Explore how Time on Task (ToT) goes beyond workload estimation to help create balanced, engaging, and effective learning experiences. This interactive session will showcase practical strategies, innovative tools, and data-driven approaches that align courses with institutional standards, improve student outcomes, and foster meaningful engagement for both students and faculty.

Overview

How long does it take students to read assigned materials? To complete a project? To participate meaningfully in a discussion forum? At the Global College of Professional Military Education, we recognized that relying on educated guesses often led to inconsistencies in student workload within and across courses. To address this issue, we integrated Time on Task (ToT) as a foundational element of our course and program design, using a novel ToT estimation tool we developed to help ensure courses are manageable, effective, and aligned with both institutional and accreditation standards.

ToT offers a strategic method for accurately estimating and balancing student workload, preventing both overload and under-engagement and allowing course designers to target course engagement methods. Despite its importance, there is surprisingly little research or concrete guidance available to help educators systematically apply ToT to online courses (Barre, Brown, & Esarey, 2016). This session will showcase the benefits and challenges of implementing ToT at the Global College, providing attendees with insights and hands-on experience for applying ToT in their own online courses. We will demonstrate how our ToT tool enables us to make data-driven decisions that benefit both students and faculty, helping ensure coursework is balanced, engaging, and optimized for learning.

Background

The Global College has leveraged ToT since 2007, continually adapting and refining it to meet evolving course management and student needs. While ToT is not a new concept, our organization developed a unique ToT tool that estimates both student and instructor time for each task—such as readings, quizzes, essays, and grading. This data-driven approach ensures transparency, guiding management decisions and optimizing student engagement while fostering a more balanced and equitable learning environment.

The ToT tool is built within a straightforward Excel spreadsheet that converts student workload—readings, quizzes, essays, and other requirements—into estimated time commitments and page counts. For instructors, it similarly converts tasks such as grading and participation into time estimates. This allows for a holistic view of course demands for both students and instructors. With ToT, we can make direct, like-for-like comparisons across various courses and programs, ensuring consistency in workload expectations and supporting continuous curriculum improvements. It provides valuable data that helps streamline course design and optimize student and faculty experiences.

This tool has been crucial in helping the Global College balance workloads, standardize expectations across courses and programs, and align our curriculum with institutional goals. Analyzing ToT data across different courses helps us ensure consistency in workload and prevent students from being either overwhelmed or under-challenged.

Importance and Benefits

At the Global College, we have found several key benefits to using ToT that we will discuss during the session. First, ToT has significant cognitive and behavioral benefits. By accurately estimating the time students need to engage with course materials and activities, ToT helps students dedicate an appropriate amount of time to processing content, deepening their cognitive engagement and fostering more meaningful learning (Pardos, Z., Borchers, C., & Yu, R., 2022). Additionally, ToT encourages the development of important academic skills like time management and self-directed learning, which are particularly vital in the online environment.

Second, ToT helps align courses with institutional and accreditation requirements (Powell, Stephens‐Helm, Layne, & Ice, 2012). Faculty can use ToT to help design courses that meet guidelines for credit hours and workload while preventing students from becoming overwhelmed by unrealistic expectations. This alignment not only improves student satisfaction but also contributes to better retention rates. Furthermore, by using ToT estimates, educators can make more informed decisions about the quantity and types of activities to include in a course (Beer, 2019). This approach helps ensure that each task is intentionally aligned with learning outcomes and contributes meaningfully to the course without overburdening students.

Finally, ToT helps standardize workloads across courses and programs. By using ToT as a consistent measure, instructional designers and faculty can compare workloads across different courses and identify discrepancies in expectations. This enables institutions to adjust workloads and maintain consistency and fairness throughout the curriculum.

Addressing Challenges

While Time on Task offers numerous benefits, implementing it effectively presents certain challenges. One of the primary challenges is educator unfamiliarity with ToT (Barre, 2016). Many educators and instructional designers are unsure how to get started with ToT, including how to estimate time for different activities, set up a ToT plan, or apply it systematically. Without proper guidance, there is a risk of inaccurate estimates, which can either overwhelm students or fail to provide enough challenge. In this session, we will discuss the practical tools and strategies we have used to overcome this barrier, providing attendees the knowledge and resources needed to confidently perform ToT in their own courses.

A key challenge in this area is the lack of standardized time estimates for online higher education courses, which have been underexplored and minimally documented in the literature (Powell, Stephens‐Helm, Layne, & Ice, 2012). Additionally, student-reported data on task completion times can be inconsistent or unreliable, as individual perceptions of task duration often vary widely (Brady, Wolters, & Lu, 2022). However, we have developed strategies and resources to improve the accuracy of time estimates that we will examine during the session.

A third challenge is engaging faculty and gaining buy-in. Faculty may be hesitant to adopt ToT into their course design process, especially if they feel confident in their current methods. We will present strategies we have implemented for gaining faculty buy-in, such as demonstrating how ToT aligns with institutional standards and improves both student outcomes and course evaluations.

Interactivity Plan

This session will feature two interactive components designed to engage attendees and provide them with practical tools for applying ToT. First, attendees will be asked to estimate how long they think certain learning activities, such as reading assignments or group projects, will take. Their estimates will then be compared to researched ToT data, revealing how difficult it can be to accurately predict student workload without proper tools. This activity will spark conversation about the importance of accurate workload estimation and lead into a discussion of how ToT can help.

Second, attendees will explore and practice filling out components of a ToT estimation sheet, which they can use in their own course design. This hands-on exercise will provide participants with a practical tool and experience in estimating time for various learning activities. It will also prompt deeper discussions about how to implement ToT in different contexts, address challenges of standardizing estimates, and foster faculty buy-in. We will provide a QR code that attendees can use to access the ToT tool after the conference.

Takeaways:

At the end of the session, participants will leave with:

Practical Understanding: Attendees will develop a working knowledge of why and how ToT can enhance the design and delivery of online and blended courses.
Hands-on Tools: Attendees will explore and practice filling out sections of a ToT estimation sheet. They can access the sheet following the conference to apply in their own course designs.
Strategies for Implementation: Attendees will discuss solutions for overcoming common challenges associated with ToT, including familiarization with ToT resources and methods, standardizing time estimates, faculty engagement.
Course Design Improvements: Attendees will be equipped to improve course design in relation to institutional requirements, student engagement, and learning outcomes.

References

Barre, E. (2016, July 11). How much should we assign? Estimating out of class workload. Rice University Center for Teaching Excellence. https://cte.rice.edu/blog/2016/workload

Barre, E., Brown, A., & Esarey, J. (2016). Course Workload Estimator 2.0. Wake Forest University Center for the Advancement of Teaching. https://cat.wfu.edu/resources/workload2/

Beer, N. (2019) Estimating student workload during the learning design of online courses: Creating a student workload calculator. In: Proceedings of the 18th European Conference on e-Learning ECEL 2019 (pp. 629-638). Academic Conferences and Publishing International Limited.

Brady, A. C., Wolters, C. A., & Yu, S. L. (2022). Self-regulation of time: The importance of time estimation accuracy. Frontiers in Psychology, 13, 1-9. https://doi.org/10.3389/fpsyg.2022.925812

Kovanović, V., Gašević, D., Dawson, S., Joksimović, S., Baker, R. S., & Hatala, M. (2015). Does time-on-task estimation matter? Implications for the validity of learning analytics findings. Journal of Learning Analytics, 2(3), 81-110. http://dx.doi.org/10.18608/jla.2015.23.6

Pardos, Z., Borchers, C., & Yu, R. (2022). Credit hours is not enough: Explaining undergraduate perceptions of course workload using LMS records. The Internet and Higher Education, 56, 1-23. https://doi.org/10.1016/j.iheduc.2022.100882

Powell, K., Stephens‐Helm, J., Layne, M., & Ice, P. (2012). Quantifying online learning contact hours. Administration Issues Journal: Education, Practice, and Research, 2(2), 80-93. https://files.eric.ed.gov/fulltext/EJ1056395.pdf