A Feed-Forward Approach to Feedback

Originally published November 14, 2025. Research Note contributed by Tracy Snoddon, professor of Economics in the Lazaridis School of Business and Economics.

What’s the Pedagogical Challenge?

The Feedback Challenge

As instructors, we strive to give feedback to students in such a way as to improve their learning. Implementing effective feedback can, however, be a daunting task. Instructors face time and resource constraints limiting their ability to deliver feedback, especially in larger classes (Henderson et. al. 2019; Boud and Dawson 2023). Feedback may come too late or too infrequently to be used in subsequent learning activities. Feedback is often one-way, with limited scope for student agency (and engagement), and it may be misunderstood or even ignored (McCarthy 2017). These challenges are compounded by changes in the post-secondary education environment, including a more diverse and less prepared student body and the increasing use of generative AI and the challenges it poses for academic integrity (VanNijnatten 2025).

Learning depends on how students engage with the feedback they receive. Indeed, Zhang and Hyland (2022) observe that the most effective type of feedback is a feed-forward approach, one that incorporates multiple opportunities for students to engage with, and respond to, feedback. But while there is broad consensus in the literature on the importance of effective feedback, there is a lack of high quality, robust empirical evidence to support this consensus (Morris et. al. 2021).

Research Insights

This project, supported by a Teaching Excellence and Innovation project grant, set out to address three gaps in the literature: existing empirical studies are limited by small sample sizes; there is limited research on the resource costs of implementing different types of feedback; and systematic measurement of the benefits of feedback on student outcomes and engagement is limited.

We investigated the costs and benefits of implementing a feed-forward model designed to address some of the complaints identified above. The feedback process was built around an infographic assignment completed by students in a 2nd year economics undergraduate course in the winter term of 2025.ⁱ While this study is work in progress, here we share some preliminary results that we presented earlier this year at the Society of Teaching and Learning in Higher Education conference.ⁱⁱ

A Feed-Forward Approach

The purpose of the scaffolded infographic assignment, and the associated feedback model, was to deepen students’ understanding of course content by connecting course material to the real world through data visualization. Table 1 summarizes the assignment and its feedback components.

Students could receive written feedback on their workshop submissions, the interim progress report and the final submission via the online learning platform. Verbal feedback was provided during in-class workshops and in-person feedback meetings. The in-person feedback meeting was included to help engage students in a two-way feedback process, reduce the possibility that feedback was ignored, encourage academic integrity, and limit the misuse of generative AI.

**Table 1: Student Infographic Project Components, Timing and Feedback**
Component/Assessment Weight	Timing	Activity	Feedback
In-class workshop (2%) + individual submission	Week 3	Individual, group & whole class activities	In-class - oral Submission – written
In-class workshop (2%) + individual submission	Week 7	Individual, group & whole class activities	In-class - oral Submission – written
Interim Submission (2%)	End of week 7	Submission	Checklist; written feedback
In-person feedback meeting (2%)	Weeks 8,9 & 10	3:1 Meeting with instructor	Oral feedback
Final Project (22%)	End of week 12	Submission	Grading rubric + written feedback

Evaluating the Experience: Some Preliminary Results

The common feedback complaints are: (i) feedback is too infrequent to be used in subsequent learning experiences; (ii) feedback is one-way with limited scope for student agency; and, (iii) feedback is ignored. Our approach addresses the first two complaints. Students had multiple opportunities to receive and respond to feedback, as demonstrated in Tables 1 and 2. From the instructor’s perspective, feedback meetings were generally lively with lots of two-way exchange. The percentage of students receiving written feedback at each stage ranged from 92 percent to 100 percent. The instructor met in-person with 78 of 105 students registered in the course and provided 346 pieces of written feedback during the term.

**Table 2: Summarizing the Experience So Far**
Component / Assessment Weight	Workshop 1	Workshop 2	Interim Submission	Feedback Meeting	Final Project
Students submitting as % of students enrolled	89% 93 students	87% 91 students	71% 74 students	74% 78 students	101 students 96%
Submissions with feedback as % of total submissions	92% 86 students	96% 87 students	99% 73 students	100% 78 students	99% 100 students
Feedback “opened” or ”read” as % of submissions with feedback	86% 74 students	69% 60 students	85% 62 students	100% 78 students	42% 42 students

One simple indicator to determine whether written feedback was ignored is to look at what percentage of written feedback was “opened” or “read” by students, as recorded by the online learning platform. Table 2 shows that 69 percent to 86 percent of written feedback on the interim components was at least opened as compared to only 42 percent for the final submission. This result is perhaps not surprising as, from the student perspective, feedback on the final project cannot be used directly to affect outcomes on the project itself. However, the goal of feedback at this stage, if read and engaged with, is to provide future learning benefits. Of course, even if a student opens the written feedback, this doesn’t tell us if and how the student might have engaged with that feedback. Our ongoing work, discussed below, digs deeper into the development of metrics of feedback quality and engagement.

While this feedback model addresses some of the common feedback complaints, it is quite costly to implement. Table 3 shows the average and total time spent providing feedback for each of the infographic components. Over all components, time costs were at least 40 minutes per student and about 70 hours in total. Whether or not this is a worthwhile investment depends critically on the benefits of this approach to feedback.

**Table 3: Time Costs**
Time Costs	Workshop 1	Workshop 2	Interim Submission	Feedback Meeting	Final Project
Average time per student (minutes)	4 minutes	5 minutes	7 minutes	14.6 minutes	16.2 minutes
Total time (hours)	6.2 hours	7.6 hours	8.8 hours	19.5 hours	27.2 hours

What’s Next?

Next on our research agenda is to turn our attention to measuring the benefits of the feedback model. This is admittedly a challenging task for several reasons. Learning is multi-dimensional. The impact of feedback may take time to translate into improved academic performance, or it may show up in attributes not well measured by typical academic assessments. We tackle this challenge by drawing on both qualitative and quantitative data. We will undertake a document analysis of the 346 pieces of written feedback given to students to track whether and how students engaged with feedback, and to develop different metrics for the quality of feedback given and feedback engagement. We will examine the relationship between academic performance, feedback quality, and feedback engagement. And finally, we will investigate students’ perceptions of the infographic project and different feedback channels using the results of student surveys undertaken at the start of the course, once final grades were released, and six months after the course was completed.

By quantifying the costs and the benefits of a feed-forward approach to feedback, this research helps inform whether investments in this type of feedback is an effective and efficient use of resources.

References and Further Reading

Boud, D. and P. Dawson (2023). “What feedback literate teachers do: An empirically-derived competency framework”, Assessment and Evaluation in Higher Education, 48(2), 158-171.

Henderson, M., T. Ryan, and M. Phillips (2019). The challenges of feedback in higher education. Assessment and Evaluation in Higher Education, 44(8), 1237–1252.

McCarthy, J. (2017). “Enhancing feedback in higher education: Students’ attitudes toward online and in-class formative assessment feedback models”, Active Learning in Higher Education, 18(2), 127-141.

Morris, R., T. Perry and L. Wardle (2021). “Formative assessment and feedback for learning in higher education: A systematic review”, Review of Education.

VanNijnatten, D. “Designing a pathway through our post-pandemic teaching challenges: How to support the teaching mission at your institution”, University Affairs, February 6, 2025.

Zhang, Z and K. Hyland (2022). “Fostering student engagement with feedback: An integrated approach”, Assessing Writing, 51, 100586.

Endnotes

^i. This is part of a larger project on active learning, feedback and engagement using infographics that collects data from 4 sections between 2023 and 2025, including survey data on students’ perceptions of their experience with the infographic project and feedback channels at three different points in time.

^ii. This work is joint with Amelia Graham, Master of Arts in Business Economics (2025), Lazaridis School of Business and Economics.