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AI In Academic Publishing: Disruption or Evolution? – Faculty Focus

Artificial Intelligence (AI) is driving one of the most significant transformations in academic publishing since the advent of peer review. There has been a steady increase in the use of AI in research manuscripts since 2022, when OpenAI launched ChatGPT. Recent data demonstrate that up to 22% of computer science papers indicate the usage of large language models (LLMs). Another study on LLM use in scientific publishing revealed that 16.9% of peer review texts contained AI content.

The integration of AI tools in every stage of publication has been met with appreciation and criticism in equal measure. Proponents advocate AI as a catalyst that boosts efficiency by automating mundane tasks such as grammar editing, reference formatting, and initial screening. However, critics warn against possible pitfalls in quality and ethical considerations. The question remains: is AI disrupting traditional publishing models, or is it fostering a natural evolution within the academic enterprise?

Rise of AI in Research and Publication

AI has become embedded throughout the research lifecycle, from idea generation to final manuscript submission. This pervasive adoption is reshaping researchers’ approach to their work; they use applications for grammar checks, plagiarism detection, format compliance, and even assessment of their research significance.

Recent studies show that LLMs have an unmatched ability to generate prose and summarize content, enabling researchers to write literature reviews and experimental descriptions more efficiently. In fact, many researchers utilize features of LLMs to assist them with brainstorming, rephrasing, and clarifying their arguments.

Besides writing assistance, AI-driven platforms can streamline other laborious tasks. For instance, searching massive databases to find relevant citations and assessing the context and reliability of references. Likewise, available text translation and summarization tools support 30+ languages— a feature that breaks down linguistic barriers and allows for international collaboration in research.

One perspective piece published in PLOS Biology notes: “A primary reason that science has not yet become fully multilingual is that translation can be slow and costly. Artificial intelligence (AI), however, may finally allow us to overcome this problem, as it can provide useful, often free or affordable, support in language editing and translation”.

The integration of AI tools in research and publication has fundamentally shifted research workflows. Automation technologies have quickened the pace of writing and made academic writing and publishing more accessible.

Ethical Implications and Risks

The increased efficiency and renewed research approach also come with significant ethical concerns. AI systems operate by learning patterns in existing data and can amplify hidden biases. If an AI tool is trained on past editorial outcomes, it may score submissions from well-known institutions or English-speaking authors more highly.

Stanford researchers found that even when non-native English researchers use LLMs to refine their submissions, peer reviewers still show bias against them. Another study revealed that AI text-detection tools often misidentify non-native English writing as machine-generated. In other words, if there are two authors with equal merits, they may face unequal scrutiny if one uses slightly different phrasing.

Beyond systemic biases, there is concern that AI integration into the peer review process can lead to over-reliance on its functionalities. An analysis of peer review highlighted that overdependence of editors and reviewers on AI-generated suggestions can result in deterioration in review quality, and not to mention, factual mistakes that slip through evaluation.

Even as AI is used for initial screening, the recommendations made by such tools about a manuscript’s quality or reviewer selection may be opaque or even include hallucinated reasoning. In the absence of transparency, it is difficult to identify and correct misjudgments. This accountability challenge can seriously undermine trust in the editorial process.

However, the most concerning risk is the potential of AI to create a feedback loop of maintaining the status quo. AIs are trained on existing published literature and are designed to evaluate new submissions based on the present data. Given this data, it is likely that the AI system may inadvertently suppress new and innovative ideas that do not coincide with established patterns.

The Irreplaceable Role of Human Editorial Judgment

Despite these technological advances, the fundamental responsibility for maintaining scientific integrity ultimately rests with human editors and reviewers. Academic publishers serve as gatekeepers of knowledge, shaping what research reaches the broader scientific community and, by extension, informing public understanding and policy decisions. This role carries immense responsibility. Editorial decisions can accelerate breakthrough discoveries or inadvertently stifle groundbreaking research that challenges conventional thinking.

Rather than delegating these critical judgements to algorithms, the academic publishing community must recognize this moment as a call to elevate editorial standards and practices. Editors must recommit to rigorous, nuanced evaluation that prioritizes scientific merit over efficiency metrics. The stakes are too high– the advancement of human knowledge and credibility of scientific enterprise itself– to entrust these decisions to systems that, however sophisticated, lack the contextual understanding, ethical reasoning, and innovative thinking that human expertise provides.

Dr. Su Yeong Kim is a Professor of Human Development and Family Sciences at the University of Texas at Austin. A leading figure in research on immigrant families and adolescent development, she earned the honor of being a Fellow on multiple national psychology associations and is the Editor of the Journal of Research on Adolescence. Dr. Kim has authored and published more than 160 works and is recognized with Division 45 of American Psychological Association’s Distinguished Career Contributions to Research Award. Her research, funded by the National Institutes of Health, National Science Foundation, and other bodies, covers bilingualism, language brokering, and cultural stressors in immigrant-origin youth. Dr. Kim is an enthusiastic mentor and community advocate, as well as a member of UT’s Provost’s Distinguished Leadership Service Academy.

References

Liang, Weixin, et al. “Quantifying Large Language Model Usage in Scientific Papers.” Nature Human Behaviour (2025). https://doi.org/10.1038/s41562-025-02273-8.

“How Much Research Is Being Written by Large Language Models?” Stanford Institute for Human-Centered Artificial Intelligence (HAI). https://hai.stanford.edu/news/how-much-research-being-written-large-language-models

Doskaliuk, B., et al. “Artificial Intelligence in Peer Review: Enhancing Efficiency …” J Korean Med Sci 40, no. 7 (2025). https://pubmed.ncbi.nlm.nih.gov/39995259/

Kim, H., J. C. Little, J. Li, B. Patel, and D. Kalderon. “Hedgehog-Stimulated Phosphorylation at Multiple Sites Activates Ci by Altering Ci–Ci Interfaces without Full Suppressor of Fused Dissociation.” PLOS Biology 23, no. 4 (2025): e3003105. https://doi.org/10.1371/journal.pbio.3003105

“How Language Bias Persists in Scientific Publishing Despite AI Tools.” Stanford Institute for Human-Centered Artificial Intelligence (HAI). https://hai.stanford.edu/news/how-language-bias-p e rsists-in-scientific-publishing-despite-ai-tools

“What Are AI Hallucinations?” Google Cloud. https://cloud.google.com/discover/what-are-ai-hallucinations

Source link

November 26, 2025

AI In Academic Publishing: Disruption or Evolution? – Faculty Focus

Artificial Intelligence (AI) is driving one of the most significant transformations in academic publishing since the advent of peer review. There has been a steady increase in the use of AI in research manuscripts since 2022, when OpenAI launched ChatGPT. Recent data demonstrate that up to 22% of computer science papers indicate the usage of large language models (LLMs). Another study on LLM use in scientific publishing revealed that 16.9% of peer review texts contained AI content.

The integration of AI tools in every stage of publication has been met with appreciation and criticism in equal measure. Proponents advocate AI as a catalyst that boosts efficiency by automating mundane tasks such as grammar editing, reference formatting, and initial screening. However, critics warn against possible pitfalls in quality and ethical considerations. The question remains: is AI disrupting traditional publishing models, or is it fostering a natural evolution within the academic enterprise?

Rise of AI in Research and Publication

AI has become embedded throughout the research lifecycle, from idea generation to final manuscript submission. This pervasive adoption is reshaping researchers’ approach to their work; they use applications for grammar checks, plagiarism detection, format compliance, and even assessment of their research significance.

Recent studies show that LLMs have an unmatched ability to generate prose and summarize content, enabling researchers to write literature reviews and experimental descriptions more efficiently. In fact, many researchers utilize features of LLMs to assist them with brainstorming, rephrasing, and clarifying their arguments.

Besides writing assistance, AI-driven platforms can streamline other laborious tasks. For instance, searching massive databases to find relevant citations and assessing the context and reliability of references. Likewise, available text translation and summarization tools support 30+ languages— a feature that breaks down linguistic barriers and allows for international collaboration in research.

One perspective piece published in PLOS Biology notes: “A primary reason that science has not yet become fully multilingual is that translation can be slow and costly. Artificial intelligence (AI), however, may finally allow us to overcome this problem, as it can provide useful, often free or affordable, support in language editing and translation”.

The integration of AI tools in research and publication has fundamentally shifted research workflows. Automation technologies have quickened the pace of writing and made academic writing and publishing more accessible.

Ethical Implications and Risks

The increased efficiency and renewed research approach also come with significant ethical concerns. AI systems operate by learning patterns in existing data and can amplify hidden biases. If an AI tool is trained on past editorial outcomes, it may score submissions from well-known institutions or English-speaking authors more highly.

Stanford researchers found that even when non-native English researchers use LLMs to refine their submissions, peer reviewers still show bias against them. Another study revealed that AI text-detection tools often misidentify non-native English writing as machine-generated. In other words, if there are two authors with equal merits, they may face unequal scrutiny if one uses slightly different phrasing.

Beyond systemic biases, there is concern that AI integration into the peer review process can lead to over-reliance on its functionalities. An analysis of peer review highlighted that overdependence of editors and reviewers on AI-generated suggestions can result in deterioration in review quality, and not to mention, factual mistakes that slip through evaluation.

Even as AI is used for initial screening, the recommendations made by such tools about a manuscript’s quality or reviewer selection may be opaque or even include hallucinated reasoning. In the absence of transparency, it is difficult to identify and correct misjudgments. This accountability challenge can seriously undermine trust in the editorial process.

However, the most concerning risk is the potential of AI to create a feedback loop of maintaining the status quo. AIs are trained on existing published literature and are designed to evaluate new submissions based on the present data. Given this data, it is likely that the AI system may inadvertently suppress new and innovative ideas that do not coincide with established patterns.

The Irreplaceable Role of Human Editorial Judgment

Despite these technological advances, the fundamental responsibility for maintaining scientific integrity ultimately rests with human editors and reviewers. Academic publishers serve as gatekeepers of knowledge, shaping what research reaches the broader scientific community and, by extension, informing public understanding and policy decisions. This role carries immense responsibility. Editorial decisions can accelerate breakthrough discoveries or inadvertently stifle groundbreaking research that challenges conventional thinking.

Rather than delegating these critical judgements to algorithms, the academic publishing community must recognize this moment as a call to elevate editorial standards and practices. Editors must recommit to rigorous, nuanced evaluation that prioritizes scientific merit over efficiency metrics. The stakes are too high– the advancement of human knowledge and credibility of scientific enterprise itself– to entrust these decisions to systems that, however sophisticated, lack the contextual understanding, ethical reasoning, and innovative thinking that human expertise provides.

Dr. Su Yeong Kim is a Professor of Human Development and Family Sciences at the University of Texas at Austin. A leading figure in research on immigrant families and adolescent development, she earned the honor of being a Fellow on multiple national psychology associations and is the Editor of the Journal of Research on Adolescence. Dr. Kim has authored and published more than 160 works and is recognized with Division 45 of American Psychological Association’s Distinguished Career Contributions to Research Award. Her research, funded by the National Institutes of Health, National Science Foundation, and other bodies, covers bilingualism, language brokering, and cultural stressors in immigrant-origin youth. Dr. Kim is an enthusiastic mentor and community advocate, as well as a member of UT’s Provost’s Distinguished Leadership Service Academy.

References

Liang, Weixin, et al. “Quantifying Large Language Model Usage in Scientific Papers.” Nature Human Behaviour (2025). https://doi.org/10.1038/s41562-025-02273-8.

“How Much Research Is Being Written by Large Language Models?” Stanford Institute for Human-Centered Artificial Intelligence (HAI). https://hai.stanford.edu/news/how-much-research-being-written-large-language-models

Doskaliuk, B., et al. “Artificial Intelligence in Peer Review: Enhancing Efficiency …” J Korean Med Sci 40, no. 7 (2025). https://pubmed.ncbi.nlm.nih.gov/39995259/

Kim, H., J. C. Little, J. Li, B. Patel, and D. Kalderon. “Hedgehog-Stimulated Phosphorylation at Multiple Sites Activates Ci by Altering Ci–Ci Interfaces without Full Suppressor of Fused Dissociation.” PLOS Biology 23, no. 4 (2025): e3003105. https://doi.org/10.1371/journal.pbio.3003105

“How Language Bias Persists in Scientific Publishing Despite AI Tools.” Stanford Institute for Human-Centered Artificial Intelligence (HAI). https://hai.stanford.edu/news/how-language-bias-p e rsists-in-scientific-publishing-despite-ai-tools

“What Are AI Hallucinations?” Google Cloud. https://cloud.google.com/discover/what-are-ai-hallucinations

Source link

November 26, 2025

Everything is Awesome: Legos® to Teach Teamwork and Communication – Faculty Focus

A group of 38 nurses, seven Lego building block kits, and 45 minutes was all our nursing professional development team needed to improve staff communication and patient safety. Game-based learning (GBL) via Lego® building is a well-received training modality with a review of literature showing the potential to increase teamwork, communication, and comprehension (Warburton et al., 2022).

Lego® Serious Play®, a specific form of GBL, is a “facilitated, communication and problem-solving teaching technique using Lego® building blocks to use the concept of ‘hand knowledge’ to teach cognitive concepts” (Lego®, 2025). GBL is a frequent training modality our nurse education department uses for the quarterly skills day. Our quarterly skills days are training days dedicated to vital training requirements. We have used escape rooms, team Jeopardy, and role-plays, but our staff asked for something different. Our team held a brainstorming session, during which we decided to utilize Legos® to teach triage and communication skills.

The Idea for Lego® GBL

The idea for Lego® GBL in our facility was based on a critical incident tabletop exercise attended by nursing residents. Our nurse residents needed to complete and experience a mass casualty incident triage, but we were unable to involve them in the actual training exercise. I considered recreating the critical incident using a Lego® hospital and emergency department model. We used Lego® minifigures as our key players and victims: we had an ambulance, a stretcher, and an overturned truck.

The use of Lego® GBL learning addresses key elements of communication required for highly functioning teams.

Staff Engagement. The training energized the staff, prompting them to run the scenario multiple times.

Team Effort. The physical nature of the building blocks fosters a strong working environment that revolves around a shared mental model.

Critical thinking. The team makes key decisions on triage using limited information, following the triage guidelines, and relying on clear communication.

Lego® GBL and Communication Training

Our team was seeking an innovative approach to teaching communication skills beyond a traditional code team exercise. I instantly thought back to how successful the Lego® critical incident tabletop exercise went and told the team we should consider using this for all our learners.

I then conducted research and found three articles outlining how to create an educational exercise and its proven efficacy (Bethel et al., 2021; Lambert et al., 2023; Warburton et al., 2022). We began our design by creating a timed building scenario that involved 13 bricks and eight distractor bricks, which are not required to complete the build. We then decided we wanted to have three distinct roles in our building team:

Staff Nurse or Builder. This person was the only person who could see the build and touch the Lego® building blocks. The builder was behind a blinder and could not see the written instructions from their team members. The builder can only create the build based on verbal instructions from the runner.

Relief Nurse or Runner: This person was responsible for verbal communication between the staff and charge nurses. They could not see the build instructions or the build itself, and they could not physically interact with the Lego® build.

Charge Nurse or Diagram Holder: This person was responsible for being the only person who could see the build instructions. They passed on the verbal instructions to the runner. The charge nurse was behind a blind and cannot leave their workstation.

Projected Outcomes of Training

In developing this opportunity, I initially thought of what our outcomes would be. First, I wanted the learners to be engaged and to have data to support the need for future training. Second, I wanted the teams to verbalize that they improved communication in their teams. Third, I aimed to teach the principles of High Reliability Organization (HRO) communication to enhance patient safety. Finally, I briefly touched on the importance of rapid process improvement and the use of standardization documents (Standard Work and Standard Operating Procedures) to make work more consistent and safe.

Build Time: Everything is Awesome!

Our team facilitated the training, consisting of seven skills days, with an average of 15-24 participants per group. We introduced the guidelines for the activity and divided the teams into three groups. After the initial build, we conducted debriefings and reviewed the builds. All the builds were within 50% accuracy of the template, and no team finished before the five-minute time limit.

Next, I provided a brief 15-minute learning on (1) communication theory, (2) running a rapid process improvement, and (3) teamwork building. The teams had five minutes to do a team huddle. The purpose of the team huddle is to communicate a shared mental model of a task to ensure all members of the team have understanding. They identified that they wanted to make changes: (1) removing the blinders, (2) providing all team members with the build instructions, and (3) allowing all team members to touch the Legos®. The team employed more effective communication techniques during the second build. All teams utilized the 3 Cs of high-quality communication (clear, concise, and complete). Most teams finished within two minutes, with all teams achieving 100% accuracy with the template model.

Next Steps in Facility Lego® GBL

I plan to present this project to our nursing evidence-based council for further review and consideration. In the meantime, five additional units have requested this training by word-of-mouth advertising. In response to these requests, I have revised the instructions so that I could train other facilitators to run a 45-minute session. Our HRO and quality staff have expressed interest in formalizing this as part of our Pathway to Excellence drive.

Conclusion

Educators can use block learning as a tactile approach for learners to witness the outcomes of their “soft skills” training, which focuses on communication and teamwork. Lego® GBL provides a fun, engaging, and novel way for healthcare workers to experience competency training. Lego® GBL and Lego® Serious Play® offer ways for teams to interact in a manner that reduces stress by removing the high stakes of traditional simulation-based education.

Michael Brakel, RN-BC, is a Registered Nurse (RN) serving with the Veterans Affairs-Northern California Health Care System (VA-NCHCS) as a Nurse Educator. He has worked with the VA-NCHCS in various capacities, including Utilization Management RN, Utilization Review RN, Community Care RN, Affiliate Professor, and Primary Care Mental Health Integration (PCMHI) RN Care Coordinator. Additionally, he has worked as a Nurse Consultant with the VA Office of Inspector General (OIG), serving as a hotline team member and team lead. Mr. Brakel holds advanced degrees in management and psychology. He graduated from Hawaii Pacific University with a degree in nursing. Mike is certified in Managed Care Nursing, Psychiatric-Mental Health Nursing, Nursing Professional Development, and Nursing Case Management. He holds certifications as a Certified Professional of Patient Safety and a Certified Professional in Healthcare Quality in addition to his nursing credentials. Resilience, compassion fatigue, nurse retention, and the application of measurement-based screening in mental health care are his main research topics. Before coming to the VA, Mr. Brakel retired after 25 years in the United States Air Force Nursing Corps, specializing in Behavioral Health. Mike served as a nurse, charge nurse, and education specialist serving on inpatient units at Travis Air Force Base, California, and the San Antonio Military Medical Center. His last roles in the Air Force were serving as the Air Force lead Mental Health Nursing Educator and as the Deputy to the Air Force Consultant to the Surgeon General for Mental Health Nursing.

Dr. Julia VanderMolen is a Professor for the Public Health program at Grand Valley State University and a Visiting Assistant Clinical Professor with the University of the Pacific, School of Health Sciences. Her research examines the benefits of assistive technology for individuals with disabilities in public health. She serves as a board member of the Disability Advocates of Kent County and is an active member of the Disability Section of the American Public Health Association (APHA). Her current research focuses on exploring the health and medical services available to individuals with intellectual and developmental disabilities.

References

Bethel, E. C., Marchetti, K. A., Hecklinski, T. M., Daignault-Newton, M. S., Kraft, K. H., Hamilton, B. D., Faerber, G. J., & Ambani, S. N. (2021). The LEGO™ exercise: An assessment of core competencies in urology residency interviews. Journal of Surgical Education, 78(6), 2063-2069. https://doi.org/10.1016/j.jsurg.2021.05.011

Lambert, N. J., Luo, X., & Ola, A. (2023). Knowing me, knowing you: Self-reflection and understanding diversity for effective teamwork Lego® building activity. Management Teaching Review, 10(1), 21-34. https://doi.org/10.1177/23792981231190589

Warburton, T., Brown, J., & Sandars, J. (2022). The use of Lego® Serious Play® within nurse education: A scoping review. Nurse Education Today, 188(1). https://doi.org/10.1016/j.nedt.2022.105528

Source link

November 24, 2025

Everything is Awesome: Legos® to Teach Teamwork and Communication – Faculty Focus

A group of 38 nurses, seven Lego building block kits, and 45 minutes was all our nursing professional development team needed to improve staff communication and patient safety. Game-based learning (GBL) via Lego® building is a well-received training modality with a review of literature showing the potential to increase teamwork, communication, and comprehension (Warburton et al., 2022).

Lego® Serious Play®, a specific form of GBL, is a “facilitated, communication and problem-solving teaching technique using Lego® building blocks to use the concept of ‘hand knowledge’ to teach cognitive concepts” (Lego®, 2025). GBL is a frequent training modality our nurse education department uses for the quarterly skills day. Our quarterly skills days are training days dedicated to vital training requirements. We have used escape rooms, team Jeopardy, and role-plays, but our staff asked for something different. Our team held a brainstorming session, during which we decided to utilize Legos® to teach triage and communication skills.

The Idea for Lego® GBL

The idea for Lego® GBL in our facility was based on a critical incident tabletop exercise attended by nursing residents. Our nurse residents needed to complete and experience a mass casualty incident triage, but we were unable to involve them in the actual training exercise. I considered recreating the critical incident using a Lego® hospital and emergency department model. We used Lego® minifigures as our key players and victims: we had an ambulance, a stretcher, and an overturned truck.

The use of Lego® GBL learning addresses key elements of communication required for highly functioning teams.

Staff Engagement. The training energized the staff, prompting them to run the scenario multiple times.

Team Effort. The physical nature of the building blocks fosters a strong working environment that revolves around a shared mental model.

Critical thinking. The team makes key decisions on triage using limited information, following the triage guidelines, and relying on clear communication.

Lego® GBL and Communication Training

Our team was seeking an innovative approach to teaching communication skills beyond a traditional code team exercise. I instantly thought back to how successful the Lego® critical incident tabletop exercise went and told the team we should consider using this for all our learners.

I then conducted research and found three articles outlining how to create an educational exercise and its proven efficacy (Bethel et al., 2021; Lambert et al., 2023; Warburton et al., 2022). We began our design by creating a timed building scenario that involved 13 bricks and eight distractor bricks, which are not required to complete the build. We then decided we wanted to have three distinct roles in our building team:

Staff Nurse or Builder. This person was the only person who could see the build and touch the Lego® building blocks. The builder was behind a blinder and could not see the written instructions from their team members. The builder can only create the build based on verbal instructions from the runner.

Relief Nurse or Runner: This person was responsible for verbal communication between the staff and charge nurses. They could not see the build instructions or the build itself, and they could not physically interact with the Lego® build.

Charge Nurse or Diagram Holder: This person was responsible for being the only person who could see the build instructions. They passed on the verbal instructions to the runner. The charge nurse was behind a blind and cannot leave their workstation.

Projected Outcomes of Training

In developing this opportunity, I initially thought of what our outcomes would be. First, I wanted the learners to be engaged and to have data to support the need for future training. Second, I wanted the teams to verbalize that they improved communication in their teams. Third, I aimed to teach the principles of High Reliability Organization (HRO) communication to enhance patient safety. Finally, I briefly touched on the importance of rapid process improvement and the use of standardization documents (Standard Work and Standard Operating Procedures) to make work more consistent and safe.

Build Time: Everything is Awesome!

Our team facilitated the training, consisting of seven skills days, with an average of 15-24 participants per group. We introduced the guidelines for the activity and divided the teams into three groups. After the initial build, we conducted debriefings and reviewed the builds. All the builds were within 50% accuracy of the template, and no team finished before the five-minute time limit.

Next, I provided a brief 15-minute learning on (1) communication theory, (2) running a rapid process improvement, and (3) teamwork building. The teams had five minutes to do a team huddle. The purpose of the team huddle is to communicate a shared mental model of a task to ensure all members of the team have understanding. They identified that they wanted to make changes: (1) removing the blinders, (2) providing all team members with the build instructions, and (3) allowing all team members to touch the Legos®. The team employed more effective communication techniques during the second build. All teams utilized the 3 Cs of high-quality communication (clear, concise, and complete). Most teams finished within two minutes, with all teams achieving 100% accuracy with the template model.

Next Steps in Facility Lego® GBL

I plan to present this project to our nursing evidence-based council for further review and consideration. In the meantime, five additional units have requested this training by word-of-mouth advertising. In response to these requests, I have revised the instructions so that I could train other facilitators to run a 45-minute session. Our HRO and quality staff have expressed interest in formalizing this as part of our Pathway to Excellence drive.

Conclusion

Educators can use block learning as a tactile approach for learners to witness the outcomes of their “soft skills” training, which focuses on communication and teamwork. Lego® GBL provides a fun, engaging, and novel way for healthcare workers to experience competency training. Lego® GBL and Lego® Serious Play® offer ways for teams to interact in a manner that reduces stress by removing the high stakes of traditional simulation-based education.

Michael Brakel, RN-BC, is a Registered Nurse (RN) serving with the Veterans Affairs-Northern California Health Care System (VA-NCHCS) as a Nurse Educator. He has worked with the VA-NCHCS in various capacities, including Utilization Management RN, Utilization Review RN, Community Care RN, Affiliate Professor, and Primary Care Mental Health Integration (PCMHI) RN Care Coordinator. Additionally, he has worked as a Nurse Consultant with the VA Office of Inspector General (OIG), serving as a hotline team member and team lead. Mr. Brakel holds advanced degrees in management and psychology. He graduated from Hawaii Pacific University with a degree in nursing. Mike is certified in Managed Care Nursing, Psychiatric-Mental Health Nursing, Nursing Professional Development, and Nursing Case Management. He holds certifications as a Certified Professional of Patient Safety and a Certified Professional in Healthcare Quality in addition to his nursing credentials. Resilience, compassion fatigue, nurse retention, and the application of measurement-based screening in mental health care are his main research topics. Before coming to the VA, Mr. Brakel retired after 25 years in the United States Air Force Nursing Corps, specializing in Behavioral Health. Mike served as a nurse, charge nurse, and education specialist serving on inpatient units at Travis Air Force Base, California, and the San Antonio Military Medical Center. His last roles in the Air Force were serving as the Air Force lead Mental Health Nursing Educator and as the Deputy to the Air Force Consultant to the Surgeon General for Mental Health Nursing.

Dr. Julia VanderMolen is a Professor for the Public Health program at Grand Valley State University and a Visiting Assistant Clinical Professor with the University of the Pacific, School of Health Sciences. Her research examines the benefits of assistive technology for individuals with disabilities in public health. She serves as a board member of the Disability Advocates of Kent County and is an active member of the Disability Section of the American Public Health Association (APHA). Her current research focuses on exploring the health and medical services available to individuals with intellectual and developmental disabilities.

References

Bethel, E. C., Marchetti, K. A., Hecklinski, T. M., Daignault-Newton, M. S., Kraft, K. H., Hamilton, B. D., Faerber, G. J., & Ambani, S. N. (2021). The LEGO™ exercise: An assessment of core competencies in urology residency interviews. Journal of Surgical Education, 78(6), 2063-2069. https://doi.org/10.1016/j.jsurg.2021.05.011

Lambert, N. J., Luo, X., & Ola, A. (2023). Knowing me, knowing you: Self-reflection and understanding diversity for effective teamwork Lego® building activity. Management Teaching Review, 10(1), 21-34. https://doi.org/10.1177/23792981231190589

Warburton, T., Brown, J., & Sandars, J. (2022). The use of Lego® Serious Play® within nurse education: A scoping review. Nurse Education Today, 188(1). https://doi.org/10.1016/j.nedt.2022.105528

Source link

November 24, 2025

FAU Reinstates 2 Faculty on Leave for Charlie Kirk Comments

One professor remains under investigation.

Sandi Smolker/Getty images

Two professors at Florida Atlantic University are back at work after the university placed them on administrative leave for making comments related to Charlie Kirk’s death, The South Florida Sun Sentinel reported Wednesday.

After the right-wing activist was shot and killed Sept. 10 during an event at Utah Valley University, President Donald Trump and his allies sought to punish anyone who made public comments about Kirk that could be perceived as critical. Numerous universities fired or suspended professors, including three at FAU: Karen Leader, an associate professor of art history; Kate Polak, an English professor; and Rebel Cole, a finance professor.

While Leader’s and Polak’s comments criticized Kirk, Cole’s comments were directed at Kirk’s opponents. “We are going to hunt you down. We are going to identify you,” he wrote on social media, according to the Sun Sentinel. “Then we are going to make you radioactive to polite society. And we will make you both unemployed and unemployable.”

While the three professors were on administrative leave, the university hired Alan Lawson, a former Florida Supreme Court justice, to investigate their comments. Lawson has since concluded that Cole’s and Leader’s comments were protected by the First Amendment and recommended they both be reinstated.

“The findings reflect that each professor’s social-media statements, though provocative to varying degrees, were authored in a personal capacity on matters of public concern,” Lawson wrote. Although both the FAU Faculty Senate and Cole himself objected to the investigation—Cole sued the university over an alleged First Amendment violation—Lawson’s report said the university “preserved constitutional rights while upholding its responsibility to ensure professionalism, civility, and safety within its academic community.”

Polak remains on leave while Lawson continues to investigate her comments.

Source link

November 21, 2025

A NEST for Online Learning: Supporting Students in Virtual Education – Faculty Focus

In online nursing education, a “nest” is more than a metaphor—it is a learning environment where students feel safe, supported, and guided as they prepare to enter professional practice. Drawing on my experience as a nursing educator, I developed the NEST framework—Nurturing, Esteeming and Encouraging, Supporting with Sensitive Listening, and Trust-building—to help faculty of any discipline create virtual classrooms where can students thrive. This framework provides actionable strategies that foster engagement, confidence, and professional growth, ensuring students succeed academically while cultivating the values and skills essential not only for nursing but for any profession they pursue.

Nurturing: Creating Safety and Connection in Virtual Classrooms

Nurturing in online education involves creating conditions where students feel seen, valued, and supported. Practical strategies include:

Personalized reminders about assignments and deadlines

Recognition of standout work or consistent effort

Targeted assistance during challenging weeks

Mid-week check-ins at key points (weeks 3, 6, and near the end of the course)

Weekly announcements that reassure students they are not navigating the course alone and invite collaboration

These intentional acts convey: you matter, I care about you and your growth, and I am here to support you. By nurturing students online, faculty shift from simply delivering content to facilitating discovery and meaningful learning, helping students internalize that professional values—like compassion, competence, collaboration, and understanding—are essential in nursing and in any career they pursue.

Esteeming and Encouraging: Recognizing Strengths Online

Esteeming affirms each student’s value, while encouragement supports their belief in their ability to meet challenges. In virtual classrooms, this can include:

Highlighting thoughtful discussion board posts

Sending brief messages to recognize consistent effort

Acknowledging creative approaches to assignments

Reframing mistakes as opportunities for growth

Esteeming and encouraging students create a learning environment that feels less like a points-based performance and more like a journey of discovery. Students flourish when they feel recognized and supported—lessons they carry into professional nursing practice and other careers, where acknowledging the efforts of colleagues and clients enhances collaboration, engagement, and overall effectiveness.

Supporting and Listening: Meeting Students Where They Are

Support in online education involves being present and responsive. Sensitive listening attends to both spoken and unspoken concerns. Many nursing students balance coursework, clinical hours, employment, and family responsibilities. Practical strategies include:

Timely, compassionate responses to emails

Flexibility with deadlines when life circumstances intervene

Online opportunities for students to share experiences and reflect

Structured activities like mid-week check-ins, collaborative discussions, and reflective journaling

These strategies model sensitive listening and support—skills students carry into nursing and other professional settings, fostering trust, collaboration, and meaningful connections with colleagues, clients, and communities.

Trust-Building: The Cornerstone of Engagement in Online Learning

Trust is essential for engagement in online learning. Students participate fully when they believe instructors are fair, consistent, and invested in their success. Trust is fostered online through:

Clear, consistent communication

Well-structured, predictable course design

Timely feedback that reassures students they are supported

Avoiding inconsistencies in messaging or directions, which can undermine trust

By demonstrating reliability and responsiveness, faculty model behaviors students can emulate in professional practice, strengthening relationships with patients and colleagues.

Carrying the NEST Forward: From Online Classroom to Professional Practice

The NEST framework extends beyond online classrooms. Students carry lessons of being nurtured, esteemed, supported, listened to, and trusted into every professional interaction. Faculty who model NEST help students internalize not just knowledge and skills, but the values that define my field of nursing practice—such as compassionate care, encouragement, support, sensitive listening, and trust—valuable principles that apply across any discipline and profession.

Students may leave the online course, but they take with them habits of mind and heart cultivated in the nest: confidence from nurturing, resilience from encouragement, empathy shaped by listening, and integrity rooted in trust. By creating an online nest where learning flourishes, faculty prepare students not only to succeed academically but to enrich the lives of those they serve—whether colleagues, clients, or communities in any professional field.

Sandra L. Daisley, MSN, RN, is a nursing educator with extensive experience in online pre-licensure programs. She is passionate about creating student-centered learning environments that foster engagement, professional growth, and the development of compassionate, competent nurses. Sandy is the creator of the NEST framework, a practical model for supporting students in virtual classrooms.

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November 21, 2025

A NEST for Online Learning: Supporting Students in Virtual Education – Faculty Focus

In online nursing education, a “nest” is more than a metaphor—it is a learning environment where students feel safe, supported, and guided as they prepare to enter professional practice. Drawing on my experience as a nursing educator, I developed the NEST framework—Nurturing, Esteeming and Encouraging, Supporting with Sensitive Listening, and Trust-building—to help faculty of any discipline create virtual classrooms where can students thrive. This framework provides actionable strategies that foster engagement, confidence, and professional growth, ensuring students succeed academically while cultivating the values and skills essential not only for nursing but for any profession they pursue.

Nurturing: Creating Safety and Connection in Virtual Classrooms

Nurturing in online education involves creating conditions where students feel seen, valued, and supported. Practical strategies include:

Personalized reminders about assignments and deadlines

Recognition of standout work or consistent effort

Targeted assistance during challenging weeks

Mid-week check-ins at key points (weeks 3, 6, and near the end of the course)

Weekly announcements that reassure students they are not navigating the course alone and invite collaboration

These intentional acts convey: you matter, I care about you and your growth, and I am here to support you. By nurturing students online, faculty shift from simply delivering content to facilitating discovery and meaningful learning, helping students internalize that professional values—like compassion, competence, collaboration, and understanding—are essential in nursing and in any career they pursue.

Esteeming and Encouraging: Recognizing Strengths Online

Esteeming affirms each student’s value, while encouragement supports their belief in their ability to meet challenges. In virtual classrooms, this can include:

Highlighting thoughtful discussion board posts

Sending brief messages to recognize consistent effort

Acknowledging creative approaches to assignments

Reframing mistakes as opportunities for growth

Esteeming and encouraging students create a learning environment that feels less like a points-based performance and more like a journey of discovery. Students flourish when they feel recognized and supported—lessons they carry into professional nursing practice and other careers, where acknowledging the efforts of colleagues and clients enhances collaboration, engagement, and overall effectiveness.

Supporting and Listening: Meeting Students Where They Are

Support in online education involves being present and responsive. Sensitive listening attends to both spoken and unspoken concerns. Many nursing students balance coursework, clinical hours, employment, and family responsibilities. Practical strategies include:

Timely, compassionate responses to emails

Flexibility with deadlines when life circumstances intervene

Online opportunities for students to share experiences and reflect

Structured activities like mid-week check-ins, collaborative discussions, and reflective journaling

These strategies model sensitive listening and support—skills students carry into nursing and other professional settings, fostering trust, collaboration, and meaningful connections with colleagues, clients, and communities.

Trust-Building: The Cornerstone of Engagement in Online Learning

Trust is essential for engagement in online learning. Students participate fully when they believe instructors are fair, consistent, and invested in their success. Trust is fostered online through:

Clear, consistent communication

Well-structured, predictable course design

Timely feedback that reassures students they are supported

Avoiding inconsistencies in messaging or directions, which can undermine trust

By demonstrating reliability and responsiveness, faculty model behaviors students can emulate in professional practice, strengthening relationships with patients and colleagues.

Carrying the NEST Forward: From Online Classroom to Professional Practice

The NEST framework extends beyond online classrooms. Students carry lessons of being nurtured, esteemed, supported, listened to, and trusted into every professional interaction. Faculty who model NEST help students internalize not just knowledge and skills, but the values that define my field of nursing practice—such as compassionate care, encouragement, support, sensitive listening, and trust—valuable principles that apply across any discipline and profession.

Students may leave the online course, but they take with them habits of mind and heart cultivated in the nest: confidence from nurturing, resilience from encouragement, empathy shaped by listening, and integrity rooted in trust. By creating an online nest where learning flourishes, faculty prepare students not only to succeed academically but to enrich the lives of those they serve—whether colleagues, clients, or communities in any professional field.

Sandra L. Daisley, MSN, RN, is a nursing educator with extensive experience in online pre-licensure programs. She is passionate about creating student-centered learning environments that foster engagement, professional growth, and the development of compassionate, competent nurses. Sandy is the creator of the NEST framework, a practical model for supporting students in virtual classrooms.

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November 21, 2025

University of Nebraska-Lincoln faculty vote no confidence in chancellor

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Dive Brief:

University of Nebraska-Lincoln’s faculty senate on Tuesday passed a no-confidence resolution in the public institution’s chancellor, Rodney Bennett, in part over allegations of poor leadership and financial management.
In a 60-14 vote, faculty approved a measure calling for Bennett’s removal and formally stating no-confidence over allegations of “failures in strategic leadership, fiscal stewardship, governance integrity, external relations, and personnel management.”
The no-confidence vote — UNL’s first — follows fierce debate at the university over Bennett’s plan to cut a handful of academic programs as part of a broader effort to slash $27.5 million from UNL’s budget.

Dive Insight:

The no-confidence resolution reflects faculty pushback against Bennett since September, when the chancellor unveiled a proposal to slash six programs — which he later reduced to four — as part of a budget-reduction plan.

Criticisms have focused largely on what faculty say is a lack of transparency about how, precisely, programs were judged worthy of keeping or cutting. They also allege that Bennett, who joined UNL as chancellor in 2023, has largely failed to include faculty in the decision-making process.

The budget process and timeline precluded “meaningful faculty and departmental leadership consultation” and “undermines the possibility of completing a thorough review of evidence, consequences, and public comments,” according to a Nov. 3 memo the faculty senate circulated ahead of the no-confidence resolution.

As to the timeline, Bennett announced his initial proposal on Sept. 12, and roughly two months later issued his final recommendation, which the University of Nebraska System’s regents plan to vote on at a Dec. 5 meeting.

The memo also questioned Bennett’s approach to reducing UNL’s deficit, saying that his plan relies on “immediate cost-reductions and across-the-board cuts rather than multi-year fiscal modeling or revenue diversification.”

“This system is a $3.5 to $4 billion enterprise, and we are damaging it for $27.5 million,” Faculty Senate President John Shrader said in prepared remarks at a Nov. 4 meeting. “These cuts are going to be devastating to this campus. So damaging to be irreparable.”

The memo further said Bennett had been “noticeably absent” from several faculty senate meetings and accused him of having periods of sparse contact with the senate’s executive committee, despite UNL bylaws calling for him to meet twice a month with the panel.

“Faculty shared governance represents one of many voices of institutions of higher education,” University of Nebraska System President Jeffrey Gold said in a statement emailed Wednesday. “We value the voice of UNL’s faculty; however, ultimate decisions rest with the Board of Regents.

A UNL spokesperson said Wednesday that Bennett does not plan to comment on the no-confidence vote.

In October, an academic advisory body of faculty, staff, students and administrators tasked with reviewing Bennett’s plan called for more time to consider alternatives to ending programs and voted against winding down four of the original six programs Bennett originally put forward for closure.

Bennett’s final plan spares two programs that were on the chopping block but still included two others that the Academic Planning Committee voted against eliminating.

“None of us want to be in this space, where the decisions we must make will inevitably impact the lives of individuals and change how we do some things on campus,” Bennett said in November when announcing his final proposal. “However, our reality is that UNL’s expenses have been greater than its revenue for many years.”

The proposal would slash UNL’s statistics, educational administration, Earth and atmospheric sciences, and textile, merchandising and fashion design programs.

UNL’s chapter of the American Association of University Professors, which has actively opposed the cuts, lauded Tuesday’s no-confidence vote by the faculty senate.

“The faculty has made clear that this chancellor does not have what it takes to lead our flagship institution,” UNL AAUP President Sarah Zuckerman, who is an educational administration professor at the university, said in a statement Tuesday. “We will not accept a lack of transparency, the exclusion of faculty from decision-making, or the erosion of our university’s 156-year-old mission to educate Nebraska’s students.

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November 19, 2025

6 Effective Ways to Build Attention and Boost Student Participation – Faculty Focus

Any educator can attest to the mounting challenge of maintaining student attention in the classroom. Students’ exposure to digital media from a very young age has both diminished their capacity to pay attention and led them to crave interactions with devices during times when their use is not essential.

Yet, engagement matters. Students’ capacity to participate in activities and “be present” serves as a powerful indicator of how they will fare in engagement with people and academics. Here are a few ways to foster that engagement, despite the challenges:

1. Igniting Curiosity and Relevance

Students should be taught lessons with thought-provoking questions. The more inquisitive the mind, the more in sync they are with dealing with real-world problems and building connections later in life. It’s important to have teachers who help students see value in what they’re learning. To help students discover that value, allow them to draw connections by using current events, surprising facts, or personal stories as examples. Incorporating movement and multiple modes of learning in day-to-day classroom life helps to build active inquiry. The idea is to foster greater participation and sustained focus. Relating students’ learning to their lived experience will help you boost interaction, spark curiosity, and keep students invested in their learning journey.

2. Create a Safe and Supportive Environment

Countless studies have shown that psychological safety acts as a foundation for participation; encouraging a culture where all contributions are respected builds that much-needed safety net. An essential key to building this safety net is establishing your classroom as a stable structure that can hold student curiosity, experimentation, and mistakes. Take care to build consistency between sessions. Using callbacks to past discussions, maintaining a classroom journal, or introducing a themed narrative across lessons helps students to stay engaged and makes their learning journey more cohesive. Strategies such as think-pair-share or anonymous responses can help students build confidence, especially as they grow into less familiar areas of learning.

3. Use Storytelling and Creative Expression

Consistent use of storytelling in the classroom can deepen students’ connection with one another, their teachers, and their voice. Storytelling allows students to express novel ideas in a familiar format. It also helps to make abstract topics more accessible and memorable. But storytelling isn’t all about comfort and familiarity. Surprise elements, such as unusual prompts, playful props, music, or themed challenges can keep your students invested in the art of making narrative. Surprise and innovation also lead to improved memory and a sharper capacity to synthesize abstract concepts.

4. Incorporate Movement and Sensory Engagement

Integrating interactive elements such as hands-on activity, physical movement, and visual aid helps to combat student restlessness and increase their enjoyment of a lesson. If your material requires lecture, break it up with quick, student-centered activities; a movement break; or an opportunity for students to give feedback. Incorporating movement and sensory engagement helps to keep the energy levels up and supports varied learning styles.

5. Give Students Voice and Choice

Offering multiple ways to approach an assignment or allowing students to help determine class discussion fosters an invaluable sense of agency and control. Invite students to prepare and lead part of a lesson; they’ll integrate their perspectives into the experience, which benefits their teachers, their peers, and themselves. The resulting sense of autonomy will increase their ownership and investment in learning.

6. Be Flexible and Empathetic

It’s important that teachers and caregivers for students understand and respond to individual learning rhythms and needs. Having flexibility with pace, deadlines, and participation formats helps to build trust, reduce anxiety, and support engagement. Teaching students the importance of empathy from a young age helps them grow into more responsible and emotionally mature adults.

Conclusion

Student attention and participation need to be nurtured through intention, empathy, and creativity. It’s important to have an all-around approach towards student-centered learning. It is important that we encourage our teachers to experiment, listen, and evolve with their students. As teachers and caregivers, we can empower students to embrace the learning process and build confidence by infusing joy and curiosity into the daily routine.

A happy, comfortable classroom invites deeper engagement and holds its students in consistent positive regard. Introducing short activities like gratitude journaling, music, and light-hearted check-ins, while adding a bit of humor to them, creates a welcoming atmosphere where students are more likely to speak up, stay focused, and enjoy the learning process.

Mallory Hellman (she/her) is a writer, educator, and advocate for youth creativity. Since 2015, she has served as the Director of the Iowa Youth Writing Project, where she leads programs that bring free, high-quality writing opportunities to young people across Iowa. Mallory graduated from the Iowa Writers’ Workshop (MFA in Fiction) and Harvard University (BA in English and American Literature) and has taught creative writing at the University of Iowa, the Duke University Talent Identification Program, and in schools, shelters, and community centers throughout the Midwest. Her nonfiction has appeared in publications such as Tuesday Magazine and Forbes. In recognition of her leadership and community engagement, she received the Bravo Award from the Coralville Chamber of Commerce in 2015. In 2024, she co-founded the Experiential Education Collective, an organization devoted to promoting student-centered learning and hands-on creativity in schools and other educational spaces.

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November 19, 2025

The AI Teammate: Three Roles to Build Student AI Fluency – Faculty Focus

AI is now embedded in teaching and learning. As educators, how do we help students benefit from AI without slipping into dependency, surface-level work, or ethical misconduct? I’ve found a helpful way to clarify conversations with students (and with myself) by thinking of AI as a teammate (or teammates) with clearly defined roles: the Tasker, the Draftsmith, and the Facilitator.

Imagine a meeting of a team of people: someone handles logistics, someone sketches ideas, someone pushes discussion. Framing AI this way has made it easier to talk about students remaining responsible for how and to what purposes they use AI. My approach draws on recent scholarship about AI reshaping how teams work (Dell’Acqua et al., 2025).

The AI Teammates

The Tasker

The Tasker deals with repetitive or procedural work such as managing our calendars, formatting citations, or cleaning datasets. These tasks often are tedious but essential and using AI frees time that can be focused on deeper thinking. To use a Tasker, we can set up a Robotic Process Automation (RPA) with AI, use embedded AI tools such as Copilot in MS:Word or Claude in MS:Excel or Google sheets, or create what is currently referred to as an LLM “Agent.” As Farri & Rosani (2025) describe in their HBR guide to generative AI for managers, we can use AI to lighten the load on procedural chores, affording us the time and energy to engage more with deeper thinking and learning.

Because AI output may contain mistakes, students must learn to identify the levels of risks they believe are acceptable for the given task before turning to AI and must validate its output. The level of validation required may depend on the risk level, needed accuracy and quality, and current knowledge of the tool’s metrics.

We approach the Tasker differently than we do the Draftsmith and Facilitator: we can set our RPA or Agent up to run and only involve ourselves in its applications until we’re sure it can work independently and accurately, or we can trigger the Tasker each time we need it. Students must learn to set aside sufficient validation time before designing a Tasker.

The Draftsmith

The Draftsmith can spot passive voice in students’ writing and explain why it’s problematic, convert an outline into a draft of a PowerPoint, and produce study tools such as multiple choice or essay questions, podcasts, and videos from their course notes. My engineering students have prompted their Draftsmiths using a prompt library I created specifically for them to help them convert their design clients’ stated needs into project requirements. Bussgang (2025) has pointed out how small steps like these can dramatically boost productivity without sacrificing learning.

While AI may generate text or ideas, the final product must be the student’s own (Duffy, 2025). I teach my students that, much to their dismay, they must develop their own writers’ voice before using AI and that this process can take years and many writing efforts! Our writer’s voice presents us to our bosses, colleagues, and clients given that much of our communication at work is through emails. College is the best time to invest in this effort because it’s rare to get opportunities later to do so.

From students’ comments, I believe they use AI in the Draftsmith role more frequently than the other two roles. Few realize the Draftsmith increases cognitive load when they use it correctly and decreases their learning when they use it incorrectly!

It increases the load because they must provide the AI with significant context for it to provide anything other than banal, common prose that flattens their own voice (Purohit, 2025) or “creative” prose that is meaningless. AI use decreases their learning when they use it to write first and second drafts because writing sharpens our thinking and embeds learned concepts into our long-term memory.

The Facilitator

Instead of using AI to generate content (the Draftsmith), the Facilitator is a use of AI as a thinking partner (Solis, 2024 and HBSP’s ManageMentor course 2025). A student might ask AI to play devil’s advocate, suggest counterarguments, or pose probing questions when their paper’s argument needs strengthening. AI might help simulate a stakeholder’s perspective with whom the student role plays to prepare for a meeting or consider how their ideas might land with their student group peers. My students have used AI in the Facilitator role to pressure test their design ideas, review their research plans, and prepare to give presentations. When students use the Facilitator, they’re reflecting (Harbridge, 2025) and thereby deepening their learning.

To get the best value from AI as a Facilitator, the student must approach it with the expectation that it will take considerable time. The Facilitator provides meaningful interaction only when the student gives it their full attention, asks probing questions, provides significant context, and is patient. They may need to iterate, restating their prompts or providing more information, and to ask the LLM to be candid and critical. They may need to step away from the LLM, perhaps try a different one or come back on another day, when it goes off in the wrong direction.

We have become too used to scanning an LLM’s output. Just as I would not expect a student who came to me for career advice to start scrolling on their phone while I’m talking, I must teach them to give their full attention to the Facilitator.

What I’m suggesting here is not a list of use cases. Instead, I’m providing students with an approach to using AI where they plan before typing into the chat box, see its best use as a Facilitator that partners with them in learning and development, and recognize that validation and reading output will be time and cognitively intensive.

What This Means for Teaching

I’ve found that when I teach these roles to students before assigning homework, they make better choices regarding when and how to use AI. Here are some tactics I’ve tried that have netted positive results:

Design assignments that invite different roles. For example, ask students to begin with AI as a Tasker (perhaps organizing sources or cleaning a dataset), then shift to using the Draftsmith to help them find passive voice or other syntax issues in a paper, and finally draw on the Facilitator to find the holes in their arguments before submitting a final paper. Intentionally stating the role each assignment calls for and requiring them to state when they’re using the Tasker, Draftsmith, or Facilitator solidifies their understanding that their approach to AI differs by role.

Be clear about where AI helps and where it doesn’t. AI can help with structure, suggestions, and ideation, but it cannot replace revision, critical thinking, or the development of one’s own voice. This must be intentionally taught by including questions requiring students to reflect on what worked and where the AI led them astray in any assignments allowing AI use.

Encourage disclosure. I talk extensively about “Total AI Transparency”, ensuring students that I will note any use of AI in my communications with them and I expect the same from them. Trust has broken down as both students and instructors believe the other is using AI when they’re not and failing to recognize when they are. Owning up to my own use and being clear on why I used AI for that task encourages students to do the same.

Closing Thoughts

We need to steer students away from extremes of either refusing to use AI at all or letting it rob them of learning. By distinguishing the roles of Tasker, Draftsmith, and Facilitator, we clarify our expectations of students. More importantly, we help them become more deliberate in their approach, preparing them to be AI-fluent.

Illysa Izenberg is an Associate Teaching Professor for the Center for Leadership Education in the Whiting School of Engineering at The Johns Hopkins University. She has been teaching management and business ethics to graduate and undergraduate students via Face-to-Face, online, and blended courses since 2006. Izenberg earned her MBA from the Harvard Graduate School of Business and is the winner of both the Alumni and Pond Excellence in Teaching Awards (2016 and 2020 respectively).

References

Bussgang, J. (2025, May 20). 3 small steps to 10x your productivity with AI this week. The Experimentation Machine. https://experimentationmachine.com/p/10x-this-week

Duffy, A. (2025, April 11). Your CEO just said ‘Use AI or else.’ Here’s what to do next. Every. https://every.to/p/your-ceo-just-said-use-ai-or-else-here-s-what-to-do-next

Farri, E., & Rosani, G. (2025). HBR guide to generative AI for managers. Harvard Business Review Press.

Gross, A. (2025). AI Crash Course [Online course]. SectionAI. https://www.sectionschool.com/courses/ai-crash-course-workshop

Harbridge, R. (2025). AI for Team Leaders [Online course]. SectionAI.

Harvard Business Publishing. (2025). Help your team harness generative AI (Lesson 1). In Leading with generative AI [Online course]. Harvard ManageMentor.

Purohit, R. (Host). (2025, June 18). The man inside the minds of the people building AGI [Audio podcast episode]. In AI & I. Every.

Solis, B. (2024, November). Train your brain to work creatively with Gen AI. Harvard Business School Publishing.

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November 17, 2025

Tag: Faculty

Rise of AI in Research and Publication

Ethical Implications and Risks

The Irreplaceable Role of Human Editorial Judgment

Rise of AI in Research and Publication

Ethical Implications and Risks

The Irreplaceable Role of Human Editorial Judgment

The Idea for Lego® GBL

Lego® GBL and Communication Training

Projected Outcomes of Training

Build Time: Everything is Awesome!

Next Steps in Facility Lego® GBL

Conclusion

The Idea for Lego® GBL

Lego® GBL and Communication Training

Projected Outcomes of Training

Build Time: Everything is Awesome!

Next Steps in Facility Lego® GBL

Conclusion

Nurturing: Creating Safety and Connection in Virtual Classrooms

Esteeming and Encouraging: Recognizing Strengths Online

Supporting and Listening: Meeting Students Where They Are

Trust-Building: The Cornerstone of Engagement in Online Learning

Carrying the NEST Forward: From Online Classroom to Professional Practice

Nurturing: Creating Safety and Connection in Virtual Classrooms

Esteeming and Encouraging: Recognizing Strengths Online

Supporting and Listening: Meeting Students Where They Are

Trust-Building: The Cornerstone of Engagement in Online Learning

Carrying the NEST Forward: From Online Classroom to Professional Practice

Dive Brief:

Dive Insight:

1. Igniting Curiosity and Relevance

2. Create a Safe and Supportive Environment

3. Use Storytelling and Creative Expression

4. Incorporate Movement and Sensory Engagement

5. Give Students Voice and Choice

6. Be Flexible and Empathetic

Conclusion

The AI Teammates

The Tasker

The Draftsmith

The Facilitator

What This Means for Teaching

Closing Thoughts