Category: collaborative learning

Beyond Breakout Rooms: Deepening Learning with Collaborative Whiteboards – Faculty Focus
Distance learning is here to stay. Both students and educators were required to quickly pivot to distance platforms during the COVID-19 pandemic without adequate preparation or training (Basilotta-Gomez-Pablos et al. 2022). Many programs elected to keep distance and hybrid learning options for students, with excellent reason. These platforms improve convenience, access, and inclusivity, gaining fast traction. Now, many institutions have an opportunity, or arguably a responsibility, to provide educators with the support needed to be successful while teaching in distance modalities; concurrently, educators are responsible for seeking resources and training to help them leverage technologies to thrive in this distance space (Crompton and Sykora 2021).

The use of technology in distance platforms is important; educators need to navigate a learning platform but don’t necessarily need to become digital technology experts (Crompton and Sykora 2021). So, what is possibly most important? Finding tools that are simple to use and have a high impact. Many educators still report that they do not feel equipped to apply new technologies, although today’s adult learners prefer novel and engaging technology tools (Borte, Nesje, and Lillejord 2023). Therefore, us educators should discuss, introduce, and share these technologies as we discover them to figure this out as a team.

In this article, we will explore how collaborative technologies, specifically collaborative whiteboards, can help bring life to adult learning theories in synchronous learning classrooms.

Students in distance learning platforms often have fewer opportunities to work collaboratively, outside of a break-out-room model, providing challenges for meaningfully applying adult learning theories. Theoretically speaking, collaboration and social engagement are essential components of adult learning, specifically to create a sense of community with learners, which can be more challenging in distance learning classes (Barbetta 2023; Shea, Richardson, and Swan 2022). Additionally, engaging students in more cognitively demanding ways, such as creating, analyzing, or developing information, is especially important to achieve higher-level learning outcomes (Vargas et al. 2024). Therefore, if we can strategically find ways to use digital technologies grounded in adult learning theory, we can strengthen the learning experience, enhance learning outcomes, and bridge the gap between theory and content delivery.

Many digital technologies and platforms exist and are met with opportunities and challenges. Time constraints and cost are common barriers (Borte, Nesje, and Lillejord 2023); therefore, free tools with relatively low preparation are prioritized. The Microsoft Collaborative Whiteboard app, which can be integrated within a Microsoft Teams Meeting space as a screen share, allows students to edit a document or template for more naturalistic collaborations simultaneously. Because it can be integrated into the meeting space, students do not need to download an app, leave the meeting, or switch to a new browser to participate. The form can be prepared before a lesson to allow instructors flexibility in their role and level of scaffolding.

Real-World Examples

A collaborative whiteboard can be applied to various programs, topic areas, or overall aims, and it may also be used as a formative assessment of content delivery. The examples included in this article were used in two separate synchronous occupational therapy courses, one focused on a neuroscience recap of the cranial nerves and one on adapting a therapeutic activity for different levels of traumatic brain injury rehabilitation. Pay special attention to the variance between the levels of learning targeted and how this is reflected in the collaborative efforts of the students.

Basic-level Whiteboard

This synchronous whiteboard was used at the beginning of the class session to serve as a formative assessment of the understanding of basic concepts of content. The 24 students were asked to match the function’s cranial nerve name, number, and a representative emoji. This was a more simplistic board that allowed students to reorganize the information presented at a basic knowledge-attainment level collaboratively. It was helpful as a formative assessment to adapt the rest of the lesson according to the students’ level of understanding, and their pace and accuracy of completion. In this case, the students moved their pointers to arrange the information simultaneously, with only a few attempts to collaborate verbally. This activity provided a collaborative effort to complete a joint, goal-oriented task.

Before

After

Advanced-level Whiteboard

The synchronous whiteboard in this example was created for a higher level of application-based learning, where 11 students were asked to alter components of an occupation and treatment modality, baking cookies, to apply to each unique level of traumatic brain injury recovery. This activity demanded greater levels of problem-solving and, therefore, greater levels of collaboration within the class. Many discussions and opportunities for problem-solving and aims for collective approval arose. To close the learning activity, I led a group debrief to discuss each level, provided immediate feedback, and facilitated discussions transferable to other real-world applications. In this example, the directions are in the middle, and the students filled in the sticky notes around the perimeter.

Make it Meaningful

We need buy-in and motivation in higher education. This begins with identifying real-world challenges and ends with reflection. The strategic use of digital technologies, specifically when combined with theoretical reasoning and adult learning principles, can improve classroom experiences through a greater sense of community while targeting higher levels of learning. If we are intentional with this design, educators can increase student engagement and facilitate higher levels of learning in synchronous online classrooms. Sprinkle goal-oriented and real-world relevant material on top, and you have a recipe for a meaningful outcome.

Looking Ahead

With institutions more widely embracing long-term implementation of distance education programs, faculty require ongoing support, training, and access to resources for sustained confidence and success. Dissemination of practical examples of use by peer educators and texts outlining an approach to identify and develop materials will benefit ongoing efforts to increase competency. In other words, we must keep each other informed on educational tech-gems we find to collectively improve our system.

How to Whiteboard: Quick Start Guide
1. Open Microsoft Teams
1. Click on the Whiteboard tab in your meeting space
1. Upload an editable template or create a blank canvas
1. Once in your meeting, share your screen and select the whiteboard app
1. Scaffold your task with prompts and questions
Jaimee Fielder, OTD, OTR is an Assistant Professor of Occupational Therapy at the University of St. Augustine for Health Sciences. She earned her Master of Science in Occupational Therapy from Touro University Nevada, Post-Professional Doctorate in Occupational Therapy from Texas Woman’s University, and is now pursuing a Doctorate in Education from the University of St. Augustine for Health Sciences, with a dissertation focused on educational technology and active learning in higher education classrooms.

References

Barbetta, Patricia M. 2023. “Technologies as Tools to Increase Active Learning During Online Higher-Education Instruction.” Journal of Educational Technology Systems 51(3): 317–339.

Basilotta-Gomez-Pablos, Verónica, Matarranz, María, Casado-Aranda, Luis A., and Otto, Andreas. 2022. “Teachers’ Digital Competencies in Higher Education: A Systematic Literature Review.” International Journal of Educational Technology in Higher Education 19(8).

Børte, Kristi, Nesje, Kjersti, and Lillejord, Sølvi. 2023. “Barriers to Student Active Learning in Higher Education.” Teaching in Higher Education 28(3): 597–615.

Crompton, Helen, and Sykora, Christopher. 2021. “Developing Instructional Technology Standards for Educators: A Design-Based Research Study.” Computers and Education Open 2: 100044.

Shea, Peter, Richardson, Jennifer, and Swan, Karen. 2022. “Building Bridges to Advance the Community of Inquiry Framework for Online Learning.” Educational Psychologist 57(3): 148–161.

Vargas, Jesús H., Ojeda, Edison C. C., Zapata, Carlos A. C., Flores, Karen A. A., Vela, Juan A. H., and Espinoza, Yessenia E. D. 2024. “Analysis of Significant Learning in Higher Education: Usefulness of Fink’s Taxonomy: A Systematic Review.” Journal of International Crisis and Risk Communication Research 7(S7): 1341.
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November 12, 2025
The Collaborative AI Classroom: Teaching Students to Work With, Not Against, AI Tools – Faculty Focus
In today’s rapidly evolving educational landscape, artificial intelligence (AI) has transformed from a distant technological concept to an everyday tool accessible to our students. In recent years, AI has proven to be a disruptor in the delivery of education, raising concerns among educators. Rather than viewing AI as a threat to academic integrity or a shortcut that undermines learning, educators have an opportunity to reframe AI as a collaborative partner in the educational process (Bowen and Watson, 2024). This article examines practical approaches for teaching students to collaborate with AI tools in a manner that enhances, rather than replaces, critical thinking and deep learning.

The Collaborative Mindset Shift

According to the Global AI Student Survey by the Digital Education Council, 86% of students already use AI in their studies (“Digital Education Council Global AI Student Survey 2024,” n.d.). However, with widespread apprehension about the effects of AI in education, a mindset shift may be beneficial in alleviating fears of the unknown. The first step in creating a collaborative AI classroom is to shift both the instructor’s and student’s mindsets. As Bowen and Watson (2024) note in their book, Teaching with AI, ‘AI is going to change our relationship with thinking. It is already challenging ideas about creativity and originality, and it will forever alter education, work, and even how we think about thinking.’ They further posit that students and educators can work with generative AI systems to improve learning processes, making them faster and more efficient. They propose that assessments should shift to focus on the process of creation rather than just the final product. For instance, students might be required to submit transcripts of their AI interactions as part of their assignments, making the learning journey more transparent and accessible.

This approach aligns with Atchley et al. (2024), who conclude that while the new AI technologies in education will initially make educators’ jobs challenging, AI should be viewed as a collaborative tool for teachers and students alike. Their review examines the adoption of AI in education from the perspective that the primary outcome of higher education is employment, that education is centered around the cognitive domains associated with learning, and that there is a risk associated with allowing technology to perform cognitive tasks. Keeping those factors in mind, they posit that ‘to maximize the benefits of collaborative learning (between fully human teams and between teams that include AI), pedagogical strategies must intentionally incorporate primary and secondary factors that encourage shared responsibility, interaction, and metacognitive skill development, enhancing student engagement and learning outcomes.’ Further, they argue that ‘as students enter a workplace, their ability to work on human/computer “teams” is a critical cognitive skillset.’

Practical Classroom Strategies

1. AI-Assisted Drafting and Revision

Instead of banning AI writing tools, consider assignments where students deliberately use AI to generate initial drafts, then critically analyze and substantially revise those drafts. This process teaches students to:
- Craft effective prompts (a transferable skill)
- Identify strengths and weaknesses in AI-generated content
- Apply their own expertise and voice to improve upon machine outputs
Students can submit both the original AI output and their revised version, along with a reflection on their editing process. In addition, asking students to support their edits with evidence-based references teaches them to critically analyze AI outputs. This transparency transforms potential academic dishonesty into a learning opportunity about the value of human expertise and judgment.

2. Comparative Analysis Activities

Design activities where students compare multiple AI-generated responses to the same prompt and then evaluate which is most effective and why. This approach:
- Develops critical evaluation skills
- Demonstrates AI limitations and inconsistencies
- Reinforces that AI requires human oversight
For example, students might prompt three different AI tools with the same question and then analyze differences in factual accuracy, reasoning approaches, and potential biases.

3. AI as Research Assistant

Teach students to use AI as a research brainstorming tool while maintaining scholarly rigor. Students can:
- Use AI to generate potential research questions
- Identify gaps in AI knowledge that require traditional research
- Cross-check AI-suggested sources with academic databases
This approach, similar to what Cianciolo and Regehr (2019) describe as “layered analysis,” helps students understand the complementary relationship between AI-assisted and traditional research methods.

Evidence of Impact

Early evidence suggests that collaborative AI approaches improve learning outcomes. In a study of healthcare education environments, students who learned to critically engage with AI tools, such as simulated gaming (SG), expressed more satisfaction with the training session than the traditional teaching group (TT). Additionally, students in the SG group found the activity more engaging and reported increased motivation (Blanie et al., 2020).

Similarly, in a recent meta-analysis examining the relationship between AI and students’ academic achievement, Dong et al. (2025) concluded that students who utilized AI-enhanced learning approaches demonstrated significantly higher academic performance, outpacing their counterparts in conventional educational settings. Moreover, the authors concluded that AI technologies may be particularly valuable for secondary and higher education students, who typically possess more developed critical thinking skills and can engage meaningfully with sophisticated AI systems that may apply across disciplines.

Implementation Considerations

When implementing collaborative AI approaches, consider these guidelines:
1. Be explicit about when and how AI use is appropriate for specific assignments
1. Create rubrics that evaluate students’ critical engagement with AI, not just the final products
1. Model appropriate AI collaboration in your teaching practices
1. Provide scaffolded opportunities for students to practice AI collaboration with feedback
Conclusion

By teaching students to work with, rather than against, AI tools, we prepare them for a future where human-AI collaboration will be commonplace across various professions. The collaborative AI classroom doesn’t diminish the value of human thinking, instead, it elevates it by helping students understand what uniquely human perspectives they bring to problems that AI alone cannot solve.

Rather than focusing solely on outcomes (what students produce), this approach emphasizes the learning process itself, aligning with calls from Allen et al. (2021) for more comprehensive evaluation approaches in education that go beyond simple outcome measures. By teaching students to be thoughtful collaborators with AI, we help them develop the critical thinking skills and technological literacy they’ll need throughout their careers.

Ewa Posorski is an educational leader and advocate for integrating artificial intelligence into modern pedagogy. With a focus on fostering collaboration between students and AI tools, Ewa champions a shift in mindset that embraces AI as a partner in learning rather than a threat to academic integrity. Her work emphasizes practical strategies for AI-assisted drafting, comparative analysis, and research support, all aimed at enhancing critical thinking and metacognitive skills. Drawing on current research and classroom evidence, she promotes transparent, process-oriented learning that prepares students for a future of human-AI collaboration across disciplines.

References

Allen, L. M., Hay, M., & Palermo, C. (2021). Evaluation in health professions education—Is measuring outcomes enough? Medical Education, 56(1), 127-136. https://doi.org/10.1111/medu.14654

Atchley, P., Pannell, H., Wofford, K., Hacker, D. J., & Risko, E. F. (2024). Human and AI collaboration in the higher education environment: opportunities and concerns. Cognitive Research: Principles and Implications, 9, 20. https://doi.org/10.1186/s41235-024-00547-9

Blanié, A., Amorim, M. A., & Benhamou, D. (2020). Comparative value of simulation by gaming and a traditional teaching method to improve clinical reasoning skills necessary to detect patient deterioration: A randomized study in nursing students. BMC Medical Education, 20, 53. https://doi.org/10.1186/s12909-020-1939-6

Bowen, J.A. & Watson, C.E. (2024). Teaching with AI: A practical guide to a new era of human learning. Johns Hopkins University Press.

Cianciolo, A. T., & Regehr, G. (2019). Learning Theory and Educational Intervention: Producing Meaningful Evidence of Impact Through Layered Analysis. Academic Medicine: Journal of the Association of American Medical Colleges, 94(6), 789–794. https://doi.org/10.1097/ACM.0000000000002591

Bowen, José Antonio, and C. Edward Watson. 2024. Teaching with AI: A Practical Guide to a New Era of Human Learning. Baltimore, Maryland: Johns Hopkins University Press.

Digital Education Council. “Digital Education Council Global AI Student Survey 2024.” n.d. Accessed March 24, 2025. https://www.digitaleducationcouncil.com/post/digital-education-council-global-ai-student-survey-2024.

Liu, D., Tang, X., & Wang, X. (2025). Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis. Computers and Education: Artificial Intelligence. https://www.sciencedirect.com/science/article/pii/S2666920X25000402
Source link
August 1, 2025
The Collaborative AI Classroom: Teaching Students to Work With, Not Against, AI Tools – Faculty Focus
In today’s rapidly evolving educational landscape, artificial intelligence (AI) has transformed from a distant technological concept to an everyday tool accessible to our students. In recent years, AI has proven to be a disruptor in the delivery of education, raising concerns among educators. Rather than viewing AI as a threat to academic integrity or a shortcut that undermines learning, educators have an opportunity to reframe AI as a collaborative partner in the educational process (Bowen and Watson, 2024). This article examines practical approaches for teaching students to collaborate with AI tools in a manner that enhances, rather than replaces, critical thinking and deep learning.

The Collaborative Mindset Shift

According to the Global AI Student Survey by the Digital Education Council, 86% of students already use AI in their studies (“Digital Education Council Global AI Student Survey 2024,” n.d.). However, with widespread apprehension about the effects of AI in education, a mindset shift may be beneficial in alleviating fears of the unknown. The first step in creating a collaborative AI classroom is to shift both the instructor’s and student’s mindsets. As Bowen and Watson (2024) note in their book, Teaching with AI, ‘AI is going to change our relationship with thinking. It is already challenging ideas about creativity and originality, and it will forever alter education, work, and even how we think about thinking.’ They further posit that students and educators can work with generative AI systems to improve learning processes, making them faster and more efficient. They propose that assessments should shift to focus on the process of creation rather than just the final product. For instance, students might be required to submit transcripts of their AI interactions as part of their assignments, making the learning journey more transparent and accessible.

This approach aligns with Atchley et al. (2024), who conclude that while the new AI technologies in education will initially make educators’ jobs challenging, AI should be viewed as a collaborative tool for teachers and students alike. Their review examines the adoption of AI in education from the perspective that the primary outcome of higher education is employment, that education is centered around the cognitive domains associated with learning, and that there is a risk associated with allowing technology to perform cognitive tasks. Keeping those factors in mind, they posit that ‘to maximize the benefits of collaborative learning (between fully human teams and between teams that include AI), pedagogical strategies must intentionally incorporate primary and secondary factors that encourage shared responsibility, interaction, and metacognitive skill development, enhancing student engagement and learning outcomes.’ Further, they argue that ‘as students enter a workplace, their ability to work on human/computer “teams” is a critical cognitive skillset.’

Practical Classroom Strategies

1. AI-Assisted Drafting and Revision

Instead of banning AI writing tools, consider assignments where students deliberately use AI to generate initial drafts, then critically analyze and substantially revise those drafts. This process teaches students to:
- Craft effective prompts (a transferable skill)
- Identify strengths and weaknesses in AI-generated content
- Apply their own expertise and voice to improve upon machine outputs
Students can submit both the original AI output and their revised version, along with a reflection on their editing process. In addition, asking students to support their edits with evidence-based references teaches them to critically analyze AI outputs. This transparency transforms potential academic dishonesty into a learning opportunity about the value of human expertise and judgment.

2. Comparative Analysis Activities

Design activities where students compare multiple AI-generated responses to the same prompt and then evaluate which is most effective and why. This approach:
- Develops critical evaluation skills
- Demonstrates AI limitations and inconsistencies
- Reinforces that AI requires human oversight
For example, students might prompt three different AI tools with the same question and then analyze differences in factual accuracy, reasoning approaches, and potential biases.

3. AI as Research Assistant

Teach students to use AI as a research brainstorming tool while maintaining scholarly rigor. Students can:
- Use AI to generate potential research questions
- Identify gaps in AI knowledge that require traditional research
- Cross-check AI-suggested sources with academic databases
This approach, similar to what Cianciolo and Regehr (2019) describe as “layered analysis,” helps students understand the complementary relationship between AI-assisted and traditional research methods.

Evidence of Impact

Early evidence suggests that collaborative AI approaches improve learning outcomes. In a study of healthcare education environments, students who learned to critically engage with AI tools, such as simulated gaming (SG), expressed more satisfaction with the training session than the traditional teaching group (TT). Additionally, students in the SG group found the activity more engaging and reported increased motivation (Blanie et al., 2020).

Similarly, in a recent meta-analysis examining the relationship between AI and students’ academic achievement, Dong et al. (2025) concluded that students who utilized AI-enhanced learning approaches demonstrated significantly higher academic performance, outpacing their counterparts in conventional educational settings. Moreover, the authors concluded that AI technologies may be particularly valuable for secondary and higher education students, who typically possess more developed critical thinking skills and can engage meaningfully with sophisticated AI systems that may apply across disciplines.

Implementation Considerations

When implementing collaborative AI approaches, consider these guidelines:
1. Be explicit about when and how AI use is appropriate for specific assignments
1. Create rubrics that evaluate students’ critical engagement with AI, not just the final products
1. Model appropriate AI collaboration in your teaching practices
1. Provide scaffolded opportunities for students to practice AI collaboration with feedback
Conclusion

By teaching students to work with, rather than against, AI tools, we prepare them for a future where human-AI collaboration will be commonplace across various professions. The collaborative AI classroom doesn’t diminish the value of human thinking, instead, it elevates it by helping students understand what uniquely human perspectives they bring to problems that AI alone cannot solve.

Rather than focusing solely on outcomes (what students produce), this approach emphasizes the learning process itself, aligning with calls from Allen et al. (2021) for more comprehensive evaluation approaches in education that go beyond simple outcome measures. By teaching students to be thoughtful collaborators with AI, we help them develop the critical thinking skills and technological literacy they’ll need throughout their careers.

Ewa Posorski is an educational leader and advocate for integrating artificial intelligence into modern pedagogy. With a focus on fostering collaboration between students and AI tools, Ewa champions a shift in mindset that embraces AI as a partner in learning rather than a threat to academic integrity. Her work emphasizes practical strategies for AI-assisted drafting, comparative analysis, and research support, all aimed at enhancing critical thinking and metacognitive skills. Drawing on current research and classroom evidence, she promotes transparent, process-oriented learning that prepares students for a future of human-AI collaboration across disciplines.

References

Allen, L. M., Hay, M., & Palermo, C. (2021). Evaluation in health professions education—Is measuring outcomes enough? Medical Education, 56(1), 127-136. https://doi.org/10.1111/medu.14654

Atchley, P., Pannell, H., Wofford, K., Hacker, D. J., & Risko, E. F. (2024). Human and AI collaboration in the higher education environment: opportunities and concerns. Cognitive Research: Principles and Implications, 9, 20. https://doi.org/10.1186/s41235-024-00547-9

Blanié, A., Amorim, M. A., & Benhamou, D. (2020). Comparative value of simulation by gaming and a traditional teaching method to improve clinical reasoning skills necessary to detect patient deterioration: A randomized study in nursing students. BMC Medical Education, 20, 53. https://doi.org/10.1186/s12909-020-1939-6

Bowen, J.A. & Watson, C.E. (2024). Teaching with AI: A practical guide to a new era of human learning. Johns Hopkins University Press.

Cianciolo, A. T., & Regehr, G. (2019). Learning Theory and Educational Intervention: Producing Meaningful Evidence of Impact Through Layered Analysis. Academic Medicine: Journal of the Association of American Medical Colleges, 94(6), 789–794. https://doi.org/10.1097/ACM.0000000000002591

Bowen, José Antonio, and C. Edward Watson. 2024. Teaching with AI: A Practical Guide to a New Era of Human Learning. Baltimore, Maryland: Johns Hopkins University Press.

Digital Education Council. “Digital Education Council Global AI Student Survey 2024.” n.d. Accessed March 24, 2025. https://www.digitaleducationcouncil.com/post/digital-education-council-global-ai-student-survey-2024.

Liu, D., Tang, X., & Wang, X. (2025). Examining the effect of artificial intelligence in relation to students’ academic achievement: A meta-analysis. Computers and Education: Artificial Intelligence. https://www.sciencedirect.com/science/article/pii/S2666920X25000402
Source link
August 1, 2025
Practical Strategies for Interdisciplinary Teaching in Today’s University – Faculty Focus

Working in the College of Interdisciplinary Studies has shown me firsthand that our students face a world full of messy, tangled problems. Climate shifts, health crises, social divides, and tech changes do not fit neatly into one subject area. They need tools from many fields to tackle these issues. This teaching helps students blend ideas, think deeply across fields, and work well with people from varied backgrounds. Drawing from my experience teaching across subjects at Zayed University in Dubai, UAE, I want to share real ways teachers can build and run cross-subject courses that truly help students handle today’s complex world.

True interdisciplinary teaching goes beyond just putting different topics side by side. At our college, we have learned that it means weaving ideas, theories, and methods from many fields to examine a shared theme or question. This takes careful planning, a willingness to step outside your comfort zone, and a focus on working together. The aim is not to water down each subject but to strengthen them by showing how different ways of thinking can shed more light on tricky issues. I will share clear steps for building cross-subject courses, sparking talks across fields, checking how well students are blending ideas, and getting past common hurdles I have faced in my own teaching.

Building Interdisciplinary Courses: Choosing Scope and Mixing Knowledge

Creating a solid interdisciplinary course starts with a clear scope and thoughtful mixing of knowledge. In our college, we aim for courses where students see connections and blend insights rather than just stacking content from different fields. Often, this means finding a central theme, problem, or question that ties everything together. For example, a course on city growth might pull from earth science, social studies, money matters, and city planning. Choose fields that each add something vital to understanding your main topic. O’Sullivan (2025) suggests a “U-shaped learning” model for teaching across fields, focusing on two main skills: blending knowledge and putting it to work. This model shows learning as a path from understanding single subjects to gaining a mixed view that works in the real world.

Once you have set your central theme and chosen your fields, think about how to structure the course for sound mixing. In our college, we have succeeded in organizing units around sub-themes where different lenses are applied or using project-based learning where students work on complex problems that need input from many fields. Yang et al. (2024) studied adding interdisciplinary learning in nursing classes using games. They found this significantly boosted nursing students’ knowledge, skills, and attitudes, especially in talking with others, solving problems, and using what they learned. At our college, we map out how ideas from different fields will be introduced, how they relate, and how we will help students make these connections. This means readings from various fields, expert guest talks, or tasks that ask students to blend information from many sources.

Sparking Talks and Teamwork Across Fields

A sign of good interdisciplinary teaching is meaningful talk and teamwork among students from different backgrounds. In my classes, creating a space where students feel safe sharing ideas from their fields and respectfully engaging with different views is crucial. Teachers must be skilled guides, steering talks, handling conflicts, and helping students find common ground. Ways to boost cross-field talk include structured debates on complex issues, small group work with students from different fields, or case studies that need multiple viewpoints. The U-shaped learning model from O’Sullivan (2025) backs this kind of team learning since building people skills helps blend knowledge and put it to use.

Team projects have proven powerful for interdisciplinary learning. When students from different fields work on a shared problem, they must talk across subject lines, work through various approaches, and blend their varied skills and knowledge. Yang et al. (2024) found that mixing social service with cross-field learning in nursing exposed students to diverse challenges, which boosted their communication and problem-solving skills. In our interdisciplinary courses, we structure projects, so students take roles based on their field expertise while ensuring everyone helps blend the knowledge. Clear guidelines for group work, ways to handle conflicts, and checking individual work and group results are essential for successful interdisciplinary projects.

Checking How Well Students Blend Ideas

Checking student learning in an interdisciplinary course brings special challenges, as the goal is to test knowledge of single subjects and the ability to blend and use information from many fields. In our college, old testing methods, like exams on facts from one field, do not work well. Instead, we use assessments that show students’ ability to think critically, analyze deeply, and use mixed knowledge on complex problems. Examples include projects, research papers that blend sources from many fields, talks on solutions to real-world problems that use diverse views, or creating things (like policy briefs, design models, and media projects) that show mixed understanding. Yang et al. (2024) used number measures (tests before and after) and quality analysis of students’ thought journals to check course effectiveness and learning outcomes across fields.

Reflection also helps check interdisciplinary learning in our college. We ask students to think about their learning process, their challenges in mixing different views, and how their understanding has changed. This shows how they are developing cross-field skills. O’Sullivan (2025) notes that learning across fields involves building inner skills. Reflection tasks can help students develop these skills by pushing them to think deeply about their learning and the value of different field approaches. When creating assessments, our faculty ensure the scoring rubrics clearly state expectations and give students chances to show their skills meaningfully.

Wrapping Up

Crossing the space between fields through good interdisciplinary teaching is essential for preparing students to handle today’s complex world. By carefully designing courses that focus on mixing knowledge, sparking rich talk and teamwork, and using fitting assessment methods, teachers can create life-changing learning experiences. The insights from research on interdisciplinary learning models (O’Sullivan, 2025) and the proven benefits of mixed approaches in fields like nursing (Yang et al., 2024) offer valuable guidance. While interdisciplinary teaching brings unique challenges, the rewards of boosting students’ critical thinking, problem-solving, and teamwork skills are tremendous. In our College of Interdisciplinary Studies, we have seen how these practical methods create a complete learning setting, giving power to the next wave of thinkers and leaders who will tackle our world’s most pressing challenges.

Dr. Zeina Hojeij is a Professor at the College of Interdisciplinary Studies at Zayed University, where she has served since 2013, specializing in educational leadership and administration. With a doctorate in Educational Leadership from Saint Louis University, USA, and extensive experience in academic administration, she has held several key leadership positions, including Associate Dean for Faculty Affairs and Academic Director for the General Education Program. A certified UAE Commission for Academic Accreditation (CAA) Reviewer and Fellow of the Higher Education Academy, Prof. Hojeij combines her expertise in curriculum development with a strong research portfolio, having secured over 2 million AED in research grants over the past 10 years. Her research focuses on educational technology, leadership development, and teaching innovation. She has taught and coordinated undergraduate and graduate courses in Education and interdisciplinary education while maintaining a ten-year commitment to teacher mentoring with the Al Jalila Foundation. She holds multiple professional certifications, including Blackboard Certified Associate, Accredited Facilitator, Certified Online Instructor, and CELTA & CELTYL certifications. Her dedication to educational innovation is further evidenced by her recent Harvard Business School Online Design Thinking and Innovation certification. Fluent in English, Arabic, and French, Prof. Hojeij brings a global perspective to her work in advancing educational excellence, regularly presenting at international conferences and publishing in peer-reviewed journals.

References

O’Sullivan, G. (2025). U-shaped learning: A new model for transdisciplinary education. Humanities and Social Sciences Communications, 12(182). https://doi.org/10.1057/s41599-025-04478-8

Yang, B.-H., Lo, K.-W., Li, Y.-S., & Chao, K.-Y. (2024). Effects of integration interdisciplinary learning on student learning outcomes and healthcare-giving competence: A mixed methods study. BMC Nursing, 23(583). https://doi.org/10.1186/s12912-024-02260-w

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July 18, 2025
Practical Strategies for Interdisciplinary Teaching in Today’s University – Faculty Focus

Working in the College of Interdisciplinary Studies has shown me firsthand that our students face a world full of messy, tangled problems. Climate shifts, health crises, social divides, and tech changes do not fit neatly into one subject area. They need tools from many fields to tackle these issues. This teaching helps students blend ideas, think deeply across fields, and work well with people from varied backgrounds. Drawing from my experience teaching across subjects at Zayed University in Dubai, UAE, I want to share real ways teachers can build and run cross-subject courses that truly help students handle today’s complex world.

True interdisciplinary teaching goes beyond just putting different topics side by side. At our college, we have learned that it means weaving ideas, theories, and methods from many fields to examine a shared theme or question. This takes careful planning, a willingness to step outside your comfort zone, and a focus on working together. The aim is not to water down each subject but to strengthen them by showing how different ways of thinking can shed more light on tricky issues. I will share clear steps for building cross-subject courses, sparking talks across fields, checking how well students are blending ideas, and getting past common hurdles I have faced in my own teaching.

Building Interdisciplinary Courses: Choosing Scope and Mixing Knowledge

Creating a solid interdisciplinary course starts with a clear scope and thoughtful mixing of knowledge. In our college, we aim for courses where students see connections and blend insights rather than just stacking content from different fields. Often, this means finding a central theme, problem, or question that ties everything together. For example, a course on city growth might pull from earth science, social studies, money matters, and city planning. Choose fields that each add something vital to understanding your main topic. O’Sullivan (2025) suggests a “U-shaped learning” model for teaching across fields, focusing on two main skills: blending knowledge and putting it to work. This model shows learning as a path from understanding single subjects to gaining a mixed view that works in the real world.

Once you have set your central theme and chosen your fields, think about how to structure the course for sound mixing. In our college, we have succeeded in organizing units around sub-themes where different lenses are applied or using project-based learning where students work on complex problems that need input from many fields. Yang et al. (2024) studied adding interdisciplinary learning in nursing classes using games. They found this significantly boosted nursing students’ knowledge, skills, and attitudes, especially in talking with others, solving problems, and using what they learned. At our college, we map out how ideas from different fields will be introduced, how they relate, and how we will help students make these connections. This means readings from various fields, expert guest talks, or tasks that ask students to blend information from many sources.

Sparking Talks and Teamwork Across Fields

A sign of good interdisciplinary teaching is meaningful talk and teamwork among students from different backgrounds. In my classes, creating a space where students feel safe sharing ideas from their fields and respectfully engaging with different views is crucial. Teachers must be skilled guides, steering talks, handling conflicts, and helping students find common ground. Ways to boost cross-field talk include structured debates on complex issues, small group work with students from different fields, or case studies that need multiple viewpoints. The U-shaped learning model from O’Sullivan (2025) backs this kind of team learning since building people skills helps blend knowledge and put it to use.

Team projects have proven powerful for interdisciplinary learning. When students from different fields work on a shared problem, they must talk across subject lines, work through various approaches, and blend their varied skills and knowledge. Yang et al. (2024) found that mixing social service with cross-field learning in nursing exposed students to diverse challenges, which boosted their communication and problem-solving skills. In our interdisciplinary courses, we structure projects, so students take roles based on their field expertise while ensuring everyone helps blend the knowledge. Clear guidelines for group work, ways to handle conflicts, and checking individual work and group results are essential for successful interdisciplinary projects.

Checking How Well Students Blend Ideas

Checking student learning in an interdisciplinary course brings special challenges, as the goal is to test knowledge of single subjects and the ability to blend and use information from many fields. In our college, old testing methods, like exams on facts from one field, do not work well. Instead, we use assessments that show students’ ability to think critically, analyze deeply, and use mixed knowledge on complex problems. Examples include projects, research papers that blend sources from many fields, talks on solutions to real-world problems that use diverse views, or creating things (like policy briefs, design models, and media projects) that show mixed understanding. Yang et al. (2024) used number measures (tests before and after) and quality analysis of students’ thought journals to check course effectiveness and learning outcomes across fields.

Reflection also helps check interdisciplinary learning in our college. We ask students to think about their learning process, their challenges in mixing different views, and how their understanding has changed. This shows how they are developing cross-field skills. O’Sullivan (2025) notes that learning across fields involves building inner skills. Reflection tasks can help students develop these skills by pushing them to think deeply about their learning and the value of different field approaches. When creating assessments, our faculty ensure the scoring rubrics clearly state expectations and give students chances to show their skills meaningfully.

Wrapping Up

Crossing the space between fields through good interdisciplinary teaching is essential for preparing students to handle today’s complex world. By carefully designing courses that focus on mixing knowledge, sparking rich talk and teamwork, and using fitting assessment methods, teachers can create life-changing learning experiences. The insights from research on interdisciplinary learning models (O’Sullivan, 2025) and the proven benefits of mixed approaches in fields like nursing (Yang et al., 2024) offer valuable guidance. While interdisciplinary teaching brings unique challenges, the rewards of boosting students’ critical thinking, problem-solving, and teamwork skills are tremendous. In our College of Interdisciplinary Studies, we have seen how these practical methods create a complete learning setting, giving power to the next wave of thinkers and leaders who will tackle our world’s most pressing challenges.

Dr. Zeina Hojeij is a Professor at the College of Interdisciplinary Studies at Zayed University, where she has served since 2013, specializing in educational leadership and administration. With a doctorate in Educational Leadership from Saint Louis University, USA, and extensive experience in academic administration, she has held several key leadership positions, including Associate Dean for Faculty Affairs and Academic Director for the General Education Program. A certified UAE Commission for Academic Accreditation (CAA) Reviewer and Fellow of the Higher Education Academy, Prof. Hojeij combines her expertise in curriculum development with a strong research portfolio, having secured over 2 million AED in research grants over the past 10 years. Her research focuses on educational technology, leadership development, and teaching innovation. She has taught and coordinated undergraduate and graduate courses in Education and interdisciplinary education while maintaining a ten-year commitment to teacher mentoring with the Al Jalila Foundation. She holds multiple professional certifications, including Blackboard Certified Associate, Accredited Facilitator, Certified Online Instructor, and CELTA & CELTYL certifications. Her dedication to educational innovation is further evidenced by her recent Harvard Business School Online Design Thinking and Innovation certification. Fluent in English, Arabic, and French, Prof. Hojeij brings a global perspective to her work in advancing educational excellence, regularly presenting at international conferences and publishing in peer-reviewed journals.

References

O’Sullivan, G. (2025). U-shaped learning: A new model for transdisciplinary education. Humanities and Social Sciences Communications, 12(182). https://doi.org/10.1057/s41599-025-04478-8

Yang, B.-H., Lo, K.-W., Li, Y.-S., & Chao, K.-Y. (2024). Effects of integration interdisciplinary learning on student learning outcomes and healthcare-giving competence: A mixed methods study. BMC Nursing, 23(583). https://doi.org/10.1186/s12912-024-02260-w

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July 18, 2025
Bridging the Gap: Active Learning Strategies for Traditional and Online Classrooms – Faculty Focus

There I was, standing in front of my face-to-face Introduction to Psychology class on a sunny Monday afternoon in spring 2024. I was watching as a few of my students took notes while the remaining students sat passively, perhaps hoping my animated gestures and pacing would somehow osmotically transfer my explanation of classical conditioning into their brains. Meanwhile, in my online section of the same course, students worked through carefully crafted modules at their own pace, their participation in discussion boards ebbing and flowing unpredictably. That’s when it hit me—despite years of teaching experience, I’m still searching for ways to spark the same level of engagement whether I’m interacting with students face-to-face or through carefully designed asynchronous activities. These parallel yet distinct teaching environments demand intentional strategies that can adapt while maintaining their power to actively engage students in the learning process.

Rethinking Active Learning for Asynchronous Spaces

Traditional active learning techniques that work beautifully in my face-to-face classes often fall flat in the asynchronous online environment. Take the classic “turn to your neighbor and discuss” prompt that energizes my traditional classes—there’s no direct equivalent when students are logging in at different times throughout the week. Yet simply abandoning these proven engagement strategies isn’t the answer. Instead, we need to reimagine active learning for both spaces, maintaining the core principles while adapting the execution. The key is finding techniques that preserve what makes active learning so powerful—student engagement, peer interaction, and immediate application of concepts—while acknowledging the unique constraints and opportunities of each learning environment.

One of the most powerful techniques in my traditional classroom is the think-pair-share discussion format. Students have those precious moments to gather their thoughts before turning to a classmate to discuss concepts like confirmation bias or the impact of classical conditioning on everyday behavior. The students are energized as pairs merge into small groups, building on each other’s insights before sharing with the whole class. But how do we capture that same collaborative energy in an asynchronous environment?

I’ve found success by structuring online discussions in three distinct phases that mirror the in-person experience. First, students post their initial response to a thought-provoking prompt (the “think” phase). Then, they must meaningfully respond to two classmates’ posts, building on their ideas rather than simply agreeing (the “pair” phase). Finally, students return to their original post and reflect on how their understanding has evolved after engaging with their peers’ perspectives (the “share” phase). The key is crafting prompts that demand critical thinking—instead of asking “What is classical conditioning?” I might ask “How would you use classical conditioning principles to help someone overcome their fear of public speaking?”

Timing matters, too. In my face-to-face class, I allow two to three minutes for individual reflection, five minutes for pair discussions, and 10 minutes for group sharing. Online, I’ve found success with a similar proportional structure: two days for initial posts, three days for peer responses, and two days for final reflections. This creates a rhythm that keeps the discussion moving while accommodating varied schedules.

Designing Collaborative Learning Experiences

Interactive content creation transforms how students engage with course material in both environments. In my traditional classes, I divide students into small groups to create concept maps exploring the relationships between different psychological disorders. Armed with markers and paper, they work collaboratively to connect concepts like anxiety, depression, and trauma responses, discovering links they might have missed studying alone. The energy is palpable as groups share their maps, debating connections and building on each other’s insights.

For my online students, I’ve adapted this activity using collaborative digital tools. Students work in small groups throughout the week to build their concept maps using shared online workspaces. Each student must add at least three concepts and make meaningful connections to their groupmates’ contributions. The asynchronous format actually offers an advantage here – students have time to think deeply about their contributions and can watch their group’s map evolve over several days. I provide specific deadlines for initial contributions and peer feedback to maintain momentum.

I have found that the key to success in either environment lies in providing clear examples of strong concept maps at the outset, establishing specific criteria for meaningful connections, and requiring students to explain their reasoning for each link they create. Deadlines for each phase keep the momentum going, while incorporating peer evaluation into the final grade ensures consistent participation. The resulting maps often reveal insights that surprise both me and my students, demonstrating how collaborative learning can deepen understanding regardless of the teaching modality.

Measuring Engagement and Refining Strategy

One-minute papers serve as powerful self-assessment tools in my traditional classes. For example, at the end of our discussion on memory formation, I ask students to quickly write down the most important concept they learned and one question they still have. This simple exercise reveals gaps in understanding and helps students consolidate their learning. In our next class, I address the most common questions, creating a feedback loop that keeps everyone engaged.

For my online students, I’ve transformed this into structured reflection journals. After completing each module, students must identify their key takeaway and pose one substantive question about the material. The asynchronous format allows for deeper reflection, and I’ve noticed online students often make fascinating connections to their personal experiences. Each week, I compile the most thought-provoking questions into a FAQ document, creating a collaborative resource that benefits the entire class.

Success in both formats require clear guidelines about what constitutes a meaningful reflection versus surface-level observations. Students stating that “the limbic system processes emotions” won’t suffice—they need to explain how this knowledge changes their understanding of human behavior. This approach not only reinforces learning but also develops critical thinking skills that serve students well beyond our course.

Measuring engagement across different learning environments requires that I use a systematic approach. In my traditional classroom, I track participation through observation and collect quick feedback via index cards. For my online students, I monitor not just the frequency but the quality of their discussion posts and collaborative work. The key metrics that I use remain consistent across both spaces: depth of analysis, peer interaction quality, and concept application.

I use a simple framework that examines three elements: initial engagement (participation in discussions or activities), sustained interaction (meaningful responses to peers), and learning application (connecting concepts to real-world scenarios). For each component, I look for evidence of critical thinking rather than mere completion. This approach helps identify which strategies are working and which need adjustment.

Beyond quantitative measures, I pay attention to qualitative indicators like the sophistication of student questions and the complexity of peer-to-peer discussions. These insights guide my refinement of teaching strategies in both environments, ensuring that active learning remains effective regardless of delivery method.

As the spring semester progressed, I saw the impact of the adapted strategies in both my traditional and online psychology classes. Those initially passive students in my traditional class began to engage in our active learning exercises, while my online students built an active learning community through their thoughtful asynchronous interactions. In my experience, the key isn’t choosing between traditional and online teaching methods—it’s understanding how to preserve active learning while adapting strategies to fit each unique environment. By reimagining rather than simply transplanting these strategies, we can create engaging learning experiences that work effectively across both spaces.

Dr. Dunja “Dee” Trunk, a professor of psychology at Bloomfield College of Montclair State University, has a passion for teaching and a genuine belief in the transformative power of education.

Source link

May 5, 2025
Bridging the Gap: Active Learning Strategies for Traditional and Online Classrooms – Faculty Focus

There I was, standing in front of my face-to-face Introduction to Psychology class on a sunny Monday afternoon in spring 2024. I was watching as a few of my students took notes while the remaining students sat passively, perhaps hoping my animated gestures and pacing would somehow osmotically transfer my explanation of classical conditioning into their brains. Meanwhile, in my online section of the same course, students worked through carefully crafted modules at their own pace, their participation in discussion boards ebbing and flowing unpredictably. That’s when it hit me—despite years of teaching experience, I’m still searching for ways to spark the same level of engagement whether I’m interacting with students face-to-face or through carefully designed asynchronous activities. These parallel yet distinct teaching environments demand intentional strategies that can adapt while maintaining their power to actively engage students in the learning process.

Rethinking Active Learning for Asynchronous Spaces

Traditional active learning techniques that work beautifully in my face-to-face classes often fall flat in the asynchronous online environment. Take the classic “turn to your neighbor and discuss” prompt that energizes my traditional classes—there’s no direct equivalent when students are logging in at different times throughout the week. Yet simply abandoning these proven engagement strategies isn’t the answer. Instead, we need to reimagine active learning for both spaces, maintaining the core principles while adapting the execution. The key is finding techniques that preserve what makes active learning so powerful—student engagement, peer interaction, and immediate application of concepts—while acknowledging the unique constraints and opportunities of each learning environment.

One of the most powerful techniques in my traditional classroom is the think-pair-share discussion format. Students have those precious moments to gather their thoughts before turning to a classmate to discuss concepts like confirmation bias or the impact of classical conditioning on everyday behavior. The students are energized as pairs merge into small groups, building on each other’s insights before sharing with the whole class. But how do we capture that same collaborative energy in an asynchronous environment?

I’ve found success by structuring online discussions in three distinct phases that mirror the in-person experience. First, students post their initial response to a thought-provoking prompt (the “think” phase). Then, they must meaningfully respond to two classmates’ posts, building on their ideas rather than simply agreeing (the “pair” phase). Finally, students return to their original post and reflect on how their understanding has evolved after engaging with their peers’ perspectives (the “share” phase). The key is crafting prompts that demand critical thinking—instead of asking “What is classical conditioning?” I might ask “How would you use classical conditioning principles to help someone overcome their fear of public speaking?”

Timing matters, too. In my face-to-face class, I allow two to three minutes for individual reflection, five minutes for pair discussions, and 10 minutes for group sharing. Online, I’ve found success with a similar proportional structure: two days for initial posts, three days for peer responses, and two days for final reflections. This creates a rhythm that keeps the discussion moving while accommodating varied schedules.

Designing Collaborative Learning Experiences

Interactive content creation transforms how students engage with course material in both environments. In my traditional classes, I divide students into small groups to create concept maps exploring the relationships between different psychological disorders. Armed with markers and paper, they work collaboratively to connect concepts like anxiety, depression, and trauma responses, discovering links they might have missed studying alone. The energy is palpable as groups share their maps, debating connections and building on each other’s insights.

For my online students, I’ve adapted this activity using collaborative digital tools. Students work in small groups throughout the week to build their concept maps using shared online workspaces. Each student must add at least three concepts and make meaningful connections to their groupmates’ contributions. The asynchronous format actually offers an advantage here – students have time to think deeply about their contributions and can watch their group’s map evolve over several days. I provide specific deadlines for initial contributions and peer feedback to maintain momentum.

I have found that the key to success in either environment lies in providing clear examples of strong concept maps at the outset, establishing specific criteria for meaningful connections, and requiring students to explain their reasoning for each link they create. Deadlines for each phase keep the momentum going, while incorporating peer evaluation into the final grade ensures consistent participation. The resulting maps often reveal insights that surprise both me and my students, demonstrating how collaborative learning can deepen understanding regardless of the teaching modality.

Measuring Engagement and Refining Strategy

One-minute papers serve as powerful self-assessment tools in my traditional classes. For example, at the end of our discussion on memory formation, I ask students to quickly write down the most important concept they learned and one question they still have. This simple exercise reveals gaps in understanding and helps students consolidate their learning. In our next class, I address the most common questions, creating a feedback loop that keeps everyone engaged.

For my online students, I’ve transformed this into structured reflection journals. After completing each module, students must identify their key takeaway and pose one substantive question about the material. The asynchronous format allows for deeper reflection, and I’ve noticed online students often make fascinating connections to their personal experiences. Each week, I compile the most thought-provoking questions into a FAQ document, creating a collaborative resource that benefits the entire class.

Success in both formats require clear guidelines about what constitutes a meaningful reflection versus surface-level observations. Students stating that “the limbic system processes emotions” won’t suffice—they need to explain how this knowledge changes their understanding of human behavior. This approach not only reinforces learning but also develops critical thinking skills that serve students well beyond our course.

Measuring engagement across different learning environments requires that I use a systematic approach. In my traditional classroom, I track participation through observation and collect quick feedback via index cards. For my online students, I monitor not just the frequency but the quality of their discussion posts and collaborative work. The key metrics that I use remain consistent across both spaces: depth of analysis, peer interaction quality, and concept application.

I use a simple framework that examines three elements: initial engagement (participation in discussions or activities), sustained interaction (meaningful responses to peers), and learning application (connecting concepts to real-world scenarios). For each component, I look for evidence of critical thinking rather than mere completion. This approach helps identify which strategies are working and which need adjustment.

Beyond quantitative measures, I pay attention to qualitative indicators like the sophistication of student questions and the complexity of peer-to-peer discussions. These insights guide my refinement of teaching strategies in both environments, ensuring that active learning remains effective regardless of delivery method.

As the spring semester progressed, I saw the impact of the adapted strategies in both my traditional and online psychology classes. Those initially passive students in my traditional class began to engage in our active learning exercises, while my online students built an active learning community through their thoughtful asynchronous interactions. In my experience, the key isn’t choosing between traditional and online teaching methods—it’s understanding how to preserve active learning while adapting strategies to fit each unique environment. By reimagining rather than simply transplanting these strategies, we can create engaging learning experiences that work effectively across both spaces.

Dr. Dunja “Dee” Trunk, a professor of psychology at Bloomfield College of Montclair State University, has a passion for teaching and a genuine belief in the transformative power of education.

Source link

May 5, 2025