Tag: teaching with technology

Artificial Intelligence and Critical Thinking in Higher Education: Fostering a Transformative Learning Experience for Students – Faculty Focus
In a digitally-driven world, artificial intelligence (AI) has become the latest technology that either will save or doom the planet depending on who you speak with. Remember when telephones (the ones that hung on the wall) were dubbed as privacy invaders? Even the radio, television, and VHS tapes were feared at the beginning of their existence. Artificial intelligence is no different, but how can we ease the minds of those educators who have trouble embracing the newest innovation in emerging technologies? A shift in the fundamental mindset of educators and learners will be vitally important as AI becomes more and more commonplace. To guide this transformative learning process, critical thinking will become an invaluable commodity.

The critical thinking model developed by Dr. Richard Paul and Dr. Linda Elder is pragmatic and fosters the critical thinking skills needed to navigate AI. Critical thinking is defined by Paul and Elder as “the art of analyzing and evaluating thought processes with a view to improving them” (Paul and Elder 2020, 9). The key is to teach your students ways to improve their thinking and using the Paul and Elder model can be an effective tool.

Navigating the Disorienting Dilemma

As we reason through this innovative technology, we will question truth and reality. Teaching students to analyze critically the information generated from AI chatbots will become necessary for a progressing society. Determining fact from fiction will be a skill that dedicated educators will train their students to harness in the work they complete.

Mezirow (1994, 224) contended that a transformative learning experience starts with a disorienting dilemma that causes an individual to question their understanding of previous assumptions by critically reflecting, validating the critical reflection with insight, and acting upon the new information. I, like many I assume, believed that artificial intelligence was a far-fetched concept that would only be real in the movies; however, AI is here and large-language models, such as Chat-GPT and Gemini, are only going to get more sophisticated with time. I also realized that once I was exposed to the Paul and Elder model for critical thinking in grad school, I was ignorant. I had my transformative moment when I realized that critical thinking is more complex than I thought and that I would need to step up my thinking game if I wanted to become an advanced thinker. Artificial intelligence will challenge even the most confident thinkers. Determining fact from fiction will be the disorienting dilemma that will lead us on this transformative journey. As educators, three strategies that we can use to support this transformation with students are to step up our thinking game, model critical thinking, and use AI for our benefit.

Step Up Your Thinking Game

An advanced thinker not only poses questions to others but focuses within. Understanding the why behind reasoning, acknowledging personal biases and assumptions, and valuing other’s perspectives are key to developing critical thinking skills. The reason that you and your students choose to use AI should be clear and intentional. AI is a tool that produces instantaneous solutions. The resulting details from AI should be analyzed for accuracy, logic, and bias. Results should be compared with multiple sources to ensure that the information, the conclusions, and the implications are precise and complete. Practicing these strategies fosters the development of intellectual virtues, such as intellectual humility, intellectual autonomy, and intellectual integrity.

Model Critical Thinking

As educators, we serve as leaders. Ultimately, our students look up to us and use our guidance in their learning. By modeling critical thinking with students, you are leading the way to fostering intentional questioning, ethical principles, and reflective practices. A start is to change the focus of your teaching from the expectation that students regurgitate information to focusing on more challenging, thought-provoking content that fosters thinking. AI can be a helpful tool for coming up with ideas, helping to shape lesson plans, and designing activities, but the real work will come from designing authentic questions that students can be trained to ask regardless of what the AI generates, such as:
1. How can I verify the validity and accuracy of this information?
1. Does the response represent logical and in-depth details?
1. Is the information precise, significant, and relevant to the knowledge that I am seeking?
1. Are perspectives that differ from mine represented or can I recognize bias in the information?
1. What other questions could be asked to dive deeper and more concisely into the information?
Use AI for Your Benefit

Generating activity ideas or lesson plans, creating rubrics, and assisting with basic writing tasks are three ways to easily get started with an AI chatbot. If the output is not what you expected or is incomplete, continue to give the chatbot more information to drive the chatbot to produce the desired outcome. Once you begin practicing with an AI chatbot, achieving your desired outcomes will become second nature.

Using learning outcomes as the basis for an inquiry provides AI with the information needed to generate an activity or lesson plan in seconds with objectives, timed components, suggestions for implementation, a materials list, closing, and follow-up ideas for the activity. Try typing a statement into an AI chatbot, such as ChatGPT or Gemini, and be amazed at the magic. When formulating your inquiry, remember to start with the end goal in mind and describe to AI the output you want. For example, type “Use this learning outcome to create an activity: (add learning outcome)”. AI will generate a comprehensive activity with all the bells and whistles.

Rubric development can be a cumbersome process; therefore, using AI to generate a rubric for a project that you have poured sweat and tears into creating is a very simple and time-saving process. Ask AI to generate a rubric based on the information and directions that you give your students. If the generated rubric is not the right style or in the right format, simply refocus the AI chatbot by being more explicit in your instructions. For example, you may need to be as specific as “Create an analytic rubric with 100, 90, 80, 70, and 0 as the levels of performance using the following expectations for the assignment (paste directions and outcomes). As always, use your critical thinking skills to evaluate the rubric and edit it to best meet your needs before sharing it with students.

Use AI to assist you with generating clearer and more concise messages. When creating an email, giving student feedback, or writing in general, a quick and easy way to use AI to assist you is to give the command “make this sound better” and plop in your message. When teaching your students to use AI, have them question the output that was generated. For example, “Why is this statement more clear and concise than my original thought” or “What can I learn from how AI changed my verbiage?” Focusing on the “why” of the produced information will be the key to fostering critical thinking with your students.

AI is a resourceful and impactful, yet imperfect tool. Fostering critical thinking with your students will help them develop the skills needed to recognize bias, inaccuracies, and AI hallucinations. With the practice of creating specific instructions and questioning the outcome, students will learn to trust themselves to defend AI-generated information.

Dr. Tina Evans earned her Ed.D. in Adult Education from Capella University in 2024. With over 25 years of experience in the education field, she brings deep expertise in higher education curriculum design, technology integration, and evidence-based practices for adult learners. Driven by a passion for critical thinking and a genuine commitment to supporting others, Dr. Evans continues to make a meaningful impact in both her professional and personal spheres.

References

Mezirow, J. 1994. “Understanding Transformation Theory.” Adult Education Quarterly, 44 (4): 222-232. https://journals.sagepub.com/doi/10.1177/074171369404400403

Paul, Richard, and Elder, Linda. 2020. The Miniature Guide to Critical Thinking: Concepts and Tools, 8th ed. Rowman & Littlefield.
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July 14, 2025
Artificial Intelligence and Critical Thinking in Higher Education: Fostering a Transformative Learning Experience for Students – Faculty Focus
In a digitally-driven world, artificial intelligence (AI) has become the latest technology that either will save or doom the planet depending on who you speak with. Remember when telephones (the ones that hung on the wall) were dubbed as privacy invaders? Even the radio, television, and VHS tapes were feared at the beginning of their existence. Artificial intelligence is no different, but how can we ease the minds of those educators who have trouble embracing the newest innovation in emerging technologies? A shift in the fundamental mindset of educators and learners will be vitally important as AI becomes more and more commonplace. To guide this transformative learning process, critical thinking will become an invaluable commodity.

The critical thinking model developed by Dr. Richard Paul and Dr. Linda Elder is pragmatic and fosters the critical thinking skills needed to navigate AI. Critical thinking is defined by Paul and Elder as “the art of analyzing and evaluating thought processes with a view to improving them” (Paul and Elder 2020, 9). The key is to teach your students ways to improve their thinking and using the Paul and Elder model can be an effective tool.

Navigating the Disorienting Dilemma

As we reason through this innovative technology, we will question truth and reality. Teaching students to analyze critically the information generated from AI chatbots will become necessary for a progressing society. Determining fact from fiction will be a skill that dedicated educators will train their students to harness in the work they complete.

Mezirow (1994, 224) contended that a transformative learning experience starts with a disorienting dilemma that causes an individual to question their understanding of previous assumptions by critically reflecting, validating the critical reflection with insight, and acting upon the new information. I, like many I assume, believed that artificial intelligence was a far-fetched concept that would only be real in the movies; however, AI is here and large-language models, such as Chat-GPT and Gemini, are only going to get more sophisticated with time. I also realized that once I was exposed to the Paul and Elder model for critical thinking in grad school, I was ignorant. I had my transformative moment when I realized that critical thinking is more complex than I thought and that I would need to step up my thinking game if I wanted to become an advanced thinker. Artificial intelligence will challenge even the most confident thinkers. Determining fact from fiction will be the disorienting dilemma that will lead us on this transformative journey. As educators, three strategies that we can use to support this transformation with students are to step up our thinking game, model critical thinking, and use AI for our benefit.

Step Up Your Thinking Game

An advanced thinker not only poses questions to others but focuses within. Understanding the why behind reasoning, acknowledging personal biases and assumptions, and valuing other’s perspectives are key to developing critical thinking skills. The reason that you and your students choose to use AI should be clear and intentional. AI is a tool that produces instantaneous solutions. The resulting details from AI should be analyzed for accuracy, logic, and bias. Results should be compared with multiple sources to ensure that the information, the conclusions, and the implications are precise and complete. Practicing these strategies fosters the development of intellectual virtues, such as intellectual humility, intellectual autonomy, and intellectual integrity.

Model Critical Thinking

As educators, we serve as leaders. Ultimately, our students look up to us and use our guidance in their learning. By modeling critical thinking with students, you are leading the way to fostering intentional questioning, ethical principles, and reflective practices. A start is to change the focus of your teaching from the expectation that students regurgitate information to focusing on more challenging, thought-provoking content that fosters thinking. AI can be a helpful tool for coming up with ideas, helping to shape lesson plans, and designing activities, but the real work will come from designing authentic questions that students can be trained to ask regardless of what the AI generates, such as:
1. How can I verify the validity and accuracy of this information?
1. Does the response represent logical and in-depth details?
1. Is the information precise, significant, and relevant to the knowledge that I am seeking?
1. Are perspectives that differ from mine represented or can I recognize bias in the information?
1. What other questions could be asked to dive deeper and more concisely into the information?
Use AI for Your Benefit

Generating activity ideas or lesson plans, creating rubrics, and assisting with basic writing tasks are three ways to easily get started with an AI chatbot. If the output is not what you expected or is incomplete, continue to give the chatbot more information to drive the chatbot to produce the desired outcome. Once you begin practicing with an AI chatbot, achieving your desired outcomes will become second nature.

Using learning outcomes as the basis for an inquiry provides AI with the information needed to generate an activity or lesson plan in seconds with objectives, timed components, suggestions for implementation, a materials list, closing, and follow-up ideas for the activity. Try typing a statement into an AI chatbot, such as ChatGPT or Gemini, and be amazed at the magic. When formulating your inquiry, remember to start with the end goal in mind and describe to AI the output you want. For example, type “Use this learning outcome to create an activity: (add learning outcome)”. AI will generate a comprehensive activity with all the bells and whistles.

Rubric development can be a cumbersome process; therefore, using AI to generate a rubric for a project that you have poured sweat and tears into creating is a very simple and time-saving process. Ask AI to generate a rubric based on the information and directions that you give your students. If the generated rubric is not the right style or in the right format, simply refocus the AI chatbot by being more explicit in your instructions. For example, you may need to be as specific as “Create an analytic rubric with 100, 90, 80, 70, and 0 as the levels of performance using the following expectations for the assignment (paste directions and outcomes). As always, use your critical thinking skills to evaluate the rubric and edit it to best meet your needs before sharing it with students.

Use AI to assist you with generating clearer and more concise messages. When creating an email, giving student feedback, or writing in general, a quick and easy way to use AI to assist you is to give the command “make this sound better” and plop in your message. When teaching your students to use AI, have them question the output that was generated. For example, “Why is this statement more clear and concise than my original thought” or “What can I learn from how AI changed my verbiage?” Focusing on the “why” of the produced information will be the key to fostering critical thinking with your students.

AI is a resourceful and impactful, yet imperfect tool. Fostering critical thinking with your students will help them develop the skills needed to recognize bias, inaccuracies, and AI hallucinations. With the practice of creating specific instructions and questioning the outcome, students will learn to trust themselves to defend AI-generated information.

Dr. Tina Evans earned her Ed.D. in Adult Education from Capella University in 2024. With over 25 years of experience in the education field, she brings deep expertise in higher education curriculum design, technology integration, and evidence-based practices for adult learners. Driven by a passion for critical thinking and a genuine commitment to supporting others, Dr. Evans continues to make a meaningful impact in both her professional and personal spheres.

References

Mezirow, J. 1994. “Understanding Transformation Theory.” Adult Education Quarterly, 44 (4): 222-232. https://journals.sagepub.com/doi/10.1177/074171369404400403

Paul, Richard, and Elder, Linda. 2020. The Miniature Guide to Critical Thinking: Concepts and Tools, 8th ed. Rowman & Littlefield.
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July 14, 2025
5 Steps to Update Assignments to Foster Critical Thinking and Authentic Learning in an AI Age – Faculty Focus

I recently attended a student panel on use of AI in college classes. The three panelists shared their perspectives, borne out in an April 2025 Gallup survey: they want to learn to use AI tools in appropriate ways, they’re anxious about the potential negative impact on their critical thinking skills, and they want explicit guidance from their faculty members—which they’re not consistently getting.

Even, or especially, in an AI age, we know our students need to think critically and learn authentically to be productive and engaged citizens and future employees. We recognize we need to update assignments to promote academic integrity in an AI age, yet many of us feel unprepared to do so. The crux of the problem is this: how do we foster critical thinking and authentic learning when it’s so easy for students to outsource their cognitive work?

One promising solution to the triple challenge of fostering critical thinking, meaningful learning, and academic integrity is to double down on transparency. We can provide the guidance students want, embed analysis and evaluation into our assignments to get at that all-important critical thinking, and nudge students toward integrity. How? By embracing transparency.

Let’s detail our expectations for responsible AI use. Let’s emphasize the why: why we want students to use their own cognitive abilities for some tasks, why using AI could be helpful at times, and why we’ve crafted our AI-integrated assignments in the ways we have. Finally, let’s ask students to disclose their use in full transparency (and reflect on their learning, as Marc Watkins argues here).

In short, we can promote integrity when assessments are meaningful, purposeful, and include transparent instruction on appropriate AI use. We can teach students to critically analyze AI-assisted work and promote authentic learning as we do. To help us achieve these aims, here are five steps to update assignments in ways that help students learn the skills they need while fostering a culture of academic honesty.

Step 1: Take a critical look at your current syllabus.

If you’re like me, you have tried-and-true activities and assignments that you’ve relied on for many years. Some of these may be updateable, but others may just need to go. If AI can easily complete a task (try running your instructions through a tool like ChatGPT to find out), maybe it’s no longer a relevant measure of authentic learning. Also, following the remaining steps below will likely mean that you add new instructional practices (like modelling AI use) and new components of the assignments you update (like a reflection on how AI helped or hindered learning). Make time for these important new course elements by getting rid of outdated tasks.

Step 2: Consider whether and how students should use AI on the assignments you keep.

Remember, students want to know exactly what is appropriate for AI use in your class. A helpful tool for this process is the 5-level AI Assessment Scale (AIAS). The levels range from No AI, AI Planning, AI Collaboration, Full AI, and AI Exploration. Each one identifies and sanctions different ways students can use AI in appropriate and meaningful ways to support their learning.

Leon Furze, one of the creators of the AIAS, presents it a tool that helps update our assignments and start conversations with our students. He recommends using this framework to guide your thinking: break down each assignment, project, or discussion board activity into disparate steps, then decide for which parts of the process AI use is appropriate. Providing transparent guidance, guidance that may vary for different parts of the project, is what students need right now.

Step 3: Carve out time to discuss and model your expectations.

Many students are not sure what is acceptable in this current moment. What better way to help them feel confident while developing the AI skills they need than modelling what you’re looking for? Take class time or record a video for your online class to teach your students what you expect them to do with AI for each assignment, what not to do, and what you’ll be looking for in their finished product.

As you approach this aspect of instruction, take heart. I don’t think every instructor needs to be an AI expert, but I do think we’re doing our students a disservice if we’re not teaching them how to be AI Whisperers, a concept I gleaned from Ethan Mollick’s 2024 book, Co-Intelligence. A new kind of expertise is emerging, he argues: the skilled and effective use of AI in every field. As disciplinary experts, you know what kind of AI use will help students learn your material and what will disempower them as learners. Let’s allocate time to help students develop AI literacy while maintaining their agency.

Step 4: Ask students to disclose their AI use, as noted above.

The student panelists showed palpable relief when they described instructors who simply had them cite their use of AI. “Encourage your students to be transparent about their AI use,” one student, a finance major, said. As she talked about how simple it was to add a line at the end of the assignment such as, “ChatGPT generated the outline for this essay,” the anxiety that had previously clouded her expression disappeared.

One approach is to use the AI Disclosure (AID) framework to document how students used AI, or add an appendix to each assignment, or add comments or footnotes to make transparent what they wrote and what AI wrote. Get students to declare their AI use and even better, ask them to reflect on whether their use helped or hindered their learning.

Step 5: If you suspect inappropriate use of AI, don’t accuse students of cheating.

Instead, have a conversation with them. Recall that a primary goal of the AIAS is to facilitate discussions about AI use. Imagine that as a class, you agreed that Level 2 (AI Planning) was appropriate for a particular project. If a student submits work that seems to have been completed at Level 4 (Full AI), refer back to the framework to facilitate a conversation about your perception of their work and their process. As AIAS co-creator Leon Furze points out, now you can get away from wondering whether a student cheated with AI and instead ask, “can I make a valid judgement of this student’s capabilities [whether they have used AI or not]?”

And as argued by the authors of a new book titled The Opposite of Cheating: Teaching for Integrity in an Age of AI, this takes moral accusation out of the conversation, reduces the adversarial tone, and enables students to reflect on and hopefully learn from the experience. You can also decide together what actions should take place next, whether the student resubmits the assignment in accordance with your AI-usage guidance, whether they lose the opportunity to earn a grade for that assignment, or whatever else you and your student decide is appropriate in that situation.

Students want to know how to use AI well. “If we don’t teach students how to use AI responsibly, they’re going to be poorly equipped for the workforce,” said the third student panelist, a computer science major. Let’s update our assignments to facilitate meaningful learning of our content, the skills students need in an AI age, and ethical, integrous use of AI to equip them for the workplace they’ll enter. In doing so, we’re helping to develop engaged citizens who think critically about information they encounter. I can’t think of more important work to be engaged in at this moment in time.

Flower Darby is an associate director of the Teaching for Learning Center at the University of Missouri, a co-author of The Norton Guide to Equity-Minded Teaching (2023), and the lead author, with James M. Lang, of Small Teaching Online: Applying Learning Science in Online Classes (2019).

References

Bertram Gallant, Tricia, and David A. Rettinger. 2025. The Opposite of Cheating: Teaching for Integrity in the Age of AI. University of Oklahoma Press.

Furze, Leon. 2024. “Updating the AI Assessment Scale.” August 28. https://leonfurze.com/2024/08/28/updating-the-ai-assessment-scale/

Furze, Leon. 2025. LinkedIn post. https://www.linkedin.com/posts/leonfurze_artificialintelligence-aieducation-assessment-activity-7295247135480889346-UWFC/

Kassorla, M. 2024. “Our New Course: Some Highlights.” January 4. https://michellekassorla.substack.com/p/our-new-course-some-highlights

McMurtrie, Beth. 2025. “AI Unready.” January 30. https://www.chronicle.com/newsletter/teaching/2025-01-30?utm_source=Iterable&utm_medium=email&utm_campaign=campaign_12441556_nl_Teaching_date_20250130&sra=true

Mollick, E. 2024. Co-Intelligence: Living and Working with AI. Portfolio.

Walton Family Foundation and Gallup. 2025. How American Youth View and Use Artificial Intelligence. https://www.gallup.com/analytics/658901/walton-family-foundation-gallup-voices-gen-american-youth.aspx

Watkins, Marc. 2024. “Make AI Part of the Assignment.” October 2. https://www.chronicle.com/article/make-ai-part-of-the-assignment?sra=true

Weaver, Kari D. 2024. “The Artificial Intelligence Disclosure (AID) Framework: An Introduction.” College & Research Libraries News 85 (10). https://crln.acrl.org/index.php/crlnews/article/view/26548/34482

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July 9, 2025
Reimagining the Flipped Classroom: Integrating AI, Microlearning, and Learning Analytics to Elevate Student Engagement and Critical Thinking – Faculty Focus

The traditional flipped classroom model, which reverses the conventional lecture-homework structure, has evolved significantly since its inception. In the digital era, especially post-pandemic, this strategy has gained renewed importance for fostering active learning, critical thinking, and academic resilience. Today, the flipped classroom is no longer just about moving lectures online but about curating immersive, personalized learning environments. The integration of Artificial Intelligence (AI), microlearning, and learning analytics provides new dimensions to this pedagogical approach, enhancing both student preparation and in-class engagement. This article explores how these three components can reshape flipped learning and address persistent challenges such as student unpreparedness, fear of participation, and lack of motivation.

Flipped Classroom 2.0: Enriching the Core Strategy

The original flipped classroom model aimed to reverse the traditional structure of education by shifting the transmission of basic content, often done through lectures, outside the classroom, while using face-to-face class time for active engagement and problem-solving. While this model offered significant benefits, the ever-changing dynamics of education in the digital era demand a more adaptive and responsive framework. This has led to the evolution of Flipped Classroom 2.0, a pedagogy that not only retains the foundational principles of the original model but enhances them with modern technologies and learner-centered practices.

AI Tools

In the Flipped Classroom 2.0 model, the learning process is amplified by integrating Artificial Intelligence (AI) tools, which help personalize student learning pathways. AI-enabled systems such as adaptive learning platforms, chatbots, and generative tools like ChatGPT can provide students with on-demand explanations, simulate peer discussions, offer low-stakes quizzes, and give instant feedback. This technological support allows students to learn at their own pace and revisit complex material without feeling anxious or dependent solely on the instructor. From the educator’s side, AI tools help identify patterns in learner behavior and performance, allowing for more targeted interventions during class time.

Microlearning

Microlearning plays a central role in supporting pre-class preparation under the Flipped Classroom 2.0 framework. Instead of overwhelming students with lengthy video lectures or dense readings, microlearning delivers short, focused modules that concentrate on single learning objectives. These modules are ideal for students who are accustomed to fast-paced digital environments and may have limited attention spans. Microlearning enhances retention by segmenting information and reinforcing key concepts through repetition and brief assessments. It also empowers students to learn efficiently on mobile devices and during flexible hours, which is particularly valuable in hybrid and online learning contexts.

Learning Analytics

Learning analytics represents another foundational component of the Flipped Classroom 2.0 design. By utilizing Learning Management Systems (LMS) and built-in analytics dashboards, instructors can gain valuable insights into which students have completed pre-class activities, how they have performed, and where they may need additional support. Analytics tools also promote student accountability, as learners are able to track their own progress and receive early alerts when they are falling behind. These data-driven approaches make it possible to transition from reactive teaching to proactive guidance.

Collectively, these innovations: AI, microlearning, and learning analytics, enhance the effectiveness of the flipped classroom by aligning content delivery, student support, and real-time feedback. Flipped Classroom 2.0 is not merely a technological upgrade; it is a reimagined learning experience that promotes self-directed learning, critical thinking, and inclusivity. It encourages students to become active participants rather than passive recipients, and it positions educators as facilitators and data-informed decision-makers in the learning process.

Understanding Student Resistance in the Digital Era

Unpreparedness often stems not from laziness or disinterest, but from deeper psychological or contextual barriers that influence a student’s ability to engage. In many cases, students may feel overwhelmed by the unfamiliarity of new instructional models or lack the confidence needed to navigate them successfully. This resistance is especially prominent in environments where flipped classroom strategies are introduced abruptly or without adequate scaffolding. In digitally enhanced learning spaces, Artificial Intelligence tools can serve as diagnostic aids to help educators understand the roots of student resistance.

By monitoring metrics such as time spent on tasks, levels of participation, and types of interactions within pre-class activities, AI systems can identify patterns of disengagement or confusion. For example, if students frequently abandon certain video modules or quiz sections, this may signal content complexity, misalignment with learning styles, or underlying cognitive fatigue. Moreover, many students, especially those transitioning from traditional learning environments, may carry negative assumptions about active learning approaches. They may perceive them as chaotic, unpredictable, or more demanding than passive learning formats. Educators must dig deeper to explore these sentiments and confront the emotional undercurrents that influence classroom behavior. Addressing resistance with empathy, transparency, and gradual acclimatization is crucial for long-term student buy-in.

Addressing Fear Through Technology-Supported Safety

Fear is one of the most formidable barriers to classroom participation. Whether it’s the fear of giving incorrect answers, speaking publicly, or being judged by peers, these emotions can significantly hinder student engagement. In the flipped classroom, where much of the responsibility for learning shifts to students, this fear may become even more pronounced if not properly addressed. Technology, particularly AI-driven tools, can be strategically used to create psychologically safe learning environments. For example, private practice environments powered by chatbots or simulations can offer students a space to make mistakes, ask questions, and rehearse ideas without fear of embarrassment. These tools are particularly beneficial for introverted students or those who lack confidence in their subject knowledge.

Microlearning also plays a vital role in reducing anxiety. By breaking down complex content into manageable chunks, students can focus on mastering one concept at a time. This incremental mastery builds confidence and reduces cognitive overload. When paired with formative assessments and feedback loops, microlearning helps normalize error-making as part of the learning process. Analytics further enhance psychological safety by providing both educators and students with objective data on progress. When students see that others are also struggling with the same concepts or that their performance is gradually improving, they are more likely to perceive learning as a collective and iterative journey.

Making Learning Visible with Analytics and Scaffolds

Visibility of learning progress is essential in maintaining student accountability and fostering meaningful classroom interactions. In traditional flipped classrooms, instructors often face the challenge of determining whether students have genuinely completed pre-class tasks or engaged with the material in a substantive way.

Flipped Classroom 2.0 addresses this issue by leveraging data and scaffolding techniques that make learning both measurable and visible. Learning analytics tools embedded in LMS platforms can track completion rates, quiz scores, engagement time, and areas of difficulty. This data is accessible to both teachers and students through visual dashboards, which serve as powerful motivators and intervention tools. Educators can use this information to adjust instruction, form differentiated groups and provide individualized support. Scaffolding further supports this visibility. Templates, guided note-taking structures, interactive mind maps, and learning journals help students organize their thoughts and reflect on their understanding. When integrated with AI, these scaffolds can be customized based on student performance and learning preferences. This transparency not only improves learning outcomes but also enhances communication between instructors and students.

Designing Pre-Class Work That Drives In-Class Success

A key feature of the flipped classroom model is the dependency on students completing pre-class work so they can actively participate in class discussions and activities. However, the perceived value of pre-class tasks directly influences student compliance and effort. To elevate this value, educators must clearly connect pre-class preparation with in-class success. AI can support this connection by generating customized content summaries, quizzes, and diagnostic questions based on each student’s pre-class performance. For instance, if a student demonstrates mastery of foundational concepts, they can be prompted with higher-order questions to challenge their thinking. Conversely, students who struggle can be provided with remedial resources and practice modules. In-class activities should build directly on pre-class efforts. Group discussions, simulations, debates, and problem-solving exercises should reference or utilize outputs from the pre-class assignments. This integration reinforces the message that preparation is essential for success and ensures that students recognize the practical benefits of investing time in asynchronous learning.

Gamification techniques, such as digital badges, progress milestones, and peer recognition can further motivate students to complete pre-class tasks. When these activities contribute to course grades or unlock exclusive learning opportunities, their relevance is amplified.

Establishing Routine and Engagement with Focusing Activities

The transition from asynchronous pre-class learning to synchronous in-class application can be challenging if not facilitated through structured routines. Focusing activities, particularly those conducted at the beginning of class, serve as critical bridges that help students activate prior knowledge and reorient their attention. These activities may include short reflective prompts, polls, problem-solving warmups, or collaborative brainstorming sessions. When enhanced with technology, focusing activities become even more impactful. For example, AI-driven polling platforms can pose adaptive questions tailored to the students’ recent performance.

Visualization tools can help students construct or revise concept maps based on their understanding of the pre-class content. Establishing predictable routines around these activities builds habits of participation. Over time, students internalize the rhythm of flipped learning: prepare independently, apply collaboratively, reflect continuously. Such engagement patterns increase cognitive readiness and reduce classroom management challenges.

Avoiding Pitfalls in Tech-Enhanced Flipped Classrooms

While Flipped Classroom 2.0 offers numerous benefits, its success is contingent upon thoughtful implementation. Several common pitfalls can undermine the model’s effectiveness. One of the most prevalent mistakes is treating technology as a substitute for pedagogy. Simply replacing lectures with videos or adding quizzes does not constitute a true flip. Without alignment to learning objectives and instructional goals, these tools can confuse rather than support learners.

Another challenge is content overload. Students may feel overwhelmed if asked to review long readings, videos, and quizzes without clear guidance or purpose. Microlearning and scaffolding should be used to break down materials and provide learning pathways that are manageable and coherent. Educator readiness is another often-overlooked factor. Successful adoption of AI tools and data dashboards requires faculty training and support. Instructors must be equipped not only with technical skills but also with an understanding of how to interpret analytics and adjust pedagogy accordingly.

Lastly, student feedback should be incorporated into the design and refinement of flipped classroom practices. Continuous evaluation, surveys, and informal check-ins can reveal usability issues and highlight opportunities for improvement.

Toward a Future-Ready Learning Model

Reimagining the flipped classroom requires more than adopting trendy tools, it demands a philosophical shift. By combining AI, microlearning, and learning analytics, educators can create classrooms that are not only flipped but also fluid, feedback-driven, and future-ready. These strategies support student autonomy, foster critical thinking, and build academic resilience in an unpredictable world. The next frontier of flipped learning is not about technology for its own sake, but about purposeful integration that places learners at the center.

N. P. K. Ekanayake

Ms. Neranjana Priyangani Kumari Ekanayake, a senior lecturer at the University of Kelaniya, teaches Investment and Portfolio Management, Enterprise Resource Planning, Behavioural Finance, and Advanced Management Accounting. She holds a BBA in Accounting (Special) and an MSc in MMs. Neranjana Priyangani Kumari Ekanayake, a senior lecturer at the University of Kelaniya, teaches Investment and Portfolio Management, Enterprise Resource Planning, Behavioural Finance, and Advanced Management Accounting. She holds a BBA in Accounting (Special) first-class and an MSc in Management (Specialized in Finance) and is a CIMA passed finalist. Further she has completed a Diploma in Enterprise Resource Planning in University of Kelaniya.

N.K.L. Silva

Ms. Nilanthige Kaushalya Lakmali Silva is a Lecturer at the Department of Accountancy, University of Kelaniya. She teaches Management, Economics, Human Resource Management, Marketing Management, Strategic Management and Information Management. Ms. Silva holds a B.B.Mgt. (Special) Degree in Accountancy with a First-Class Honours and an M.Sc. in Management with a Merit. Her research interests include major areas of Accounting and Finance, with a particular focus on Sri Lanka’s Capital Markets, Micro and Macro Economic Environment, Corporate Governance, and Corporate Fraud. She has published several research papers in academic journals and conference proceedings. She is a CMA Sri Lanka Passed Finalist and has completed the Diploma in Banking and Finance at the Institute of Bankers of Sri Lanka.

References

Berrett, D. (2012, February 19). How “flipping” the classroom can improve the traditional lecture. Chronicle of Higher Education. https://www.chronicle.com/article/how-flipping-the-classroom-can-improve-the-traditional-lecture/130857

Gerstein, J. (2012, May 15). Flipped classroom: The full picture for higher education. User Generated Education. https://usergeneratededucation.wordpress.com/2012/05/15/flipped-classroom-the-full-picture-for-higher-education/

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July 2, 2025
A Values-Based Approach to Using Gen AI – Faculty Focus

As a learning designer in a centralized teaching and learning unit, it’s my job to explore new technologies, particularly AI. But I’ll admit, I didn’t jump right in. As Generative AI (GenAI, a subset of AI that can produce content, ideas, and data by learning from existing data and patterns) has become prevalent, so have a wide range of concerns about its usage: authenticity, critical thinking, bias, representation, plagiarism, and sustainability, to name a few.

For a while, I felt paralyzed. How am I supposed to make decisions about this emerging technology that I don’t fully understand? But scholars like Maha Bali reminded me that we need to engage with AI in order to discuss its implications and influence its outcomes. As leaders, educators, users, and creators, we have choices. So, here’s how I have been thinking through when and how I’m going to use GenAI in a way that aligns with my values.

I value originality.

I create original work as a learning designer, as well as personally as a writer and artist, and I don’t want GenAI to train on my work. If I use GenAI, I will use a proprietary tool from my university (e.g., CoPilot), a tool with a paid subscription (like ChatGPT Plus), or another tool that won’t use my work.

I value transparency.

Working in digital learning, I am a partner on academic content. I respect my instructors’ hard-earned expertise and original work, and I won’t use their work with GenAI tools without their permission. In addition, if instructors’ content appears on platforms that use GenAI, I will inform them where and how it is used. As GenAI use increases in our course development processes, I will discuss the advantages and disadvantages of using specific tools, and we will work together to decide whether and how GenAI will be applied.

I value collaboration.

I work with amazing instructors to create online courses and other digital learning experiences. With a team of experts, I guide instructors through the process of brainstorming, outlining, and developing academic materials that we organize into a guided, accessible experience. My teammates and I bring a broad range of skills to this complex work, and we collaborate to create unique and valuable learning experiences. GenAI can help us with parts of this process, but I won’t use GenAI to replace our work with material that lacks the rich human experience and expertise that informs effective teaching and learning.

I value scholarship.

Higher education centers on the exchange, synthesis, and development of ideas. We build on others’ work while crediting them for their contributions. We do this to support our arguments, demonstrate our scholarship, and contribute to an ongoing conversation. While I can use GenAI for research, I can’t depend on it to accurately quote or cite others. Therefore, I won’t assume what GenAI writes or cites is accurate, and I will do my own research. In addition, if I use AI in my work (or in collaborative work), I will cite it.

I value sustainability.

Estimates vary on how much energy GenAI uses, and it depends on what you’re using it for. We do know that simple text queries don’t use as much energy as generating images or video requires. Is it worth using GenAI to create an image of your dog as an astronaut, or a dress composed of hundreds of kittens? As much as I love cute animals, I will minimize using GenAI to create images or videos, particularly for nonessential tasks. Additionally, I will weigh the impact of saving significant time and energy on essential tasks against the potential sustainability costs.

I value critical thinking.

I don’t want the easy answer. I want the complexities, the nuance, the human experience that makes an article or study or creative work unique. I won’t rely on GenAI to create something simplistic, biased, or inaccurate. If I use GenAI, I will use it to generate ideas, answer simple questions, or create an initial outline or template. From there, I will edit and rewrite what it provides, checking for bias, representation, and accuracy. Further, I will advise instructors on how to guide their learners in taking a similar approach.

I’m far from an expert in GenAI, and it’s a moving target. But deciding how I will engage with it has given me some peace of mind in a chaotic, ever-changing world. My best wishes on your own AI journey.

Heather Hans, MLIS is a senior learning designer at Duke University. She is energized by learner-centered design, good UX, and expanding access. She enjoys travel, wildlife gardening, and pie.

References

Bali, M. (2024, June 16). What Can We Refuse in AI? Reflecting Allowed. https://blog.mahabali.me/pedagogy/critical-pedagogy/what-can-we-refuse-in-ai/

Hillier, M. (2023, February 20). Why does ChatGPT generate fake references? TECHE. https://teche.mq.edu.au/2023/02/why-does-chatgpt-generate-fake-references/

Brown University Library. (2025, February 5). Generative Artificial Intelligence: Citation and Attribution with AI Tools. LibGuides at Brown University. https://libguides.brown.edu/c.php?g=1338928&p=9868287

Nicoletti, L., & Bass, D. (2023, June 9). Humans are biased. Generative AI is even worse. Bloomberg.com. https://www.bloomberg.com/graphics/2023-generative-ai-bias/

Duke Learning Innovation & Lifetime Education. (2024, August 12). Generative AI and Teaching at Duke. Duke Learning Innovation & Lifetime Education. https://lile.duke.edu/ai-and-teaching-at-duke-2/

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June 11, 2025
Reviving Engagement in the Spanish Classroom: A Musical Challenge with ChatGPT – Faculty Focus
Halfway through the semester, it’s not uncommon to notice a shift in your students’ energy levels (Baghurst and Kelley, 2013; Kumari et al., 2021). The initial enthusiasm for learning a foreign language may wane as other courses with demanding assignments compete for their attention. Some students prioritize subjects they perceive as more directly tied to their major or career, while others simply feel the weight of mid-semester exhaustion. In the spring, the long winter months can add to this fatigue, making it even harder to keep students engaged (Rohan and Sigmon, 2000).

This is the moment when a language instructor must pivot, shifting the classroom dynamic to reignite curiosity and motivation. Although instructors strive to incorporate activities that cater to the five preferred learning styles (Felder and Henriques, 1995)—visual (learning through images and spatial understanding), auditory (learning through listening and discussion), reading/writing (learning through text-based interaction), kinesthetic (learning through movement and hands-on activities), and multimodal (a combination of multiple styles)—it is beneficial to intersperse these well-structured, and, after a while, predictable classes with activities that break the mold. Introducing something unexpected and different from the established classroom dynamics can reenergize students, foster creativity, and enhance their enthusiasm for learning.

Music, in particular, has long been an ally of instructors teaching a second language (L2)—a language learned after one’s native tongue—especially since the field transitioned toward a more communicative approach. Rooted in interaction and real-world application, the communicative approach prioritizes meaningful engagement over rote memorization, helping students develop fluency in natural, immersive ways. Research has consistently highlighted the benefits of music in L2 acquisition, from improving pronunciation and listening skills to enhancing vocabulary retention and cultural understanding (Degrave, 2019; Kumar et al. 2022; Nuessel and Marshall, 2008; Vidal and Nordgren, 2024).

Building on this tradition, the activity we will share here not only incorporates music but also integrates artificial intelligence, adding a new layer of engagement and critical thinking. By using AI as a tool in the learning process, students not only familiarize themselves with its capabilities but also develop the ability to critically evaluate the content it generates. This approach encourages them to reflect on language, meaning, and interpretation while engaging in text analysis, creative writing, public speaking, and gamification—all within an interactive, culturally rich framework.

Activity Description: Musical Challenge with ChatGPT: “Sing and Discover”

Objective:

Students will improve their listening comprehension and written production in Spanish by analyzing and recreating song lyrics with the help of ChatGPT. While the instructions are presented here in English, the activity should be conducted in the target language—whether Spanish or another language being taught.

Instructions:

1. Listen and Decode
- Divide the class into groups of 2-3 students.
- Choose a song in Spanish (e.g., La Llorona by Chavela Vargas, Oye Cómo Va by Tito Puente, Vivir Mi Vida by Marc Anthony).
- Provide each group with an incomplete version of the lyrics with missing words.
- Students listen to the song and fill in the blanks.
2. Interpret and Discuss
- Within their groups, students analyze the song’s meaning.
- They discuss what they think the lyrics convey, including emotions, themes, and any cultural references they recognize.
  
  Each group shares their interpretation with the class.
  
  What do you think the song is trying to communicate?
  
  Which emotions or feelings do the lyrics evoke for you?
  
  Can you identify any cultural references in the song? How do they shape its meaning?
  
  How does the music (melody, rhythm, etc.) influence your interpretation of the lyrics?
3. Compare with ChatGPT
- After forming their own analysis, students ask ChatGPT:
  
  What do you think the song is trying to communicate?
  
  Which emotions or feelings do the lyrics evoke for you?
- They compare ChatGPT’s interpretation with their own ideas and discuss similarities or differences.
4. Create Your Own Verse
- Each group writes a new verse that matches the song’s style and rhythm.
- They may ask ChatGPT for assistance: “Help us write a new verse for this song in the same style.”
5. Perform and Sing
- Each group presents their new verse to the class.
- If they feel comfortable, they can sing it using the original melody.
- It is beneficial for the professor to have a karaoke (instrumental) version of the song available so that students’ lyrics can be heard clearly.
- Displaying the new lyrics on a monitor or projector allows other students to follow along and sing together, enhancing the collective experience.
6. Election – The Grammy Goes To
Students vote for different categories, including:
- Best Adaptation
- Best Reflection
- Best Performance
- Best Attitude
- Best Collaboration
7. Final Reflection
- What was the most challenging part of understanding the lyrics?
- How did ChatGPT help interpret the song?
- What new words or expressions did you learn?
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June 6, 2025
What Can College Instructors Offer Their Students in the Age of AI? – Faculty Focus

The Age of AI is Upon Us.

Generative AI is changing the landscape of higher education, in both good and bad ways (Balch, 2023). In a world where AI skills and fluency will be necessary and marketable, colleges and universities have made efforts to embrace AI in the classroom (e.g., Balch & Blanck, 2025; Butulis, 2023; Parks & Oslick, 2024) and to provide their students with instruction and practice in using AI in productive and ethical ways (e.g., Schoeder, 2024). As the capacity of AI grows to complete increasingly complex tasks, we (as college instructors) may wonder what we can offer our students in the age of AI. Microsoft co-founder Bill Gates recently stated in an interview that advances in AI will mean the humans will no longer be needed “for most things,” and stated that doctors and teachers in particular could be replaced by AI (CNBC, 2025). Microsoft AI CEO Mustafa Suleyman stated the AI, because it will have the ability to complete tasks faster and more reliably than human workers, will change occupations broadly and will have a “hugely destabilizing” impact on the occupational landscape. Suleyman further stated that the fundamental purpose of AI is to be labor replacing (CNBC, 2025).

In higher education, we see our students use AI in many ways, to provide both authorized and unauthorized aid in their completion of assignments. We have crafted AI policies to help our students understand how AI is and is not permitted in our classes, and some of us have devoted energy to try to detect and police AI use in our classes. Given this reality in which AI can provide and synthesize information for and to our students at their requests in seconds, it is not completely paranoid to ask the question, “What can we, as college instructors, offer our students in the age of AI?”

Why College Instructors Matter: A Student’s Perspective

I had a conversation with one of my students recently about this exact question. He visited my office and in the course of our conversation he asked me how I thought I would use AI as a college instructor moving forward. I admit that I did not have the most thoughtful or eloquent answer as I discussed trying to keep up with advances, to recognize the utility of AI, but also to continue to foster critical thinking skills in my students. He told me that he uses ChatGPT all the time (and he is not alone among students in doing so; Kichizo Terry, 2023). He told me how quick and convenient it is. He surprised me, though, by telling me that he uses ChatGPT despite thinking that it would create “brain rot” in him and other students because it was doing their thinking for them. He then gave me the answer about what we can offer our students. He said that college instructors are not needed to give information to their students, at least not the foundations, definitions, etc., that comprise of a lot of traditional lecturing. He said that students could read much of the content off our PowerPoint slides and in the assigned readings without AI. What college instructors are needed for, he said, is to motivate our students to learn. We are needed to inspire students to come to class, to ask questions, to work out the answers with them. We are needed to engage them and to help them develop curiosity and critical thinking skills to offset their potential AI-induced brain rot. He said that students have had access to the information we teach prior to AI. They could always find and read the content on their own. What we can do as instructors is inspire them to learn the content, to ask their own questions, and to perhaps motivate their AI use to serve their own curiosity beyond the conversations in our classes.

Our Role as Instructors in the Age of AI

This is our role as instructors in the age of AI. This was our role as instructors prior to the advent of AI. As instructors, our role is not just to provide access to content. We cannot compete with the other resources available to our students in our fundamental content knowledge. Our role is to excite our students about the content. Our role is to inspire our students to learn that content. Our role is to bring PEACE to our classes so that our students will see the value in our classes and will engage in our classes to deepen their curiosity and their learning. PEACE is an acronym that stands for Preparation, Expertise, Authenticity, Caring, and Engagement (Saucier, 2019; Saucier, 2022; Saucier, Jones, Schiffer, & Renken, 2022). Beginning on the first days of our classes (Saucier, 2020; Saucier, Renken, Fulton, & Schiffer, 2024), we can demonstrate to our students that we have a plan, that we have content knowledge, that we are real living human beings with relatable thoughts and emotions, that we care about our students and their learning, and that we are enthusiastic and invested in the content we will learn with them. We can nurture our students’ intrinsic motivation to learn the content through demonstrations of our own engagement, activating the process of trickle-down engagement by which our own engagement as instructors promotes our students’ engagement and their subsequent learning (Saucier, Miller, Martens, & Jones, 2022). We can cue our engagement in the content by intentionally and explicitly sharing our own enthusiasm about the content and its value and importance (Saucier, Jones, Miller, Schiffer, Mills, & Renken, 2025).

AI is here. It is here to stay. It is a valuable tool that can accomplish important tasks quickly. Our students recognize its value and are already using it in many ways, both in and out of our classes. As college instructors, we are best served in providing our students with something that AI is not yet able to – our authentic investment in the learning, experiences, and success of our students. We have the ability to inspire our students’ wonder and curiosity in ways that will inspire them to be intrinsically motivated to learn and to keep learning. We should embrace this role as we teach in the age of AI.

Donald A. Saucier, Ph.D. (2001, University of Vermont) is a University Distinguished Teaching Scholar and Professor of Psychological Sciences at Kansas State University. Saucier has published more than 100 peer-reviewed journal articles and is a Fellow of the Society for Personality and Social Psychology, the Society for the Psychological Study of Social Issues, the Society for Experimental Social Psychology, and the Midwestern Psychological Association. His awards and honors include the University Distinguished Faculty Award for Mentoring of Undergraduate Students in Research, the Presidential Award for Excellence in Undergraduate Teaching, and the Society for the Psychological Study of Social Issues Teaching Resource Prize. Saucier is also the Faculty Associate Director of the Teaching and Learning Center at Kansas State University and offers a YouTube channel called “Engage the Sage” that describes his teaching philosophy, practices, and experiences.

References

Balch, D. E. (2023, August 25^th). Artificial intelligence: The rise of ChatGPT and its implications. Faculty Focus. https://www.facultyfocus.com/articles/teaching-with-technology-articles/artificial-intelligence-the-rise-of-chatgpt-and-its-implications/

Balch, D. E., & Blanck, R. (2025, March 31^st). AI-powered teaching: Practical tools for community college faculty. Faculty Focus. https://www.facultyfocus.com/articles/teaching-with-technology-articles/ai-powered-teaching-practical-tools-for-community-college-faculty/

Butulis, M. (2023, December 6^th). Embracing artificial intelligence in the classroom. Faculty Focus. https://www.facultyfocus.com/articles/teaching-with-technology-articles/embracing-artificial-intelligence-in-the-classroom/

CNBC (2025). “Bill Gates: Within 10 years, AI will replace many doctors and teachers—humans won’t be needed ‘for most things’.” Published March 26, 2025.

Kichizio Terry, O. (2023, May 12^th). I’m a student. You have no idea how much we’re using ChatGPT. Chronicles of Higher Education. https://www.chronicle.com/article/im-a-student-you-have-no-idea-how-much-were-using-chatgpt

Parks, M., & Oslick, M. E. (2024, May 22^nd). Empowering student learning: Navigating artificial intelligence in the college classroom. Faculty Focus. https://www.facultyfocus.com/articles/teaching-with-technology-articles/empowering-student-learning-navigating-artificial-intelligence-in-the-college-classroom/

Saucier, D. A. (2019, September 9^th). Bringing PEACE to the classroom. Faculty Focus. https://www.facultyfocus.com/articles/philosophy-of-teaching/bringing-peace-to-the-classroom/

Saucier, D. A. (2020). Rocking your first day of class (and beyond!). E-xcellence in Teaching, Society for the Teaching of Psychology. Retrieved from: https://teachpsych.org/E-xcellence-in-Teaching-Blog/8454525

Saucier, D. A. (2022, February 23^rd). Bringing PEACE to support all students. Inside Higher Ed. Retrieved from: https://www.insidehighered.com/views/2022/02/23/professors-should-learn-about-respond-students-unique-experiences-opinion

Saucier, D. A., Jones, T. L., Miller, S. S., Schiffer, A. A., Mills, H. D., & Renken, N. D. (2025). Cueing engagement: Applying the trickle-down engagement model to instructors’ in-class behaviors. Teaching of Psychology, 52(1), 45-52.

Saucier, D. A., Jones, T. L., Schiffer, A. A., & Renken, N. D. (2022). The empathetic course design perspective. Applied Economics Teaching Resources, 4(4), 101-111.

Saucier, D. A., Miller, S. S., Martens, A. L., & Jones, T. L. (2022). Trickle down engagement: Effects of perceived teacher and student engagement on learning outcomes. International Journal of Teaching and Learning in Higher Education, 33(2), 168-179.

Saucier, D. A., Renken, N. D., Fulton, C. E., & Schiffer, A. A. (2024, August 26^th). Making memories on the first day of class. Faculty Focus. https://www.facultyfocus.com/teaching-strategies/making-memories-on-the-first-day-of-class/

Schoeder, R. (2024, July 31^st). Our responsibility to teach AI to students. Insider Higher Ed. https://www.insidehighered.com/opinion/blogs/online-trending-now/2024/07/31/our-responsibility-teach-ai-students

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May 12, 2025
AI as an Educational Ally: Innovative Strategies for Classroom Integration – Faculty Focus
Since the public release of ChatGPT in December 2022, educators have faced the challenge of effectively integrating artificial intelligence (AI) into their teaching. Rather than simply acknowledging that students are using AI, we should create opportunities for them to explore practical strategies. This approach will help students better understand and utilize AI as an educational ally, enabling innovative methods for effective classroom integration. The key question is: how can we transform AI from a potential source of plagiarism into a valuable educational resource?

Let’s confront the reality: students are using AI. According to a recent survey by Anthology (2023), 60% of students in the US have used AI tools, with 10% reporting weekly use 38% using them monthly. Instead of fearing AI, we should actively explore its potential in the classroom, emphasizing how it can enrich the learning experience.

Strategic Approaches to AI Integration

One effective strategy is to intentionally redesign classroom activities and assignments to incorporate AI tools. This allows educators to gain insights from students’ interactions with these technologies, fostering a deeper understanding of their applications and promoting ethical use. Here is one example from an AI reflective assignment that I tried out in my classes, followed by some other actionable strategies you may want to try out.

In a junior-level education course, I assigned students the task of writing a reflective paper on the various uses of AI tools, such as ChatGPT, in the classroom. My intent was to encourage them to connect these technologies to broader ethical concerns within our field, particularly around plagiarism, drawing from their experiences as students and their emerging roles as future educators. The goal was to prompt deep reflection on AI’s implications, not just for themselves but for the future of education across disciplines.

To scaffold their analysis, I provided a couple of foundational readings on AI, alongside an article of their choosing, see Roose, 2023 and Gates, 2023 citations. This approach allowed them to contextualize their insights within the landscape of their respective fields, examining the potential benefits and ethical considerations of AI usage, as well as strategies for monitoring its impact and the implications of banning such technologies in educational settings.

Their reflections revealed several critical themes. Students emphasized the importance of creatively integrating AI into the classroom. As educators, we should consider it an enrichment tool rather than a replacement for traditional learning. This aligns with findings from the literature, which emphasize that by intentionally integrating AI-powered learning tools, we can highlight best practices for student engagement with these technologies (Johnson, Adams Becker, & Cummins, 2022). In this context, AI serves as a companion that guides students in their tasks, enhancing their critical thinking and problem-solving skills.

Some students expressed recognition that AI’s presence in education is inevitable; if they did not leverage these tools, their students would likely use them anyway. One student articulated a proactive stance, stating the importance of “find[ing] clever ways to incorporate technology into [student] work.” This highlights a shift in mindset—moving from fear of AI to embracing its potential to enhance learning experiences.

Another key insight was the broader applicability of AI in future classrooms. One student posited that AI could “extend and enrich student learning by assisting in generating ideas, discussion points, and encouraging critical thinking.” This perspective reflects the notion that when properly integrated, technology can serve as a catalyst for deeper engagement and understanding (Cooper, 2023). Moreover, recent recommendations highlight that AI can help personalize learning experiences, catering to individual student needs, and thereby improving educational outcomes (U.S. Department of Education, 2023).

Additionally, several students emphasized the responsibility of educators to prepare students for real-world applications of AI. One student summarized this sentiment powerfully: “If used properly, AI can elevate the education students receive and prepare them for a world where its use will be commonplace.” This statement underscores the urgency of equipping future educators with the skills to integrate AI thoughtfully and ethically into their teaching practices, transforming their practice by utilizing AI in novel ways (García-Peñalvo & Ramos, 2023).

Implications for Faculty

To implement a similar reflective approach in your own courses, consider the following strategies:
1. Facilitate Critical Discussions: Begin by assigning readings that frame the conversation around AI and its ethical implications in your particular field. Encourage students to select supplemental articles relevant to their fields to foster interdisciplinary connections, allowing for both autonomy and current insights in the field. AI is so new that the landscape of our knowledge is changing constantly.
1. Encourage Reflective Writing: Ask students to write reflective papers that analyze the impact of AI tools on their discipline. Prompt them to explore both benefits and ethical considerations, allowing for a nuanced understanding of the topic.
1. Create Collaborative Learning Opportunities: Consider group projects where students can share their insights and strategies for incorporating AI. This can lead to a richer dialogue and diverse perspectives on AI integration.
1. Highlight Real-World Applications: Emphasize the relevance of AI skills in their future careers. Discuss potential scenarios where they might utilize AI in the university classroom, preparing them for the challenges and opportunities ahead.
By focusing on these strategies, faculty can engage students in meaningful exploration of AI, ensuring they are not just consumers of technology, but critical thinkers prepared for a rapidly evolving educational landscape. Further, by centering our teaching practices on critical engagement with AI, we can better prepare our students for a future where these tools are integral to learning and teaching.

Final Reflections

A quote by Soren Kierkegaard resonates deeply in the context of adopting AI in education:

“To be a teacher in the right sense is to be a learner. Instruction begins when you, the teacher, learn from the learner, put yourself in their place so that you may understand what they understand and the way they understand it.”

This perspective highlights the reciprocal nature of learning. By embracing AI, educators can better understand and support their students. Understanding how students interact with AI tools allows teachers to guide ethical usage, ensuring that both educators and learners benefit from these technologies. By stepping into our students’ shoes, we can enhance learning, promote critical thinking, and address ethical concerns through thoughtful integration of AI in our classrooms.

Note: this article used collaboration between the human author and the AI program ChatGPT.

Lisa Delgado Brown, PhD, is a current Assistant Professor of Education at The University of Tampa and the former Middle/Secondary Program Administrator at Saint Leo University where she also served on the Academic Standards Committee. Dr. Delgado Brown teaches literacy courses with a focus on differentiation in the general education classroom.

References

Anthology. (2023). AI in Higher Ed: Hype, Harm, or Help [Whitepaper] Anthology.   https://www.anthology.com/sites/default/files/2023-11/White%20Paper-USA-AI%20in%20Higher%20Ed-Hype%20Harm%20or%20Help-v1_11-23.pdf

Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(4), 444–452. https://doi.org/10.1007/s10956-023-10039-y

García-Peñalvo, F. J., Lorens-Largeo, F., & Vidal, J. (2023). The new reality of education in the face of advances in generative artificial intelligence. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 1–15. https://doi.org/10.5944/ried.27.1.37716 (translation accessed at: https://www.redalyc.org/journal/3314/331475280002/html/ )

Gates, B. (2023, March 21). The Age of AI has Begun. GatesNotes. https://www.gatesnotes.com/The-Age-of-AI-Has-Begun

Johnson, L., Adams Becker, S., & Cummins, M. (2022). Technology outlook for higher education 2022–2027. EDUCAUSE. https://library.educause.edu/-/media/files/library/2022/4/2022hrteachinglearning.pdf?#page=40

U.S. Department of Education. (2023). AI and the future of learning: Insights and recommendations. https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf

Roose, K. (2023, January 12). Don’t Ban ChatGPT in Schools. Teach With It. The New York Times. https://www.straitstimes.com/tech/tech-news/don-t-ban-chatgpt-in-schools-but-teach-with-it
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April 23, 2025

Promoting AI-Enhanced Performance in the Online Classroom – Faculty Focus

With the release of AI on a broad scale and the evolving procedural policies for policing and supporting its use in online higher education classrooms, instructor hesitancy to implement AI in ethical and effectual ways is shared by many. To emphasize, research indicates that curriculum designers and university stakeholders need to provide best-practice examples of how to utilize AI tools to effectively and positively promote the use of AI for students’ advantage (Deroncle-Acosta et al. 2024, 9). Clearly, AI offers many benefits as it can drive efficiency, creativity, and innovation. AI comes in various forms from generative AI to gamification to chatbots to adaptive learning platforms amidst other formats. Due to the sheer volume of AI options, pairing high-impact AI tools with highly desirable outcomes aids in the promotion and implementation of such usage in the online classroom.

Elevating Engagement

Engagement is an important factor driving retention in online classrooms; furthermore, dynamic environments capture the attention of students, ensuring greater dedication to learning. AI can considerably improve engagement in the classroom (A. Huang et al. 2023, 11). One way that online instructors can use AI in the classroom is to become a digital master and use generative AI, such as ChatGPT, to develop deeper content ideas or analyze student contributions within discussion (Mora and Semingson 2023, 57). Such tailored discussions add depth and rigor to courses, captivating students and bringing forth relevant and dynamic topics.

Furthermore, a second way to further improve engagement is through the development of AI developed feedback for formative assessments (Perry 2023, 78). Timely and personalized feedback plays an essential role in engaging students and motivating them (Wang and Lehman 2021, 571); AI can aid in streamlining and fast-tracking feedback. In deeply engaging students in an immersive and individualized way, students are more motivated to learn and more satisfied with educational outcomes.

Finally, while generative AI can offer just-in-time support to students, it also simulates a social presence, which is a “crucial component in technology-rich learning environments” (X. Huang et al. 2023, 396). Considered as a study companion, generative AI provides direct and immediate assistance and support, reducing anxiety and improving student motivation and psychological and personal contentment (Luan et al. 2024, 6). Ultimately, AI as a guide to both instructors and students can aid in boosting wholesale engagement in the online classroom.

Prompting Productivity

Another satisfactory outcome regarding the use of AI involves student productivity. Research notes, “By leveraging AI-driven solutions, students can streamline mundane tasks, optimize time management, and achieve higher levels of performance and academic excellence” (Capinding and Dumayas 2024, 647). With AI readily available to aid in the completion of so many activities, it behooves instructors to promote the ethical and practical use of applicable AI tools. For instance, a productivity tool for aiding in the completion of schoolwork is Quillbot, an AI tool on steroids; this one-stop-shop program paraphrases, translates, corrects grammar, and generates citations. Such a tool also ensures more accuracy in terms of performance.

Additionally, an entertaining and useful tool in maximizing time management is the gamified timer app called Forest. With this app, you grow a digital and real-tree forest based on the ability to focus on one’s work for extended clocked times, thus avoiding the distractions of one’s phone. While this may seem like a novel suggestion, its need for implementation is real and underused. In one study based on 106 college students with ADHD, achievement was negatively associated with the sound mode of cell phone; turning off the phone substantially improved accuracy and achievement in quantifiable ways (Albert et al 2023, 1192). Used wisely, AI can boost productivity for students, allowing students to earn higher grades while leaving them more time for the creativity and critical thinking required of top-performing students.

Incorporating Inclusivity

A final desired outcome associated with AI tools is the promotion of inclusivity and accessibility in the online classroom. More than 1 billion people across the world have disabilities and AI optimizes accessibility, inclusion, and equity, thus ensuring fairer access to educational information of all types (Nacheva 2025, 137). A top AI tool for accessibility is Otterai; this transcription service provides captions for recordings and videos. Transcriptions ease and enable learning for many students with disabilities. Likewise, translation AI tools, such as Quillbot or Google Translate, aid English Language Learner (ELL) students. Similarly, Seeing AI from Microsoft is a free app that identifies currency, objects, text, and people for people with visual impairments. Not only is AI valuable for students with disabilities, facilitators can also use it to enhance instruction regarding accessibility. For instance, AI can be used to create visuals for students. Canva has a Dream Lab feature that will generate images. Meeting the dual coding needs of students with audio-visual processing requirements can also improve accessibility while adding depth and engagement to one’s classroom. Using and offering ethical ways to use AI tools benefits student experiences while increasing the impact of instructors.

Conclusion

As instructors, we are curators of learning resources, and AI tools can aid student engagement, productivity, and accessibility. In promoting AI-driven options that enrich and improve student learning, we position students for success and teach them empowering ways to support their autonomous educational growth. AI stands for Artificial Intelligence, but with the right implementation, it can also stand for Adds Insight; Accelerates Improvements, and Assists Instruction.

AI Tool	Description	Application
ChatGPT	Generative AI that uses natural language processing technology	Human-like conversational assistant helpful in supplying assistance, generating ideas, and organizing content
Quillbot	Multipurpose writing tool: grammar editor, citation generator, paraphraser, translator, AI detector, and plagiarism checker	Task assistant and support system helpful in completing academic tasks
Forest	Gamified timer app	Assists in helping users stay task-focused and avoid chronic phone addiction
Otterai	Transcription service	Supplies transcriptions and captions, aiding students with hearing impairments or processing needs
Google Translate	Multilingual neural machine translation service	Aids in translating languages through both inserted text and images; helpful for ELL students
Seeing AI	Camera world setting narrator	Helpful for people with vision impairments in describing the world as seen through the camera lens
Canva – Dream Lab	Image generator	Creates visual aids

Amy Winger is an online instructor for the University of Phoenix and American InterContinental University. She holds a BA in English from the University of Iowa and a MEd in English Education from the University of Minnesota. For over 19 years, she has taught English and general education courses and enjoys pioneering the use of tech tools. Prior to that, she taught English at the secondary level. Her academic research primarily focuses on retention strategies, technology tools, and social media implementation in the online classroom. She is also a freelance fiction writer.

References

Albert, Gila, Shimon Fridkin, and Or Delevski. 2023. “Mobile Phone Distraction and Its Effects on Academic Performance of Israeli College Students.” Israel Affairs 29 (6): 1181–99. doi:10.1080/13537121.2023.2257472.

Capinding, Andie Tangonan and Franklin Tubeje Dumayas. 2024. “Transformative Pedagogy in the Digital Age: Unraveling the Impact of Artificial Intelligence on Higher Education Students.” Problems of Education in the 21st Century 82 (5): 630–57. https://research.ebsco.com/linkprocessor/plink?id=c8d24236-63fc-3796-b8c5-bc4134816fad.

Deroncele-Acosta, Angel, Omar Bellido-Valdiviezo, María de los Ángeles Sánchez-Trujillo, Madeleine Lourdes Palacios-Núñez, Hernán Rueda-Garcés, and José Gregorio Brito-Garcías. 2024. “Ten Essential Pillars in Artificial Intelligence for University Science Education: A Scoping Review.” SAGE Open 14 (3). https://research.ebsco.com/linkprocessor/plink?id=2ab6bfc4-e5ec-33d7-a5d5-d7a6f9747bfb.

Huang, Anna Y.Q., Owen H.T. Lu, and Stephen J.H. Yang. 2023. “Effects of Artificial Intelligence–Enabled Personalized Recommendations on Learners’ Learning Engagement, Motivation, and Outcomes in a Flipped Classroom.” Computers & Education 194 (March): N.PAG. doi:10.1016/j.compedu.2022.104684.

Huang, Xiaoshan, Alejandra Ruiz-Segura, Chengyi Tan, Tingting Wang, Robin Sharma, and Susanne P. Lajoie. 2023. “Social Presence in Technology-Rich Learning Environments: How Real We Are Feeling Connected and How Does It Matter for Learning?” Information & Learning Science 124 (11/12): 396–424. doi:10.1108/ILS-04-2023-0034.

Luan, Lingfei, Xi Lin, Yan Dai, Shu Hu, and Qianlu Sun. 2024. “Exploring the Cognitive Dynamics of Artificial Intelligence in the Post-COVID-19 and Learning 3.0 Era: A Case Study of ChatGPT.” Asian Journal of Distance Education 19 (2): 1–10. https://research.ebsco.com/linkprocessor/plink?id=5e5adf38-08c7-317f-875c-5a3740249029.

Mora, Raúl Alberto, and Peggy Semingson. 2023. “AI and Literacy Education: Consider the Challenges, Embrace the Possibilities, and Make Your Classroom Even More Human.” Literacy Today (2411-7862) 41 (1): 54–58. https://research.ebsco.com/linkprocessor/plink?id=448ddec2-8908-3565-8329-f93e8e062486.

Nacheva, Radka. 2025. “Analysis of AI Mobile Applications for Ensuring Digital Accessibility in Higher Education for People with Disabilities.” Acta Educationis Generalis 15 (1): 133–45. doi:10.2478/atd-2025-0009.

Perry, Abby. 2024. “Ai Meets Academia.” Christianity Today 68 (1): 73–92. https://research.ebsco.com/linkprocessor/plink?id=80289ae4-1ab6-32a2-8589-530a7b2a90e2.

Wang, Huanhuan, and James D. Lehman. 2021. “Using Achievement Goal-Based Personalized Motivational Feedback to Enhance Online Learning.” Educational Technology Research and Development 69 (2): 553–81. https://research.ebsco.com/linkprocessor/plink?id=e40d870e-82a9-36ba-b1de-217bd2d657cb.

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April 9, 2025

AI-Powered Teaching: Practical Tools for Community College Faculty – Faculty Focus
Artificial intelligence (AI) has transitioned from a speculative concept to a transformative tool in higher education, particularly within community colleges. This article explores AI’s historical evolution, critically assesses its benefits and challenges for teaching, and provides evidence-based strategies for faculty to integrate AI effectively. Drawing on the scholarship of teaching and learning (SoTL), it argues that AI can enhance accessibility and efficiency while preserving the human essence of education. A case study from a California community college illustrates these principles in action. Faculty developers and instructors can use this framework to harness AI’s potential, ensuring it supports rather than supplants their pedagogical roles.

Introduction

In Ayad Akhtar’s 2023 play McNeal, ChatGPT performs alongside Robert Downey Jr., a theatrical milestone reflecting artificial intelligence’s (AI) encroachment into domains once deemed uniquely human (Akhtar, 2023, as cited in “From Čapek to ChatGPT”). This echoes Karel Čapek’s R.U.R. (Rossum’s Universal Robots), where artificial beings, created to serve, ultimately undo their creators (Čapek, 1920/2004). A century later, AI is no longer fiction but a dynamic force in community college education, reshaping how faculty teach, and students learn. For instructors serving diverse, often underserved populations, AI raises critical questions: How has it evolved into a pedagogical tool? What are its merits and limitations? How can it enhance teaching without diminishing faculty agency?

This article addresses these questions through a three-part exploration: tracing AI’s historical development, critically evaluating its role in community college classrooms, and offering practical, evidence-based strategies for faculty. Grounded in the scholarship of teaching and learning (SoTL), it expands on prior work (e.g., Davidson, 2021; Pritts, 2023) to position AI as a partner in faculty development. A case study illustrates these principles in practice, aligning with Faculty Focus’s mission to improve teaching and student success in higher education.

Historical Context: AI’s Evolution and Educational Implications

AI’s journey from myth to modernity informs its current educational applications. Ancient tales of Talos, a bronze automaton guarding Europa, and Pygmalion’s animated sculpture reveal humanity’s early fascination with artificial life (Hamilton, 1942). By the 3rd century BC, Greek inventors like Archytas built the steam-powered Flying Pigeon, an early self-operating device (Berryman, 2003). The 18th-century Jaquet-Droz automata—mechanical dolls mimicking human actions—furthered this vision (Riskin, 2016). Philosophers like Descartes and Leibniz speculated on machine cognition, while 19th-century pioneers Babbage and Lovelace laid computing’s foundations (Copeland, 2012).

The modern AI field emerged in 1950 when Alan Turing posed, “Can machines think?” (Turing, 1950), followed by John McCarthy’s naming of “artificial intelligence” (McCarthy, 2007). Early systems like MYCIN, which diagnosed infections using rule-based logic, showcased potential but lacked adaptability (Buchanan & Shortliffe, 1984). The 1990s introduced machine learning, enabling AI to learn from data—email spam filters improved iteratively, marking a shift from static programming (Mitchell, 1997). The 2010s brought deep learning, with neural networks emulating human cognition; Google’s AlphaGo defeated Go champion Lee Sedol in 2016, devising strategies its creators couldn’t predict (Silver et al., 2016).

Since 2020, generative AI—exemplified by OpenAI’s GPT-3 and ChatGPT—has produced human-like text, transforming fields from healthcare to education (Spitale et al., 2023; Topol, 2019). In classrooms, AI’s trajectory is evident: 1980s grading software evolved into 2020s virtual tutors, shifting from peripheral aids to central tools (Baylor & Ryu, 2003). For community college faculty, this history contextualizes AI’s rapid ascent, highlighting its capacity to augment teaching—yet it also underscores the need for critical oversight, a theme explored next.

AI’s integration into community colleges offers transformative potential but demands scrutiny, particularly given the sector’s diverse student body—often first-generation, working adults, or developmental learners (Cohen et al., 2014).

Benefits: Accessibility and Faculty Efficiency
AI enhances accessibility, a cornerstone of community college missions. Hybrid and HyFlex models, supported by AI-driven platforms like Zoom, allow asynchronous learning, vital for students balancing work and family (Quality Matters, 2022). A 2022 report documented a 220% surge in preference for online/hybrid courses (from 9% in 2020 to 29% in 2022), reflecting AI’s role in broadening access (Kelly, 2022, as cited in Quality Matters, 2022). Faculty benefit too: automated grading reduces routine burdens, while NLP tools like ChatGPT provide instant student support, amplifying instructors’ reach (Barnes & Noble Education, 2022; Topol, 2019).

Challenges: Engagement and Skill Development
However, AI’s efficacy hinges on student self-regulation, a persistent challenge where developmental courses predominate (Zimmerman, 2002). Virtual settings often lack in-person dynamics—non-verbal cues, spontaneous discussions—potentially weakening engagement (Quality Matters, 2022). Faculty unease is notable: 54% prefer fully in-person instruction, citing discomfort with digital mediation (Barnes & Noble Education, 2022). Overreliance on AI risks undermining critical thinking; Pritts (2023) warns that tools generating papers may erode analytical skills, echoing SoTL calls for active learning (Davidson, 2021).

Ethical Considerations: Equity and Agency
Ethical dilemmas loom large. Algorithmic bias in grading systems can exacerbate inequities, disproportionately affecting marginalized learners (O’Neil, 2016). Access disparities—unreliable internet or devices—threaten equitable implementation (Means et al., 2020). Spitale et al. (2023) highlight AI’s dual edge: it clarifies concepts but also crafts compelling disinformation, posing risks to academic integrity. Without oversight, AI could shift from facilitator to arbiter, diminishing faculty agency—a concern rooted in Čapek’s cautionary tale (1920/2004). Faculty development must address these tensions to ensure AI serves educational goals.

AI and Academic Integrity: Redrawing Assessment
The rise of AI tools like ChatGPT has forced educators to rethink traditional assessment methods. As discussed in Inside Higher Ed (2025), the prevalence of AI-generated content has made it increasingly difficult to distinguish between student work and machine-generated output. This has led to a growing concern over academic integrity, particularly in community colleges where students may lack the resources or support to navigate these challenges effectively. However, rather than viewing AI as a threat to academic honesty, educators can use this moment to redesign assessments that emphasize critical thinking, creativity, and problem-solving—skills that AI cannot easily replicate. For example, instead of traditional essays, instructors might assign reflective portfolios, oral presentations, or collaborative projects that require students to engage deeply with the material and demonstrate their understanding in ways that go beyond what AI can produce. Faculty development programs should focus on equipping instructors with the tools and strategies to design assessments that are both AI-resistant and pedagogically sound, ensuring that students are evaluated on their ability to think critically and apply knowledge, rather than their ability to generate text.

Practical Applications: Strategies for Faculty Development

To harness AI’s benefits while mitigating risks, community college faculty can adopt five evidence-based strategies, each enhancing teaching practice and student success:
1. AI as a Virtual Tutor: NLP models like ChatGPT offer 24/7 support. A developmental math instructor might direct students to ask, “Explain quadratic equations,” receiving tailored responses, freeing class time for conceptual exploration (Topol, 2019). Faculty can train on integrating such tools via workshops, enhancing their tutoring capacity.
1. Hybrid Course Design: AI platforms enable asynchronous lectures, reserving in-person sessions for interaction. A sociology instructor could post AI-generated summaries on social inequality, then facilitate debates, accommodating diverse schedules (Quality Matters, 2022). Faculty development can include HyFlex training to optimize this balance.
1. Creative Exploration: Tools like MidJourney foster innovation. An English instructor might have students generate visual interpretations of Their Eyes Were Watching God, sparking discussions on symbolism (Hutchison & Woodward, 2014). Workshops on AI-driven creativity can empower faculty to adapt this approach.
1. Personalized Feedback: AI tools like Grammarly flag errors, allowing instructors to refine feedback with comments like, “Expand this argument,” blending efficiency with mentorship (Pritts, 2023). Faculty can learn to leverage AI feedback systems through peer mentoring.
1. Redesigning Assessments for AI-Resistance: In light of the challenges posed by AI-generated content, faculty can adopt assessment strategies that prioritize critical thinking and creativity. For example, instead of traditional essays, instructors might assign reflective portfolios, oral presentations, or collaborative projects that require students to engage deeply with the material and demonstrate their understanding in ways that go beyond what AI can produce. Faculty development programs should focus on equipping instructors with the tools and strategies to design assessments that are both AI-resistant and pedagogically sound, ensuring that students are evaluated on their ability to think critically and apply knowledge, rather than their ability to generate text.
At Sacramento City College (SCC), a 2023 pilot integrated AI into developmental English courses. Faculty used ChatGPT as a virtual tutor, assigning students to draft essays and refine them with AI feedback before submission. Instructors then provided final critiques, focusing on argumentation over mechanics. A survey of 50 students found 78% felt more confident in writing, while faculty reported a 30% reduction in grading time (SCC Faculty Development Report, 2023, unpublished). However, 20% of students lacked reliable internet, prompting SCC to expand Wi-Fi access. This case underscores AI’s potential to enhance teaching efficiency and student outcomes, while highlighting equity challenges faculty developers must address.

In response to concerns about AI-generated content, SCC also piloted a new assessment model in which students were required to present their essays orally and engage in peer review sessions. This approach not only reduced the risk of AI-generated submissions but also fostered a deeper understanding of the material through active engagement and collaboration. Faculty reported that students were more invested in the learning process and demonstrated higher levels of critical thinking and creativity in their work.

Conclusion

AI’s evolution—from ancient myths to ChatGPT’s theatrical debut—mirrors humanity’s quest to extend its capabilities. In community colleges, it offers accessibility and efficiency, yet risks eroding the relational core of teaching. Faculty development can bridge this gap by equipping instructors with strategies to integrate AI as a tutor, design tool, creative aid, feedback enhancer, and discussion catalyst. The SCC case study illustrates this balance in practice. As Davidson (2021) and Pritts (2023) argue, the goal is to delegate routine tasks to AI while reserving inspiration and mentorship for faculty—a principle rooted in SoTL. By fostering AI literacy and ethical oversight, faculty developers can ensure AI amplifies, rather than supplants, the human element of education.

Moreover, as the Inside Higher Ed article highlights, the rise of AI-generated content presents an opportunity to rethink assessment practices. By designing assessments that emphasize critical thinking, creativity, and collaboration, faculty can ensure that students are evaluated on their ability to engage deeply with the material, rather than their ability to generate text. This shift not only addresses concerns about academic integrity but also prepares students for a future in which AI is an integral part of the workforce.

David E. Balch, PhD, is a professor at Rio Hondo College and has published articles in the areas of ethics, humor, distance education, and AI.

Robert Blanck, MA, has 35 years’ experience in teaching and administration within the fields of education and business. Blanck earned the Lean Six Sigma Black Belt designation for industrial quality control.

Note: this article used collaboration between the human authors and the AI program Grok (xAI).

References

Barnes & Noble Education. (2022, June 28). College 2030™ report: Higher education’s preparation post-pandemic. Business Wire. https://www.businesswire.com/news/home/20220628005207/en/

Baylor, A. L., & Ryu, J. (2003). The API model: Using AI to enhance learning. Educational Technology Research and Development, 51(4), 89–102. https://doi.org/10.1007/BF02504554

Buchanan, B. G., & Shortliffe, E. H. (1984). Rule-based expert systems: The MYCIN experiments of the Stanford Heuristic Programming Project. Addison-Wesley.

Čapek, K. (2004). R.U.R. (Rossum’s Universal Robots) (C. Novack, Trans.). Penguin Classics. (Original work published 1920)

Davidson, C. N. (2021). The new education: How to revolutionize the university to prepare students for a world in flux. Basic Books.

EDUCAUSE. (2023). AI and academic integrity: Rethinking assessment. https://www.educause.edu

Hutchison, A., & Woodward, L. (2014). A planning cycle for integrating digital technology into literacy instruction. The Reading Teacher, 67(6), 455–464. https://doi.org/10.1002/trtr.1225

McCarthy, J. (2007). What is artificial intelligence? Stanford University. http://jmc.stanford.edu/articles/whatisai/whatisai.pdf

Means, B., Bakia, M., & Murphy, R. (2020). Learning online: What research tells us about whether, when and how. Routledge.

Mitchell, T. M. (1997). Machine learning. McGraw-Hill.

O’Neil, C. (2017). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown. Note: changed the date from 2016 to 2017

Pritts, N. (2023). AI and the future of critical thinking in higher education. Journal of Educational Technology, 40(2), 123–135.

Quality Matters. (2022). 2022 higher education trends report. https://www.qualitymatters.org/research

Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., van den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., Dieleman, S., Grewe, D., Nham, J., Kalchbrenner, N., Sutskever, I., Lillicrap, T., Leach, M., Kavukcuoglu, K., Graepel, T., & Hassabis, D. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587), 484–489. https://doi.org/10.1038/nature16961

Spitale, G., Biller-Andorno, N., & Germani, F. (2023). AI model GPT-3 (dis)informs us better than humans. Science Advances, 9(5), Article eade7823. https://doi.org/10.1126/sciadv.ade7823

Topol, E. J. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.

Turing, A. M. (1950). Computing machinery and intelligence. Mind, 59(236), 433–460. https://doi.org/10.1093/mind/LIX.236.433

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
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March 31, 2025

Tag: teaching with technology

Navigating the Disorienting Dilemma

Step Up Your Thinking Game

Model Critical Thinking

Use AI for Your Benefit

Navigating the Disorienting Dilemma

Step Up Your Thinking Game

Model Critical Thinking

Use AI for Your Benefit

Step 1: Take a critical look at your current syllabus.

Step 2: Consider whether and how students should use AI on the assignments you keep.

Step 3: Carve out time to discuss and model your expectations.

Step 4: Ask students to disclose their AI use, as noted above.

Step 5: If you suspect inappropriate use of AI, don’t accuse students of cheating.

Flipped Classroom 2.0: Enriching the Core Strategy

AI Tools

Microlearning

Learning Analytics

Understanding Student Resistance in the Digital Era

Addressing Fear Through Technology-Supported Safety

Making Learning Visible with Analytics and Scaffolds

Designing Pre-Class Work That Drives In-Class Success

Establishing Routine and Engagement with Focusing Activities

Avoiding Pitfalls in Tech-Enhanced Flipped Classrooms

Toward a Future-Ready Learning Model

I value originality.

I value transparency.

I value collaboration.

I value scholarship.

I value sustainability.

I value critical thinking.

Activity Description: Musical Challenge with ChatGPT: “Sing and Discover”

Objective:

Instructions:

Final Thoughts: Music, AI, and Critical Thinking

The Age of AI is Upon Us.

Why College Instructors Matter: A Student’s Perspective

Our Role as Instructors in the Age of AI

Strategic Approaches to AI Integration

Implications for Faculty

Final Reflections

Elevating Engagement

Prompting Productivity

Incorporating Inclusivity

Conclusion

Introduction

Historical Context: AI’s Evolution and Educational Implications

Practical Applications: Strategies for Faculty Development

Conclusion