We all remember the warning from math class:

“You won’t always have a calculator in your pocket!”

How we laugh now, with calculators first arriving in our pockets and, eventually, smartphones putting one in our hands at all times.

I have seen a lot of comparisons ¹ ² ³ across the Internet to artificial intelligence (AI) and these mathematics classes of yesteryear. The idea being that AI is but the newest embodiment of this same concern, which ended up being overblown.

But is this an apt comparison to make? After all, we did not replace math lessons and teachers with pocket calculators, nor even with smart phones. The kindergarten student is not simply given a Casio and told to figure it out. The quote we all remember has a deeper meaning, hidden among the exacerbated response to the question so often asked by students: “Why are we learning this?”

The response

It was never about the calculator itself, but about knowing how, when, and why to use it. A calculator speeds up the arithmetic, but the core cognitive process remains the same. The key distinction is between pressing the = button and understanding the result of the = button. A student who can set up the equation, interpret the answer, and explain the steps behind the screen will retain the mathematical insight long after the device is switched off.

The new situation – Enter AI

Scenario

Pressed for time and juggling multiple commitments, a student turns to an AI tool to help finish an essay they might otherwise have written on their own. The result is a polished, well-structured piece that earns them a strong grade. On the surface, it looks like a success, but because the heavy lifting was outsourced, the student misses out on the deeper process of grappling with ideas, making connections, and building understanding.

This kind of situation highlights a broader concern: while AI can provide short-term relief for students under pressure, it also risks creating long-term gaps in learning. The issue is not simply that these tools exist, but that uncritical use of them can still produce passing grades without the student engaging in meaningful reflection gained by prior cohorts. Additionally, when AI-generated content contains inaccuracies or outright hallucinations, a student’s grade can suffer, revealing the importance of reviewing and verifying the material themselves. This rapid, widespread uptake stresses the need to move beyond use alone and toward cultivating the critical habits that ensure AI supports, rather than supplants, genuine learning.

Some background studies

In a 2024 study on Generative AI Usage and Exam Performance, Wecks et al. (2024) describe that:

Employing multivariate regression analysis, we find that students using GenAI tools score on average 6.71 (out of 100) points lower than non-users. While GenAI may offer benefits for learning and engagement, the way students actually use it correlates with diminished exam outcomes

Another study (Ju, 2023) found that:

After adjusting for background knowledge and demographic factors, complete reliance on AI for writing tasks led to a 25.1% reduction in accuracy. In contrast, AI-assisted reading resulted in a 12% decline. Ju (2023).

In this same study, Ju (2023) noted that while using AI to summarize texts improved both quality and output of comprehension, those who had a ‘robust background in the reading topic and superior reading/writing skills’ benefited the most.

Ironically, the students who would benefit most from critical reflection on AI use are often the ones using it most heavily, demonstrating the importance of embedding AI literacy into the curriculum. For example: A recent article by Heidi Mitchell from the Wall Street Journal (Mitchell, 2025) cites a study showing that the “less you know about AI, the more you are likely to use it”, and describing AI as seemingly “magical to those with low AI literacy”.

Finally, Kosmyna et al. (2025), testing how LLM usage affects cognitive processes and neural engagement in essay writing, assembled groups of LLM users, search engine users, and those without these tools (dubbed “brain-only” users). The authors recorded weaker performance in students with AI assistance over time, a lower sense of ownership of work with inability to recall work, and even seemingly reduced neural connectivity in LLM users compared to the brain-only group, which scored better in all of the above.

The takeaways from these studies are that unstructured AI use acts as a shortcut that erodes retention. While AI-assistance can be beneficial, outright replacement of thinking with it is harmful. In other words, AI amplifies existing competence but rarely builds it from scratch.

Undetected

Many people believe themselves to be fully capable of detecting AI-usage:

Most of the writing professors I spoke to told me that it’s abundantly clear when their students use AI. Sometimes there’s a smoothness to the language, a flattened syntax; other times, it’s clumsy and mechanical. The arguments are too evenhanded — counterpoints tend to be presented just as rigorously as the paper’s central thesis. Words like multifaceted and context pop up more than they might normally. On occasion, the evidence is more obvious, as when last year a teacher reported reading a paper that opened with “As an AI, I have been programmed …” Usually, though, the evidence is more subtle, which makes nailing an AI plagiarist harder than identifying the deed. (Walsh, 2025).

In the same NY Mag article, however, Walsh (2025) cites another study, showing that it might not be as clear who is using AI and who is not (emphasis added):

[…] while professors may think they are good at detecting AI-generated writing, studies have found they’re actually not. One, published in June 2024, used fake student profiles to slip 100 percent AI-generated work into professors’ grading piles at a U.K. university. The professors failed to flag 97 percent.

The two quotes are not contradictory; they describe different layers of the same phenomenon. Teachers feel they can spot AI because memorable extremes stick in their minds, yet systematic testing proves that intuition alone misses the overwhelming majority of AI‑generated work. This should not be surprising though, as most faculty have never been taught systematic ways to audit AI‑generated text (e.g., checking provenance metadata, probing for factual inconsistencies, or using stylometric analysis). Nor do most people, let alone faculty grading hundreds of papers per week, have the time to audit every student. Without a shared, college-wide rubric of sorts, detection remains an ad‑hoc, intuition‑driven activity. Faulty detection risks causing undue stress to students, and can foster a climate of mistrust by assuming that AI use is constant or inherently dishonest rather than an occasional tool in the learning process. Even with a rubric, instructors must weigh practical caveats: large-enrollment courses cannot sustain intensive auditing, some students may resist AI-required tasks, and disparities in access to tools raise equity concerns. For such approaches to work, they must be lightweight, flexible, and clearly framed as supporting learning rather than policing it.

This nuance is especially important when considering how widespread AI adoption has been. Walsh (2025) observed that “just two months after OpenAI launched ChatGPT, a survey of 1,000 college students found that nearly 90 percent of them had used the chatbot to help with homework assignments.” While this figure might seem to justify the use of AI detectors, it could simply reflect the novelty of the tool at the time rather than widespread intent to circumvent learning. In other words, high usage does not automatically equal cheating, showing the importance of measured, thoughtful approaches to AI in education rather than reactionary ones.

What to do…?

The main issue here is not that AI is magically writing better essays than humans can muster, it is that students are slipping past the very moments where they would normally grapple with concepts, evaluate evidence, and argue a position. Many institutions are now taking a proactive role rather than a reactive one, and I want to offer such a suggestion going forward.

Embracing the situation: The reflective AI honor log

It is a fact that large language models have become ubiquitous. They are embedded in web browsers, word processors, and even mobile keyboards. Trying to ban them outright creates a cat‑and‑mouse game; it also sends the message that the classroom is out of sync with the outside world.

Instead of fighting against a technology that is already embedded in our lives, invite students to declare when they use it and to reflect on what they learned from that interaction.

For this post, I am recommending using an “AI Honor-Log Document”, and deeply embedding it into courses, with the goal of increasing AI literacy.

What is it?

As assignments vary across departments and even within courses, a one-size-fits-all approach is unlikely to be effective. To support thoughtful AI use without creating extra work for students, faculty could select an approach that best aligns with their course design:

Built-in reflection: Students note when and how they used AI, paired with brief reflections integrated into their normal workflow.
Optional, just-in-time logging: Students quickly log AI use and jot a short note only when it feels helpful, requiring minimal time.
Embedded in assignments: Reflection is incorporated directly into the work, so students engage with it as part of the regular writing or research process.
Low-effort annotations: Students add brief notes alongside tasks they are already completing, making reflection simple and natural.

These options aim to cultivate critical thinking around AI without imposing additional burdens or creating the perception of punishment, particularly for students who may not be using AI at all.

AI literacy is a massive topic, so let’s only address a few things here:

Mechanics Awareness: Ability to explain the model architecture, training data, limits, and known biases.
Critical Evaluation: Requiring fact-checking, citation retrieval, and bias spotting.
Orchestration Skills: Understanding how to craft precise prompts, edit outputs, and add original analysis.

Note: you might want to go further and incorporate these into an assignment level learning outcome. Something like: “Identifies at least two potential biases in AI-generated text” could be enough on a rubric to gather interesting student responses.

Log layout example

#	Assignment/Activity	Date	AI Model	Exact Prompt	AI Output	What you changed/Added	Why You Edited	Confidence (1-5)	Link to Final Submission
1	Essay #2 – Digital-privacy law	2025-09-14	GPT-5	“Write a 250-word overview of GDPR’s extraterritorial reach and give two recent cases	[pastes AI text]	Added citation to 2023 policy ruling; re-phrased a vague sentence.	AI omitted the latest case; needed up-to-date reference	4	https://canvas.oregonstate.edu/……

Potential deployment tasks (and things to look out for)

It need not take much time to model this to students or deploy it in your course. That said, there are practical and pedagogical limits depending on course size, discipline, and student attitudes toward AI. The notes below highlight possible issues and ways to adjust.

Introduce the three reasons above (either text form or video, if you have more time and want to make a multimedia item).
Caveat: Some students may be skeptical of AI-required work.
Solution: Frame this as a reflection skill that can also be done without AI, offering an alternative if needed.
Distribute the template to students: post a Google-Sheet link (or similar) in the LMS.
Caveat: Students with limited internet access or comfort with spreadsheets may struggle.
Solution: Provide a simple Word/PDF version or allow handwritten reflections as a backup.
Model the process in the first week: Submit a sample log entry like the one above but related to your class and required assignment reflection type.
Caveat: In large-enrollment courses, individualized modeling is difficult.
Solution: Share one well-designed example for the whole class, or record a short screencast that students can revisit.
Require the link with each AI-assisted assignment (or as and when you believe AI will be used).
Caveat: Students may feel burdened by repeated uploads or object to mandatory AI use.
Solution: Keep the log lightweight (one or two lines per assignment) and permit opt-outs where students reflect without AI.
Provide periodic feedback: scan the logs, highlight common hallucinations or errors provided by students, give a “spot the error” mini lecture/check-in/office hour.
Caveat: In large classes, it’s not realistic to read every log closely.
Solution: Sample a subset of entries for themes, then share aggregated insights with the whole class during office hours, or post in weekly announcements or discussion boards designed for this kind of two-way feedback.
(Optional) Student sharing session in a discussion board: allow volunteers or require class to submit sanitized prompts (i.e., any personal data removed) and edits for peer learning.
Caveat: Privacy concerns or reluctance to share work may arise.
Solution: Keep sharing optional, encourage anonymization, and provide opt-outs to respect comfort levels.

Important considerations when planning AI-tasks

Faculty should be aware of several practical and pedagogical considerations when implementing AI-reflective logs. Large-enrollment courses may make detailed feedback or close monitoring of every log infeasible, requiring sampling or aggregated feedback. Some students may object to AI-required assignments for ethical, accessibility, or personal reasons, so alternatives should be available (i.e. the option to declare that a student did not use AI should be present). Unequal access to AI tools or internet connectivity can create equity concerns, and privacy issues may arise when students share prompts or work publicly. To address these challenges, any approach should remain lightweight, flexible, and clearly framed as a tool to support learning rather than as a policing mechanism.

Conclusion

While some students may feel tempted to rely on AI, passing an assignment in this manner can also pass over the critical thinking, analytical reasoning, and reflective judgment that go beyond content mastery to true intellectual growth. Incorporating a reflective AI-usage log based not on assumption of cheating, but on the ubiquitous availability of this now-common tool, reintroduces one of the evidence-based steps for learning and mastery that has fallen out of favor in the last 2-3 years. By encouraging students to pause, articulate, and evaluate their process, reflection helps them internalize knowledge, spot errors, and build the judgment skills that AI alone cannot provide.

Footnotes

References

Fu, Y. and Hiniker, A. (2025). Supporting Students’ Reading and Cognition with AI. In Proceedings of Workshop on Tools for Thought (CHI ’25 Workshop on Tools for Thought). ACM, New York, NY, USA, 5 pages. https://arxiv.org/pdf/2504.13900v1

Ju, Q. (2023). Experimental Evidence on Negative Impact of Generative AI on Scientific Learning Outcomes. https://doi.org/10.48550/arXiv.2311.05629

Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. https://arxiv.org/abs/2506.08872

Mitchell, H. (2025). The Less You Know About AI, the More You Are Likely to Use It. Wall Street Journal. Accessed September 3, 2025: https://www.wsj.com/tech/ai/ai-adoption-study-7219d0a1

Wecks, J. O., Voshaar, J., Plate, B. J., & Zimmermann, J. (2024). Generative AI Usage and Exam Performance. https://doi.org/10.48550/arXiv.2404.19699

Walsh, J. (May 7, 2025). Everyone Is Cheating Their Way Through College ChatGPT has unraveled the entire academic project. Intelligencer. https://nymag.com/intelligencer/article/openai-chatgpt-ai-cheating-education-college-students-school.html

Fall Term is just around the corner, bringing with it new opportunities, fresh faces, and the chance to make a lasting impact on your students. Whether they’re logging in for the first time or for their final term, setting a welcoming and engaging tone from day one helps create a foundation for everyone’s success, yours included.

Here are a few ways to kick things off and set the stage for a smooth, successful term:

Start with a warm welcome

Post a welcome announcement and introduce yourself to your students.
Use a warm and welcoming tone in your message to help students feel encouraged, supported, and comfortable as they enter the course.
Personalize it with a photo or short video, it goes a long way in making connections.

Open your course early

If possible, open your course before the official start date. This gives students a chance to explore, order materials, and introduce themselves.
Open modules at least two weeks ahead. Many students juggle full-time jobs, families, and other commitments, so maximum flexibility is appreciated.

Keep communication open

Set up a Q&A discussion forum, and check it regularly. This allows you to answer common questions once and ensures everyone sees the response.
Encourage students to post questions in this forum and let students know when and how they can expect replies.
Be responsive to messages and follow up with students if needed.

Model engagement

Join discussion boards and post regularly. Ask guiding questions, offer feedback, or simply cheer students on, show them you’re present and engaged.
Think about how you’d engage in a face-to-face class and bring that energy to your online space too.

Be accessible

Hold regular office hours or offer flexible scheduling options. Creating the time and space for students to connect with you makes a difference.

Grade consistently and give meaningful feedback

Timely, constructive feedback helps students grow. The effort you put in early pays off in improved work later in the term.

Stay organized

Block out time in your calendar each week for class check-ins and grading. A little planning now can prevent overwhelm and burnout later.

Take care of yourself

Don’t forget to breathe. Support your students by also supporting yourself.
Be kind to yourself and set boundaries to attend to personal commitments, too.

Here’s to a strong, successful Fall Term — you’ve got this!

Too often, online courses struggle with communication that feels slow and one-sided. Students swap ideas in discussion boards, but collaboration stops there. Integrating Microsoft Teams into Canvas changes that. It brings real-time conversation, file-sharing, and group spaces directly into the LMS–helping students connect more naturally and giving instructors new ways to guide and engage. This integration not only boosts collaboration, it also provides more opportunities for Regular and Substantive Interaction (RSI) between students and instructors—structured, faculty-initiated engagement that is required in online courses under federal guidelines.

Seamless Collaboration Across Projects and Courses

Integrating Teams into Canvas ensures that group work and peer review move beyond static discussion boards into dynamic, asynchronous interactions. Students can download the app on their mobile devices, which allows them to have more consistent and real-time access to the comments and work shared by their peers. Teams allows for:

Dedicated channels for individual projects or study groups
Tagging teammates so each member of a channel knows when they are needed
File sharing by both team members and instructors

This unified workspace helps teams stay organized, accountable, and focused on shared learning outcomes. Teams has both course-level and group-level integrations. This allows instructors flexibility in how they would like to use the app. These different levels allow Teams to be used for the entire course or just for specific group projects (or both). Regardless of the level of integration and use, instructors can see how students are collaborating and completing a task or group assignment. This gives them a space to quickly jump in if students are struggling or off track.

Enhanced Communication and Community Building

Canvas announcements and emails can feel one-sided; within Teams, conversations become two-way forums where ideas flow instantly. Notifications appear directly inside Canvas (and on mobile devices if students/instructors allow), ensuring students never miss critical updates. Meanwhile, professors can host Q&A chats without scheduling hurdles by simply creating a channel in Teams. The fluid interaction nurtures a vibrant learning community, fostering peer support and timely faculty feedback. Additionally, this allows instructors to meet their Regular and Substantive Interaction goals, nurtures a collaborative online community and directly addresses the Ecampus Essentials standard of requiring all three forms (student–student, student–instructor, student–content) of interaction and engagement in a classroom.

Easy Oversight for Seeking Solutions Courses

One of the new CoreEd (Core Education is OSU’s state-of-the-art, 21st-century-focused general education program) categories being implemented this year include the Seeking Solutions courses. These courses require students to work in interdisciplinary groups and “wrestle with complex, multifaceted problems, and evaluate potential solutions from multiple points of view” (from the Seeking Solutions OSU page). This necessitates that students complete group assignments and projects while instructors mentor and monitor these groups individually.

With a fully asynchronous OSU Ecampus course, this can be difficult. One way this can be accomplished is through Teams channels. If each group has its own Teams channel and the instructor requires that they use Teams to communicate and collaborate for their project, then instructors can use this space to share resources, mentor the students, and facilitate hard conversations.

Conclusion

Integrating Microsoft Teams into Canvas reshapes the university experience by uniting collaboration and communication within a single resource. Students benefit from real-time teamwork features and greater access to their instructors, while professors enjoy streamlined group work oversight and the ability to intervene whenever necessary. Adopting this integrated approach not only enhances the quality of instruction but also fosters a more engaged and connected learning community. For more information on how to integrate Teams into your Canvas site, read the Canvas: Create linked Teams from Canvas page.

multidisciplinary seeking solutions — Seeking Solutions @Oregon State University

Core Education at Oregon State University launched summer 2025 and is designed to deepen how students think about problem-solving in ways that transcend disciplinary-specific approaches. It aims at preparing students to be adaptive, proactive members of society who are ready to take on any challenge, solve any problem, advance in their chosen career and help build a better world (Oregon State University Core Education, 2025).

Designing Seeking Solutions Signature Core category courses presents a few challenges, such as the nature of wicked problems, cross-discipline teamwork, and the global impact of wicked problems, to name just a few. In the past eight months, instructional designers at Oregon State University Ecampus have worked intensively to identify design challenges, brainstorm course design approaches, discuss research on teamwork and related topics, and draft guidelines and recommendations in preparation for the upcoming Seeking Solutions course development projects. Here is a list of the key topics we reviewed in the past few months.
1. Wick Problems
2. Team conflict
3. Online Large Enrollment Courses

Next, I will share summaries of research articles reviewed and implications for instructional design work for each of the above topics.

Wicked Problems

A wicked problem, also knowns as ill-structure problem or grand challenge, is a problem that is difficult or impossible to solve due to its complex and ever-changing nature. Research suggests that wicked problems must have high levels of three dimensions: complexity, uncertainty and value divergence. Complexity can take many forms but often involves the need for interdisciplinary reasoning and systems with multiple interacting variables. Uncertainty typically refers to how difficult it is to predict the outcome of attempts to address wicked problems. Value divergence refers particularly to wicked problems having stakeholders with fundamentally incompatible worldviews. It is the presence of multiple stakeholders in wicked problems with incompatible viewpoints that marks the shift from complex to super complex. (Veltman, Van Keulen, and Voogt, 2019; Head, 2008)
The Seeking Solutions courses expect students to “wrestle with complex, multifaceted problems, and work to solve them and/or evaluate potential solutions from multiple points of view”. Supporting student learning using wicked problems involves designing activities with core elements that reflect the messiness of these types of problems. McCune et al. (2023) from University of Edinburgh interviewed 35 instructors teaching courses covering a broad range of subject areas. 20 instructors teaching practices focused on wicked problems, while the other 15 instructors whose teaching did not relate to wicked problems. The research goal is to understand how higher education teachers prepare students to engage with “wicked problems”—complex, ill-defined issues like climate change and inequality with unpredictable consequences. The research question is “Which ways of thinking and practicing foster effective student learning about wicked problems?” The article recommended four core learning aspects essential for addressing wicked problems from their study:
1. Interdisciplinary negotiation: Students must navigate and integrate different disciplinary epistemologies and values.
2. Embracing complexity/messiness: Recognizing uncertainty and non linear problem boundaries as part of authentic learning.
3. Engaging diverse perspectives: Working with multiple stakeholders and value systems to develop consensus-building capacities.
4. Developing “ways of being”: Cultivating positional flexibility, uncertainty tolerance, ethical awareness, and communication across differences

Applications for instructional designers:

As instructional designers work very closely with course developers, instructors, and faculty, they contribute significantly to the design of Seeking Solutions courses. Here are a few instructional design recommendations regarding wicked problems from instructional designers on our team:
• Provide models or structures such as systems thinking for handling wicked problems.
• Assign students to complete the Identity Wheel activity and reflect on how their different identities shape their views of the wicked problems or shifts based on contextual factors. (resources on The Identity Wheel, Social Wheel, and reflection activities).
• Provide activities early in the course to train students on how to work and communicate in teams; to take different perspectives and viewpoints.
• Create collaborative activities regarding perspective taking.
• Evaluate assessment activities by focusing on several aspects of learning (students’ ability to participate; to solve the problem; grading the students on the ability to generate ideas, to offer different perspectives, and to collaborate; evaluation more on the process than the product, and self-reflection).

Team Conflict and Teamwork

“A central goal of this category is to have students wrestle with complex, multifaceted problems, and evaluate potential solutions from multiple points of view” (OSU Core Education, 2025). Working in teams provides an opportunity for teammates to learn from each other. However, teamwork is not always a straightforward and smooth collaboration. It can involve different opinions, disagreements, and conflict. While disagreements and differences can be positive for understanding others’ perspectives when taken respectively and rationally; when disagreements are taken poorly, differences in perspectives rises to become conflict and conflict could impact teamwork, morality, and outcomes negatively. Central to Seeking Solutions courses is collaborative teamwork where students will need to learn and apply their skills to work with others, including perspectives taking.

Aggrawal and Magana (2024) conducted a study on the effectiveness of conflict management training guided by principles of transformative learning and conflict management practice simulated via a Large Language Modeling (ChatGPT 3.5).
Fifty-six students enrolled in a systems development course were exposed to conflict management intervention project. The study used the five modes of conflict management based on the Thomas-Kilmann Conflict Mode Instrument (TKI), namely: avoiding, competing, accommodating, compromising, and collaborating. The researchers use a 3-phase (Learn, Practice and Reflect) transformative learning pedagogy.

Learn phase: The instructor begins with a short introduction; next, students watch a youtube video (duration 16:16) on conflict resolution. The video highlighted two key strategies for navigating conflict situations: (1) refrain from instantly perceiving personal attacks, and (2) cultivate curiosity about the dynamics of difficult situations.
Practice phase: students practice conflict management with a simulation scenario using ChatGPT 3.5. Students received detailed guidance on using ChatGPT 3.5.
Reflect phase: students reflect on this session with guided questions provided by the instructor.

The findings indicate 65% of the students significantly increased in confidence in managing conflict with the intervention. The three most frequently used strategies for managing conflict were identifying the root cause of the problem, actively listening, and being specific and objective in explaining their concerns.

Application for Instructional Design

Providing students with opportunities to practice handling conflict is important for increasing their confidence in conflict management. Such learning activities should have relatable conflicts like roommate disputes, group project tension, in the form of role-play or simulation where students are given specific roles and goals, with structured after-activity reflection to guide students to process what happened and why, focusing on key conflict management skills such as I-messages, de-escalation, and reframing, and within safe environment.

Problem Solving

Creativity, collaboration, critical thinking, and communication—commonly referred to as the 4Cs essential for the future—are widely recognized as crucial skills that college students need to develop. Creative problem solving plays a vital role in teamwork, enabling teams to move beyond routine solutions, respond effectively to complexity, and develop innovative outcomes—particularly when confronted with unfamiliar or ill-structured problems. Oppert et al. (2022) found that top-performing engineers—those with the highest levels of knowledge, skills, and appreciation for creativity—tended to work in environments that foster psychological safety, which in turn supports and sustains creative thinking. Lim et al. (2014) proposed to provide students with real-world problems. Lee et al. (2009) suggest to train students on fundamental concepts and principles through a design course. Hatem and Ferrara (2001) suggest using creative writing activities to boost creative thinking among medical students.

Application for Instructional Designers

We recommend on including an activity to train students on conflict resolution, as a warm-up activity before students work on actual course activities that involve teamwork and perspective taking. Also, it will be helpful to create guidelines and resources that students can use for managing conflict, and add these resources to teamwork activities.

Large Enrollment Online Courses

Teaching large enrollment science courses online presents a unique set of challenges that require careful planning and innovative strategies. Large online classes often struggle with maintaining student engagement, providing timely and meaningful feedback, and facilitating authentic practice. These challenges underscore the need for thoughtful course design and pedagogical approaches in designing large-scale online learning environments.

Mohammed and team (2021) assessed the effectiveness of interactive multimedia elements in improving learning outcomes in online college-level courses, by surveying 2111 undergraduates at Arizona State University. Results show frequently reported factors that increase student anxiety online were technological issues (69.8%), proctored exams (68%), and difficulty getting to know other students. More than 50% of students reported at least moderate anxiety in the context of online college science courses. Students commonly reported that the potential for personal technology issues (69.8%) and proctored exams (68.0%) increased their anxiety, while being able to access content later (79.0%) and attending class from where they want (74.2%), and not having to be on camera where the most reported factors decreased their anxiety. The most common ways that students suggested that instructors could decrease student anxiety is to increase test-taking flexibility (25.0%) and be understanding (23.1%) and having an organized course. This study provides insight into how instructors can create more inclusive online learning environments for students with anxiety.

Applications for Instructional Design

What we can do to help reduce student anxieties in large online courses:
1. Design task reminders for instructors, making clear that the instructor and the school care about student concerns.
2. Design Pre-assigned student groups if necessary
3. Design warm up activities to help students get familiar with their group members quickly.
4. Design students preferences survey in week 1.
5. Design courses that Make it easy for students to seek and get help from instructors.

As Ecampus moves forward with course development, these evidence-based practices will support the instructional design work to create high-quality online courses that provide students with the opportunities to develop, refine, and apply skills to navigate uncertainty, engage diverse viewpoints, and contribute meaningfully to a rapidly changing world. Ultimately, the Seeking Solutions initiative aligns with OSU’s mission to cultivate proactive global citizens, ensuring that graduates are not only career-ready but also prepared to drive positive societal change.

Conclusions

Instructional design for solution-seeking courses requires thoughtful course design that addresses perspective taking, team collaboration, team conflict, problem solving, and possibly large enrollments. Proactive conflict resolution frameworks, clear team roles, and collaborative tools help mitigate interpersonal challenges, fostering productive teamwork. Additionally, integrating structured problem-solving approaches (e.g., design thinking, systems analysis) equips students to tackle complex, ambiguous “wicked problems” while aligning course outcomes with real-world challenges. Together, these elements ensure a robust, adaptable curriculum that prepares students for dynamic problem-solving and sustains long-term program success.

References

Aggrawal, S., & Magana, A. J. (2024). Teamwork Conflict Management Training and Conflict Resolution Practice via Large Language Models. Future Internet, 16(5), 177-. https://doi.org/10.3390/fi16050177

Bikowski, D. (2022). Teaching large-enrollment online language courses: Faculty perspectives and an emerging curricular model. System. Volume 105

Head, B. (2008). Wicked Problems in Public Policy. Public Policy, 3 (2): 101–118.

McCune, V., Tauritz, R., Boyd, S., Cross, A., Higgins, P., & Scoles, J. (2023). Teaching wicked problems in higher education: ways of thinking and practising. Teaching in Higher Education, 28(7), 1518–1533. https://doi.org/10.1080/13562517.2021.1911986

Mohammed, T. F., Nadile, E. M., Busch, C. A., Brister, D., Brownell, S. E., Claiborne, C. T., Edwards, B. A., Wolf, J. G., Lunt, C., Tran, M., Vargas, C., Walker, K. M., Warkina, T. D., Witt, M. L., Zheng, Y., & Cooper, K. M. (2021). Aspects of Large-Enrollment Online College Science Courses That Exacerbate and Alleviate Student Anxiety. CBE Life Sciences Education, 20(4), ar69–ar69. https://doi.org/10.1187/cbe.21-05-0132

Oppert ML, Dollard MF, Murugavel VR, Reiter-Palmon R, Reardon A, Cropley DH, O’Keeffe V. A Mixed-Methods Study of Creative Problem Solving and Psychosocial Safety Climate: Preparing Engineers for the Future of Work. Front Psychol. 2022 Feb 18;12:759226. doi: 10.3389/fpsyg.2021.759226. PMID: 35250689; PMCID: PMC8894438.

Veltman, M., J. Van Keulen, and J. Voogt. (2019). Design Principles for Addressing Wicked Problems Through Boundary Crossing in Higher Professional Education. Journal of Education and Work, 32 (2): 135–155. doi:10.1080/13639080.2019.1610165.

This post was written in collaboration with Mary Ellen Dello Stritto, Director of Ecampus Research Unit.

Quality Matters standards are supported by extensive research on effective learning. Oregon State University’s own Ecampus Essentials build upon these standards, incorporating OSU-specific quality criteria for ongoing course development. But what do students themselves think about the elements that constitute a well-designed online course?

The Study

The Ecampus Research Unit took part in a national research study with Penn State and Boise State universities that sought student insight into what elements of design and course management contribute to quality in an online course. Data was collected from 6 universities across the US including Oregon State in Fall of 2024. Students who chose to participate completed a 73-item online survey that asked about course design elements from the updated version of the Quality Matters Rubric. Students responded to each question with the following scale: 0=Not important, 1=Important, 2=Very Important, 3=Essential. A total of 124 students completed survey, including 15 OSU Ecampus students. The findings reveal a remarkable alignment between research-based best practices and student preferences, validating the approach taken in OSU’s Ecampus Essentials.

See the findings in data visualization form below, followed by a detailed description.

Data visualization of the findings. See detailed description after the image.

What Students Consider Most Important

Students clearly value practical, research-backed features that make online courses easier to navigate, more accessible, and more supportive of learning. The following items received the most ratings of “Essential” + “Very Important”:

QM Standards and Study Findings	Related Ecampus Essentials
Accessibility and Usability (QM Standards 8.2, 8.3, 8.4, 8.5, 8.6): Every OSU student rated course readability and accessible text as “Very Important” or “Essential” (100%). Nationally, this was also a top priority (96% and 91%, respectively). Accessibility of multimedia—like captions and user-friendly video/audio—was also highly rated (100% OSU, 90% nationally).	Text in the course site is accessible. Images in the course are accessible (e.g., alt text or long description for images). The course design facilitates readability. All video content is accurately captioned.
Clear Navigation and Getting Started (QM Standards 1.1, 8.1): 93% of OSU students and 94% of the national sample rated easy navigation highly, while 89% of OSU students and 96% nationally said clear instructions for how to get started and where to find things were essential.	Course is structured into intuitive sections (weeks, units, etc.) with all materials for each section housed within that section (e.g., one page with that week’s learning materials rather than a long list of files in the module). Course is organized with student-centered navigation, and it is clear to students how to get started in the course.
Meaningful Feedback and Instructor Presence (QM Standards 3.5, 5.3): Students placed high importance on receiving detailed feedback that connects directly to course content (100% OSU, 94% nationally). The ability to ask questions of instructors was also essential (100% OSU, 96% nationally).	Assessments are sequenced in a way to give students an opportunity to build knowledge and learn from instructor feedback. The instructor’s plan for regular interaction with students in substantive ways during the course is clearly articulated. Information about student support specific to the course (e.g., links to the Writing Center in a writing course, information about TA open office hours, etc.) is provided.
Clear Grading Criteria (QM Standards 3.2, 3.3): 93% of OSU students and the full sample found clear, detailed grading rules to be essential.	Specific and descriptive grading information for each assessment is provided (e.g., detailed grading criteria and/or rubrics).
Instructional Materials (QM Standard 4.1): All OSU students and 92% nationally rated high-quality materials that support learning outcomes as very important or essential.	Instructional materials align with the course and weekly outcomes. A variety of instructional materials are used to appeal to many learning preferences (readings, audio, visual, multimedia, etc.). When pre-recorded lectures are utilized, content is brief and integrated into course learning activities, such as with interactive components, discussion questions, or quiz questions. Longer lectures should be shortened to less than 20 min. chunks.

What Students Consider Less Important

The study also revealed areas where students expressed less enthusiasm:

Study Findings	Related Ecampus Essentials
Self-Introductions (QM Standard 1.9): Over half of OSU students (56%) and a third nationally (33%) rated opportunities to introduce themselves as “Not Important”.	No specific EE
Peer Interaction (QM Standard 5.2): Students were lukewarm about peer-to-peer learning activities. Nearly half said that working in small groups is not important (47% OSU, 46% nationally). About a quarter didn’t value sharing ideas in public forums (27% OSU, 24% nationally) or having learning activities that encourage them to interact with other students (27% OSU, 23% nationally).	Three forms of interaction are present, in some form, in the course (student/content, student/instructor, student/student).
Technology Variety and Data Privacy Info (QM Standards 6.3, 6.4): Some students questioned the value of using a variety of tech tools (20% OSU, 23% nationally rated this as “Not Important”) or being given info about protecting personal data (20% OSU, 22% nationally).	Privacy policies for any tools used outside of Canvas are provided.

Student Comments

Here are a few comments from Ecampus students that illustrate their opinions on what makes a quality course:

“Accessible instructional staff who will speak to students in synchronous environments. Staff who will guide students toward the answer rather than either treating it like cheating to ask for help at all or simply giving out the answer.”
“A lack of communication/response from teachers and no sense of community” – was seen as a barrier.
“Mild reliance on e-book/publisher content, out-weighed by individual faculty created content that matches student deliverables. In particular, short video content guiding through the material in short, digestible amounts (not more than 20 minutes at a go).”
“When there aren’t a variety of materials, it makes it hard to successfully understand the materials. For example, I prefer there to be lectures or videos associated with readings so that I understand the material to the professor’s standards. When I only have reading materials, I can sometimes misinterpret the information.”
“Knock it off with the discussion boards, and the ‘reply to 2 other posts’ business. This is not how effective discourse takes place, nor is it how collaborative learning/learning community is built.”

Conclusion and Recommendations

The takeaways? This research shows that students recognize and value the same quality elements emphasized in OSU’s Ecampus Essentials:

Student preferences align with research-based standards – Students consistently value accessibility, clear structure, meaningful feedback, and purposeful content.
Universal design benefits everyone – Students’ strong preference for accessible, well-designed courses supports the universal design principles embedded in the Ecampus Essentials.

However, there is always room for improvement, and these data provide some hints. Many students don’t immediately see value in peer interactions and collaborative activities, even though extensive educational research shows these are among the most effective learning strategies. Collaborative learning is recognized as a High Impact Practice that significantly improves student outcomes and critical thinking. This disconnect suggests we need to design these experiences more thoughtfully to help students recognize their benefits. Here are some suggestions:

Frame introductions purposefully: Instead of generic “tell us about yourself” posts, connect introductions to course content (“Introduce yourself and share an experience related to the topic of this course”).
Design meaningful group work: Create projects that genuinely require collaboration and produce something students couldn’t create alone.
Show the connection: Explicitly explain how peer interactions help students learn and retain information better, and the value of teamwork for their future jobs.
Start small: Begin with low-stakes peer activities before moving to more complex collaborations.

Core Education Curriculum Reform and Implementation

The summer of 2025 marks a new era in general education at Oregon State University. After years of collaboration among faculty, students, and community partners, OSU has crafted a forward-thinking general education program designed to empower the next generation of global leaders.

The Core Education Curriculum will be implemented starting June 23, and students enrolling in this term and beyond will begin their academic journeys at OSU by gaining knowledge and skills through two major curriculum areas: the Foundational Core and the Signature Core.

Re-envisioning Education

OSU has undergone a multi-year curriculum reform in which faculty, students, staff, alumni, community partners, and administrators came together to develop a state-of-the-art, 21st-century-focused general education program. The Core Ed curriculum underscores students’ potential to become global innovators and critical agents of societal change. By integrating real-world problem-solving and social responsibility, Core Education embodies OSU’s land-grant mission to serve communities locally and globally.

The new curriculum incorporates high-impact practices intended to support student learning and prepare them to meet challenges, solve problems, adapt to a rapidly changing world, and become proactive members of society, advancing their fields of study. These practices—defined as strategies that promote deeper learning, meaningful engagement, and a positive impact on historically underserved student populations (Kuh & O’Donnell, 2013)—are central to Core Education. As stated in the Core Education mission, the curriculum also “addresses the ever-changing needs of our learners and graduates in our global society and promotes critical thinking, information literacy, social and environmental justice, interdisciplinary teamwork, and communication.” (Core Education)

Uniqueness of Core Education

The Core Ed curriculum is defined by two main areas: the Foundational Core and the Signature Core, which offer students a variety of learning opportunities. The Foundational Core helps students build essential skills and broad knowledge, fostering lifelong learning and creative problem-solving, while preparing them to engage with complex topics in academic and professional settings. The Signature Core empowers students to apply critical thinking to create positive change in their field and society, while strengthening the skills needed to navigate a complex, interconnected world.

The Foundational Core includes the following categories:

Writing Foundations (4 credits)
Arts and Humanities – Global and General (6–8 credits; 2 courses)
Quantitative Literacy and Analysis (4 credits)
Communication, Media, and Society (3 credits)
Social Science (3–4 credits)
Scientific Inquiry and Analysis (8 credits; 2 courses from two different designators)
Difference, Power, and Oppression Foundations (3–4 credits)

The Signature Core includes the following categories:

Transitions (2 credits)
Beyond OSU Career Integration (0 credits)
Difference, Power, and Oppression Advanced (3–4 credits)
Seeking Solutions (3–4 credits)
Writing Elevation (3 credits)
Writing Intensive Curriculum (In Major)

A standout feature of Core Education is the Beyond OSU Career Integration component, which equips students with NACE-aligned competencies for lifelong career success. This component offers students opportunities to explore and apply career-related practices, including career readiness and advancement. It focuses on building core skills for workplace success and lifelong career management, based on the NACE Career Competencies.

Preparing to Launch Core Education

The Core Education reform process dates back to 2002, when OSU initiated a review of the Baccalaureate Core Curriculum. Since then, the OSU community has worked intensively to design, develop, and implement the new general education curriculum. Ecampus has been no exception—each Ecampus team (e.g., Course Development) has actively strategized its work to support this transition. Specifically, the Instructional Design (ID) Team at Ecampus has launched iterative course design initiatives to inform, test, and evaluate the course design process and resources. These initiatives include:

Difference, Power, and Oppression Working Group: A group of four instructional designers (IDs) met regularly during Winter 2025 to review the DPO learning outcomes, criteria, and rationale and to draft a DPO Course Design Guide. This guide provides questions and considerations IDs can use during course intakes, development, and resource support.
Outcomes and Alignment Working Group: Two IDs led the creation of a guide and template to support the alignment of Core Education outcomes (CSLOs) with course assignments. The template includes a spreadsheet to document the alignment of exam questions with outcomes, offering instructors a clear and structured strategy for maintaining consistency.
Seeking Solutions Professional Learning Community: A group of eight IDs tasked with designing Seeking Solutions courses launched a professional learning community (PLC) in late Fall 2024 and continued into Spring 2025. The PLC reviewed the learning outcomes, criteria, and rationale and developed a detailed Course Design Guide to assist the ID team in planning course intakes and providing follow-up support to instructors.
Core Ed Outcomes and Alignment Review Group. A group of five IDs served as peer reviewers for a guide on the Alignment of CSLOs to the Essential Assignment(s) in Canvas. This resource guides IDs step-by-step through the process of linking the appropriate CSLOs to the course Essential Assignment(s) so that samples of student work can be used for Core Education category assessment. With this guide, IDs can support course developers in making the alignment visible in Canvas.
Core Education Course Development Guide. This guide provides the ID team with a comprehensive guide on the development of Core Education, Baccalaureate Core, and Writing Intensive Courses.

Although the course design guides are fully drafted and available to the ID team, the working groups continue to communicate regularly for updates and improvements.

The OSU community—especially Ecampus’s dedicated teams—has worked tirelessly to bring Core Education to life. Their collaborative spirit and innovation have been instrumental in shaping this transformative curriculum. I’m very proud of the initiatives we’ve undertaken, and it has been an honor to lead them. This blog highlights my colleagues’ work and the Ecampus leadership team’s guidance, especially the Course Development and Training Unit leaders, who have fully supported the initiatives.

I invite you to explore the full Core Education Curriculum or contact Karen Watte karen.watte@oregonstate.edu for online course development.

References

Oregon State University. (2025). Core Education
Kuh, George D. & O’Donnell, K. (2013). Ensuring quality & taking high-impact practices to scale. Washington, DC: Association of American Colleges & Universities.

Over the past few years, Higher Education (HE) has been called to action in response to the rise of Generative Artificial Intelligence (GenAI) tools. As Artificial Intelligence (AI) becomes more autonomous and capable, proactive steps are needed to preserve academic and learning integrity. This article will explore tangible strategies educators can apply to their unique program and course contexts. Only slight adjustments may be necessary to support learning processes and capture evidence of learning, as changes will build upon the excellent work that is already occurring.

Initially, the focus in HE was on understanding the potential impact these tools would have on teaching and learning. Awareness of GenAI capabilities, limitations, and risks has been acknowledged with great care. Today, the tools are now being tested, and educators are envisioning how to use them for various purposes (e.g., productivity, creativity). Integration of these tools has begun with the aim of supplementing and enhancing human learning. As we move forward, concerns with regard to academic and learning integrity become increasingly prominent.

Meet Agentic AI

Recently, I had the opportunity to attend the Quality Matters Quality in Action conference, where I attended the session Ensuring Academic Integrity and Quality Course Design in the Age of AI. The presenter Robert Gibson, Director of Instructional Design at WSU Tech, shared about an Artificial Intelligence (AI) innovation now available to the public (and our students)….meet Agentic AI!

Your new Agentic AI assistant no longer requires you to be an expert prompt engineer. These tools are designed to achieve specific and clear goals with minimal human supervision or oversight. Engagement in complex reasoning, decision making, problem solving, learning from new information, and adapting to environments can occur autonomously (Gibson, 2025; Schroeder, 2025; Marr, 2025). These new Agentic AIs can even work together to form what is known as an Orchestrated AI. Think of this as an AI team working collaboratively to accomplish complex tasks. Agentic AI has already demonstrated the capability to create and complete online courses. What does this mean for Higher Education?

Now more than ever, we need to come together to collectively reinforce academic and learning integrity in online and hybrid courses. Preserving the quality of our institutional products and credentials is essential. Equally important are the students who will apply their OSU-acquired knowledge and skills in the real world. The time to be proactive is now.

Where and how should I start?

A good starting point is to evaluate assessments that AI can complete. Running an assignment through a GenAI tool to see if it can complete the task, with relative accuracy, can produce helpful insights. Next, consider modifications to pedagogical approaches and assessment methods. The goal is to design assessments to produce and capture evidence that learning is taking place. This could include assessments that are process-oriented, focus on skill mastery, are personalized, incorporate visual demonstrations (e.g., video), and/or integrate real-time engagement (Gibson, 2025).

What might a reimagined activity look like?

For example, let us say an instructor uses case-based learning in their course, and small groups discuss real-world scenarios on a discussion board. This activity could be reimagined by having students meet virtually and record their discussion. During their real-time interaction, they examine a real-world scenario, identify associated evidence, present examples, and share their lived experiences. This would be similar to how students conduct group presentations currently. This approach could be enhanced by shifting the focus to the learning process, such as arriving at ideas and cultivating perspectives (i.e., learning, growth, development). This would be in lieu of having students find a right or wrong answer (Gibson, 2025). This approach encourages students to engage substantively, co-construct knowledge, and work together to demonstrate learning. After participating in the activity, each student could create an individual video presentation to synthesize their learning. A synthesis video could include discussing their initial perspectives (Where did I start? – prior knowledge activation), how those initial perspectives evolved (What was my cognitive process? – metacognition), what new knowledge is needed (gap analysis), and how my perspectives and knowledge change (learning reflection). This method reinforces academic and learning integrity by validating that students are learning and achieving outcomes (Bertram-Gallant, 2017).

Reflect! Take a moment to reflect on how you know that students are learning in your course(s). What evidence do you have?

While the potential for academic dishonesty cannot be entirely controlled, there should not be an assumption that students will use these tools in their coursework just because they are available. Take a moment to examine the Ecampus Research Unit’s research, “Student Perceptions of Generative AI Tools in Online Courses.” This research study explores online students’ perceptions, understanding, and use of GenAI tools. The study found that most students had not been using GenAI tools in their courses, but rather, they were primarily using GenAI tools within professional contexts. Students noted that they understood that using AI in their careers would be necessary. However, strong concerns were articulated around inaccuracies, biases, lack of reliability, propagation of misinformation, and that the use of the tools is not in alignment with their personal values and ethics. (Dello Stritto, M, Underhill, G. and Aguiar, N., 2024).

How can academic and learning integrity be reinforced?

Educators can foster academic integrity in a way that drives students’ internal motivation, self-determination, and desire to demonstrate their learning because they value the work they are doing. A multifaceted developmental approach that fosters a culture of academic integrity using various strategies in concert with one another is key (Bertram-Gallant, 2025), as no single approach can serve as a definitive solution.

Integrity teaching – Taking on the role of an active guide during course delivery and meeting students where they are developmentally is essential. This may include teaching students how to engage in critical thinking around the use of AI tools, connect the value of academic and learning integrity to their future profession, how to make well-informed decisions, and how to leverage metacognitive strategies when engaging with AI.
Integrity messaging – This approach is one that can be most effective if holistically integrated into a course. The content communicates that integrity, values, and ethics are normative within the course and will be held at the forefront of the learning community. Staged and timed messaging can be most helpful when targeted at different points in a course and as the complexity of academic work increases.
Transformative real time experiential learning – Transformative experiential learning involves designing opportunities that generate new ideas for action, which can be applied to other experiences. These activities may include, but are not limited to, service learning, internships, hands-on collaborative activities (e.g., role play, point-counterpoint discussions), and demonstrations. By focusing on real-time engagement, this approach demonstrates learning and thereby reinforces academic and learning integrity.
Deep learning – Learning opportunities focused on skill mastery and demonstration through staged attempts. This approach may necessitate a pedagogical shift focusing on development and growth (Bertram-Gallant, 2025).

Agentic AI brings exciting opportunities for the world but tangible challenges for HE. By intentionally designing assessments that lead students to demonstrate evidence of their learning and using facilitation strategies that foster a culture of academic integrity, we can harness the potential of AI to supplement learning. What is the end goal? To ensure that educational opportunities are designed to preserve and enhance learners’ critical skills and knowledge needed to thrive in their professional pursuits. Will you accept this challenge?

Ecampus Artificial Intelligence Tools Resource Inventory

Trying to decide when and how to incorporate AI into your work? Take a look at the AI Decision Tree!
Need a few quick, practical strategies to get started? These recommendations aim to improve learning for both teachers and students.
Are you ready to evaluate and enhance the resiliency (i.e., flexibility, adaptability) of your course within the context of AI? Check out the new The Course AI Resilience Tracker [CART] interactive tool. This interactive tool can help you reflect on various course elements and will share personalized resources to help you get started.
Review Bloom’s Taxonomy Revisited to explore how to emphasize distinctive human skills and/or integrate AI tools to supplement the learning process.
Explore our AI Assessment Examples Library for assessment ideas designed to incorporate AI tools and strategies in your course and/or create more human-centric assessments.

Sources

Bertram Gallant, T. (2017). Academic Integrity as a Teaching & Learning Issue: From Theory to Practice. Theory into Practice, 56(2), 88–94.
Bertram Gallant, T. & Rettinger, D. (2025, March 11). The Opposite of Cheating: Teaching for Integrity in the Age of AI. University of Oklahoma Press.
Dello Stritto, M. E., Underhill G. R., & Aguiar, N. R. (2024). Online Students’ Perceptions of Generative AI. Oregon State University Ecampus Research Unit. https://ecampus.oregonstate.edu/research/publications/
Gibson, R. (2025, April 10). Ensuring Academic Integrity and Quality Course Design in the Age of AI [Conference presentation]. Quality Matters Quality in Action 2025. Virtual.
Marr, B. (2025, February 3). Generative AI Vs. Agentic AI: The Key Differences Everyone Needs to Know. Forbes.
Purdy, M. (2024, December 12). What is Agentic AI, and How Will it Change Work. Harvard Business Review.
Schroeder, R. (2025, February 5). Setting a Context for Agentic AI in Higher ED. Upcea.

About the Author

Connect with Ashlee! Email | Linkedin

Ashlee M. C. Foster, MSEd, is a seasoned Instructional Designer with the Oregon State University Ecampus Course Development and Training Team. With a profound commitment to supporting faculty and students in online teaching and learning, Ashlee’s mission is to design high-quality and innovative educational opportunities that foster transformational learning, development, and growth. Ashlee’s learning design approaches are grounded in research-based insights, foundational learning theories, and the thoughtful integration of industry-led practices. This ensures that each educational experience is not only effective but also engaging and relevant.

This is a guest post by Winter 2025 Ecampus Instructional Design Intern Terrence Scott.

Creating Online Learning Spaces Where Adult Learners Belong

Today’s college students are increasingly adults returning to education to pursue career shifts, personal growth, or new credentials. Yet, this return often brings discomfort. Adult learners find themselves in a liminal space, caught between who they were and who they are becoming as students. This “in-between” state is a psychological and social threshold where identity and belonging are in flux (Maksimović, 2023; Turner, 1969).

Liminal space is defined as “characterized by the questioning and reexamination of one’s identity, often as a result of transitional moments in an individual’s life such as separation, loss, and conflicts” (Maksimović, 2023). Rather than a moment, adult learners experience the entire educational journey—from enrollment to graduation—as a liminal space. Supporting learners through this journey requires intentional course design that centers on inclusion and belonging.

Online Learning as a Threshold

As Johnson (2022) and Maksimović (2023) describe, adult learners often navigate identity shifts as they move from familiar roles in work or family life into the unfamiliar space of studenthood. For some, prior negative school experiences further intensify feelings of isolation during this transition.

Adult learners in liminal space often struggle with:

Imposter Syndrome: “Am I really capable of doing this?”
Identity Conflict: “Am I a student now, or still just a working professional?”
Social Isolation: “Do I belong here, or am I too different from my classmates?”
Fear of Failure: “What if I don’t succeed and let myself or my family down?”

Without a strong sense of belonging, these feelings can lead to disengagement or dropout. But when courses are designed to recognize this liminal space, learners are more likely to persist and thrive (Mezirow, 1991).

The Role of Belonging in Adult Learning

Belonging is a powerful driver of student success, especially for those from nontraditional backgrounds. It’s not just about showing up—it’s about feeling seen, respected, and included. When learners experience psychological safety and validation, motivation and commitment grow (Strayhorn, 2019).

How Does Belonging Develop?

Representation: Course content should reflect diverse identities and lived experiences.
Identity Validation: Recognize the knowledge adult learners bring with them.
Connection: Encourage interaction through group work, discussion forums, or mentorship.
Flexibility: Design with life responsibilities in mind—multiple paths to participation and success.

These elements help learners cross the threshold from “outsider” to “insider,” evolving from questioning their role in higher education to fully embracing it.

UDL 3.0: Designing for Inclusion and Belonging

Universal Design for Learning offers a framework for inclusive online course design. The latest iteration, UDL 3.0, centers identity, belonging, and engagement more explicitly than ever (CAST, 2024). It urges instructors to create spaces where students feel welcomed and recognized, not just accommodated.

How UDL Supports Adult Learners in Liminal Spaces

Engagement: Make content relevant with real-world examples, reflection exercises, and collaborative activities.
Representation: Use varied media—text, video, podcasts, interactive tools—and include voices that reflect learners’ identities.
Action & Expression: Offer multiple ways to demonstrate understanding with flexible formats, low-stakes practice, and accommodations for life’s demands.

When courses reflect these principles, adult learners gain the confidence to move through uncertainty and emerge with a stronger academic identity.

Conclusion

Liminal spaces—the uncertain, transitional moments in adult learning—can be both challenging and transformative. While some learners struggle with identity shifts, imposter syndrome, or social isolation, institutions that prioritize belonging and inclusive design can help them navigate these transitions successfully.

Higher education can foster a sense of belonging and empowerment for adult learners by integrating UDL 3.0 principles into course design and student support services. Welcoming students, valuing their diverse experiences, and establishing supportive learning environments are essential to addressing students’ unique needs and ensuring their success.

References

CAST (2024). UDL Guidelines 3.0: Universal Design for Learning.
De Abreu, K. (2023, August 7). Extreme coming of age rituals. ExplorersWeb. Link
Johnson, K. (2022). Beginning, Becoming and Belonging: Using Liminal Spaces to Explore How Part-Time Adult Learners Negotiate Emergent Identities. Widening Participation and Lifelong Learning, 24(2).
Maksimović, M. (2023). Insights from Liminality: Navigating the Space of Transition and Learning. Sisyphus–Journal of Education, 11(1).
Mezirow, J. (1991). Transformative dimensions of adult learning. Jossey-Bass.
Turner, V. (1969). The ritual process: Structure and anti-structure. Cornell University Press.
Strayhorn, T. L. (2019). College Students’ Sense of Belonging: A Key to Educational Success for All Students (2nd ed.). Routledge.

chart describing the steps in the feedback process

In part one of this two-part blog series, we focused on setting the stage for a better feedback cycle by preparing students to receive feedback. In part two, we’ll discuss the remaining steps of the cycle- how to deliver feedback effectively and ensure students use it to improve.

In part one, we learned about the benefits of adding a preliminary step to your feedback system by preparing students to receive suggestions and view them as helpful and valuable rather than as criticism. If you haven’t read part one, I recommend doing so before continuing. This first crucial but often overlooked step involves fostering a growth mindset and creating an environment where students understand the value of feedback and learn to view it as a tool for improvement rather than criticism.

Step 2: Write Clear Learning Outcomes

The next step in the cycle is likely more familiar to teachers, as much focus in recent decades has been placed on developing and communicating clear, measurable learning outcomes when designing and delivering courses. Bloom’s Taxonomy is commonly used as a reference when determining learning outcomes and is often a starting point in backwards design strategy. Instructors and course designers must consider how a lesson, module, or course aligns with the learning objectives so that students are well-equipped to meet these outcomes via course content and activities. Sharing these expected outcomes with students, in the form of CLOs and rubrics, can help them to focus on what matters most and be better informed about the importance of each criterion. These outcomes should also inform instructors’ overall course map and lesson planning.

Another important consideration is ensuring that learning outcomes are measurable, which requires rewriting unmeasurable ones that begin with verbs such as understand, learn, appreciate, or grasp. A plethora of resources are available online to assist instructors and course designers who want to improve the measurability of their learning outcomes. These include our own Ecampus-created Bloom’s Taxonomy Revisited and a chart of active and measurable verbs from the OSU Center for Teaching and Learning that fit each taxonomy level.

Step 3: Provide Formative Practice & Assessments

The third step reminds us that student learning is also a cycle, overlapping and informing our feedback cycle. When Ecampus instructional designers build courses, we try to ensure instructors provide active learning opportunities that engage students and teach the content and skills needed to meet our learning objectives. We need to follow that up with ample practice assignments and assessments, such as low-stakes quizzes, discussions, and other activities to allow students to apply what they have learned. This in turn allows instructors to provide formative feedback that should ideally inform our students’ study time and guide them to correct errors or revisit content before being formally or summatively graded. Giving preliminary feedback also gives us time to adjust our teaching based on how students perform and hone in on what toreview before assessments. Providing practice tests or assignments or using exam wrappers, exit cards, or “muddiest point” surveys to collect your students’ feedback can also be an important practice that can help us improve our teaching.

Step 4: Make Feedback Timely and Actionable

Step four is two-fold, as both the timeliness and quality of the feedback we give are important. The best time to give feedback is when the student can still use it to improve future performance. When planning your term schedule, it can be useful to predict when you will need to block off time to provide feedback on crucial assignments and quizzes, as a delay for the instructor equates to a delay for students. Having clear due dates, reminding students of them, and sticking to the timetable by giving feedback promptly are important aspects of giving feedback.

To be effective, feedback must focus on moving learning forward. It should target the identified learning gap and suggest specific steps for the student to improve.. For a suggestion to be actionable, it should describe actions that will help the student do better without overloading them with too much information- choose a few actionable areas to focus on each time. Comments that praise students’ abilities, attitudes, or personalities are not as helpful as ones that give them concrete ways to improve their work.

Step 5: Give Time to Use Feedback and Incentive it

The last step in the cycle, giving students time to use the feedback provided, is often relegated to homework or ignored altogether. Feedback is most useful when students are required to view it and preferably do something with it, and by skipping this important step, the feedback might be ignored or glanced over perfunctorily and promptly forgotten. To close the loop, students must put the feedback to use. This can be the point where your feedback cycle sputters out, so be sure to make time to prioritize this final step. Students may need assistance in applying your feedback. Guiding students through the process, and providing scaffolds and models for using your feedback can be beneficial, especially during the initial attempts.

In my experience, it never hurts to incentivize this step: this can be as simple as adding points to an assignment for reflecting on the feedback given or giving extra credit opportunities around redone work. As a writing teacher, I required rewrites for work that scored below passing and offered to regrade any rewritten essays incorporating my detailed feedback. This proved to be a good solution, and while marking essays was definitely labor intensive, I was rewarded with very positive feedback from my students, often commenting that they learned a lot and improved significantly in my courses.

Considerations

A robust feedback cycle often includes opportunities for students to develop their own feedback skills by performing self-assessments and peer reviews. Self-assessment helps students in several ways, promoting metacognition and helping them learn to identify their own strengths and weaknesses. It also allows students to reflect on their study habits and motivation, manage self-directed learning, and develop transferable skills. Peer review also provides valuable practice honing their evaluative skills, using feedback techniques, and giving and receiving feedback, all skills they will find useful throughout adulthood. Both self-assessment and peer review give students a deeper understanding of the criteria teachers use to evaluate work, which can help them fine-tune their performance.

Resources for learning more:

Feedback

Learning Outcomes

Self-assessment

Exam Wrappers – Eberly Center – Carnegie Mellon University
- Lots of downloadable samples of exam wrappers for different subject areas.
Self-Assessment | Center for Teaching Innovation

Peer review

graphic image of the five steps in the feedback cycle

Giving and receiving feedback effectively is a key skill we all develop as we grow, and it helps us reflect on our performance, guide our future behavior, and fine-tune our practices. Later in life, feedback continues to be vital as we move into work and careers, getting feedback from the people we work for and with. As teachers, the most important aspect of our job is giving feedback that informs students how to improve and meet the learning outcomes to pass our courses. We soon learn, however, that giving feedback can be difficult for several reasons. Despite it being one of our primary job duties as educators, we may have received little training on how to give feedback or what effective feedback looks like. We also realize how time-consuming it can be to provide detailed feedback students need to improve. To make matters worse, we may find that students don’t do much with the feedback we spend so much time providing. Additionally, students may not respond well to feedback- they might become defensive, feel misunderstood, or worse, ignore the feedback altogether. This can set us up for an ineffective feedback process, which can be frustrating for both sides.

I taught ESL to international students from around the world for more than 10 years and have given a fair amount of feedback. Over many cycles, I developed a detailed and systematic approach for providing feedback that looked like this.

Gaps in this cycle can lead to frustration from both sides. Each step in the cycle is essential, so we’ll look at each in greater depth in this blog series. Today, we will focus on starting strong by preparing students to receive feedback, a crucial beginning that sets the stage for a healthy cycle.

Step 1: Prepare Students to Receive Feedback

An effective feedback cycle starts before the feedback is given by laying careful groundwork. The first and often-overlooked step in the cycle is preparing students to receive feedback, which takes planned, ongoing work. Various factors may influence whether students welcome feedback, including their self-confidence going into your course, their own self-concept and mindset as a learner, their working memory and learning capacity, how they view your feedback, and whether they feel they can trust you. Outside factors such as motivation and working memory are often beyond our control, but creating an atmosphere of trust and safety in the classroom can positively support students. Student confidence and mindset are areas in which teachers can play a crucial supporting role.

Researcher Carol Dweck coined the term “growth mindset” after noticing that some students showed remarkable resilience when faced with hardship or failure. In contrast, others tended to easily become frustrated and angry, and tended to give up on tasks. She developed her theory of growth vs. fixed mindsets to explain and expound on the differences between these two mindsets. The chart below shows some of the features of each extreme, and we can easily see how a fixed mindset can limit students’ resilience and persistence when faced with difficulties.

graphic of brain with growth mindset hallmarks on the left and fixed mindset ideas on the right.

Mindset directly impacts how students receive feedback. Research has shown that students who believe that their intelligence and abilities can be developed through hard work and dedication are more likely to put in the effort and persist through difficult tasks, while those who see intelligence as a fixed, unchangeable quality are more likely to see feedback as criticism and give up.

Developing a growth mindset can have transformative results for students, especially if they have grown up in a particularly fixed mindset environment. People with a growth mindset are more likely to seek out feedback and use it to improve their performance, while those with a fixed mindset may be more likely to ignore feedback or become defensive when receiving it. Those who receive praise for their effort and hard work, rather than just their innate abilities, are more likely to develop a growth mindset. This is because they come to see themselves as capable of improving through their own efforts, rather than just relying on their natural talents. A growth mindset also helps students learn to deal with failure and reframe it positively. It can be very difficult to receive a critique without tying our performance to our identity. Students must have some level of assurance that they will be safe taking risks and trying, without fear of being punished for failing.

Additionally, our own mindset affects how we view student effort, and we often, purposefully or not, convey those messages to students. Teachers with growth mindsets have a positive and statistically significant association with the development of their students’ growth mindsets. Our own mindset affects the type of feedback we are likely to provide, the amount of time we spend on giving feedback, and the way we view the abilities of our students.

These data suggest that taking the time to learn about and foster a growth mindset in ourselves and our students results in benefits for all. Teachers need to address the value of feedback early on in the learning process and repeatedly throughout the term or year, and couching our messaging to students in positive, growth-oriented language can bolster the feedback process and start students off on the right foot, prepared to improve.

Here are some concrete steps you can take to improve how your students will receive feedback:

Model a growth mindset through language and actions
Include growth-oriented statements in early messaging
Provide resources for students to learn more about growth vs. fixed mindsets
Discuss the value of feedback and incorporate it into lessons
Create an atmosphere of trust and safety that helps students feel comfortable trying new things
Teach that feedback is NOT a judgment of the person, but rather a judgment on the product or process
Ensure the feedback we give focuses on the product or process rather than the individual
Praise effort rather than intelligence
Make it clear that failure is part of learning and that feedback helps improve performance
Provide students with tools and strategies to plan, monitor, and evaluate their learning

Resources for learning more about growth mindset and how it relates to feedback:

Stay tuned for part 2, covering the remaining steps in the feedback cycle.

The response

The new situation – Enter AI

Scenario

Some background studies

Undetected

What to do…?

Embracing the situation: The reflective AI honor log

What is it?

Log layout example

Potential deployment tasks (and things to look out for)

Important considerations when planning AI-tasks

Conclusion

Footnotes

References

Start with a warm welcome

Open your course early

Keep communication open

Model engagement

Be accessible

Grade consistently and give meaningful feedback

Stay organized

Take care of yourself

Seamless Collaboration Across Projects and Courses

Enhanced Communication and Community Building

Easy Oversight for Seeking Solutions Courses

Conclusion

Wicked Problems

Applications for instructional designers:

Team Conflict and Teamwork

Application for Instructional Design

Problem Solving

Application for Instructional Designers

Large Enrollment Online Courses

Applications for Instructional Design

Conclusions

References

The Study

What Students Consider Most Important

What Students Consider Less Important

Student Comments

Conclusion and Recommendations

Core Education Curriculum Reform and Implementation

Re-envisioning Education

Uniqueness of Core Education

Preparing to Launch Core Education

References

Meet Agentic AI

Where and how should I start?

What might a reimagined activity look like?

How can academic and learning integrity be reinforced?

Ecampus Artificial Intelligence Tools Resource Inventory

Sources

About the Author

Creating Online Learning Spaces Where Adult Learners Belong

Online Learning as a Threshold

The Role of Belonging in Adult Learning

How Does Belonging Develop?

UDL 3.0: Designing for Inclusion and Belonging

How UDL Supports Adult Learners in Liminal Spaces

Conclusion

References

Step 2: Write Clear Learning Outcomes

Step 3: Provide Formative Practice & Assessments

Step 4: Make Feedback Timely and Actionable

Step 5: Give Time to Use Feedback and Incentive it

Considerations

Resources for learning more:

Feedback

Learning Outcomes

Self-assessment

Peer review

Resources for learning more about growth mindset and how it relates to feedback:

Contact Info