requirements, allowing courses to be flexible across credit points while considering learner well-being in workload. By translating high-level policy into an intuitive digital resource, the tool not only models how technology can nurture adaptive learning communities but also provides a practical mechanism for delivering the flexible learning options today’s adaptable learners need.

Next steps

Since its launch a year ago, the estimator has attracted steady enquiries and positive feedback from educators who report clearer workload conversations and smoother course-approval cycles. Building on this momentum, we will: (1) publish a research article on its theoretical foundations and curricular impact; (2) add use requested functions—such as creative-project workload calculators—via co-design workshops; and (3) develop a student-facing version to help learners plan and manage their own study time.