Tag: building student engagement

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
Source link
March 31, 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
Source link
March 31, 2025
Supporting Non-Major Biology Students: Making the Classroom YOUnique – Faculty Focus
Supporting biology courses for non-majors involves addressing the diverse needs of students with little intrinsic motivation to study the subject. Many take these courses as part of general education, not personal interest, creating a challenge in maintaining engagement and fostering deeper understanding (Haak et al. 2011). Non-majors often struggle to connect course content to their lives, making it harder to see the subject’s value (Labrov and Singer, 2010). These students come from varied academic backgrounds, resulting in different levels of preparedness and confidence (Tobias 1990; Gormally and Heil 2022). Some may experience anxiety or feel science is irrelevant to their careers (Rice et al. 2013). 

To address these challenges, educators must adopt approaches that make biology accessible and meaningful. By creating a learning environment tailored to various majors, addressing barriers, and demonstrating real-world applications, instructors can make the classroom “YOUnique.” Making the classroom “YOUnique” tailors the experience to individual needs, fostering belonging and showing biology’s relevance. This article explores how strategies—fostering engagement, connecting biology to real-world contexts, and to students’ majors—can support non-major biology students. These strategies will help students build confidence to apply biological knowledge in their careers. 

1. Fostering Engagement in Non-Major Biology Students through a Studio Environment

Engaging students not inherently drawn to biology requires innovative teaching methods. Active learning strategies, where students actively engage in the learning process, promote participation and retention (Freeman et al. 2014). These include group discussions, hands-on experiments, problem-solving activities, and creative assessments that encourage critical thinking and peer collaboration. 

A case study of engagement is the studio-style introductory biology classroom at Kansas State University (Manhattan, KS, USA). This innovative teaching environment blends engaged lectures with hands-on, collaborative activities, with the instructor as a facilitator. The studio integrates lecture, lab, and group work in a flexible learning environment, allowing students to actively participate in problem-solving, discussions, and projects, and it supports diverse learning activities and styles. This approach fosters an interactive environment which is beneficial for student learning. 

Here are some ways the studio-style classroom helps non-major biology students: 
- Active Learning: The classroom setup encourages active engagement, helping non-majors grasp complex biological concepts through hands-on experiences, computer tutorials, and group activities, rather than passive listening. 
- Collaborative Learning: Students work in small groups, promoting peer interaction and problem-solving, which supports non-majors who may feel less confident in their knowledge. 
- Integrated Learning: Combining lecture and lab time allows students to apply theoretical knowledge to practical experiments, helping solidify learning and making complex concepts more understandable. 
- Personalized Attention: The instructor can circulate among groups, providing targeted support and reassurance, which is especially beneficial for non-majors needing more guidance. 
- Flexible Space: The studio classroom’s flexibility to use various technology allows instructors to adapt teaching styles and activities, ensuring responsiveness to the diverse needs of non-major students.
2. Connecting Biology to Real-World Contexts

For non-majors, understanding how biology applies to everyday life is crucial for maintaining interest and motivation. Without a clear connection to their personal or professional lives, students may view biology as abstract or irrelevant. By demonstrating how biological principles impact their world, educators can foster greater engagement. When students recognize the value of what they are learning—whether through daily applications or career relevance—they are more likely to stay motivated, actively participate, and retain information. 

A highly effective way to establish relevance is through interdisciplinary connections that show how biology extends beyond the classroom (Beers and Jensen 2009; Morales and Boulware 2020). Prior to the first day of class, there is a discussion board asking why biology is important to them, and instructors use the responses as an avenue to connect biology and their lives during a class discussion. For every class period, the instructor connects what they are learning to their lives. For instance, using a computer simulation called “Kansas feeds the world” students can explore how photosynthesis and cellular respiration (cell biology unit), along with energy and nutrient dynamics (ecology unit), interconnect with real world issues. In the genetics unit, students connect molecular genetics and biotechnology using an assignment where the students develop a biotechnology product and generate a print ad or video commercial. The ads are shared during class, showcasing how biological processes can drive innovations like medical devices and biofuels. Each unit follows a pattern of building basic knowledge followed by exploring implications and applications to people’s lives.  

Another effective method is case-base active learning (Chaplin 2009; Dewi and Rahayu 2023). Presenting real-world scenarios, like infectious diseases or genetic testing, makes biology come alive. For example, the instructors use a readily available MMR vaccine autism case study to explore the process of science, and let students come to their own conclusions about vaccine efficacy. 

Inviting guest speakers from diverse fields can help students see biology’s broad applications (D’Andrea and Mertens 2006; Marx et al. 2021). For example, we have graduate students presenting on the benefits of “long-term ecological research stations” (LTERs) such as the Konza Prairie Biological Center (Kansas, USA), or the Scientist Spotlights, which is biography about them and their research showing that biologists are real people. These speakers not only provide real-life examples but also inspire students to think critically about how biological knowledge could inform their own career aspirations. Hearing from professionals at the intersection of biology and their disciplines broadens students’ perspectives, reinforcing biology’s fundamental role in life and work.

3. Demonstrating Relevance to Students’ Majors

For non-majors, a significant barrier to success in biology is the perception that the subject lacks relevance to their lives or careers (Gormally and Hall 2022). Students in fields like business, art, or education may struggle to see how topics like cellular respiration or ecology apply to their goals, which can hinder motivation and engagement. 

To address this challenge, educators must emphasize biology’s connections to different majors and to generate connections that have career relevance. Highlighting interdisciplinary applications, such as the role of biology in public health (communications majors), technology (computer science majors), or environmental policy (pollical science majors), can help students appreciate its broad impact. For example, a lesson on climate change might include discussions on the biological effects of carbon emissions, connecting the topic to social and economic issues like the displacement of communities due to rising sea levels and the economic costs of extreme weather events, such as hurricanes and wildfires. 

Another effective approach is personalized assignments (Driessen et al. 2024). Personalized projects allow students to explore biology in ways that resonate with their own lives. One such assignment is a “Biology Connections” activity, where students reflect on how biological concepts connect to their major and career. For example, a business student might describe how ecological sustainability impacts corporate strategies, while an education major might reflect on the importance of understanding human development in teaching practices. This reflection promotes motivation, showing students that biology has practical applications in their daily lives and careers. These personalized assignments allow instructors to make biology “YOUnique”. 

Conclusion

Supporting non-major biology students requires efforts to foster engagement, connect material to real-world contexts, and demonstrate relevance to different majors and backgrounds. Active learning, real-world connections, and ties to their major create a supportive environment where students thrive. By addressing unique challenges and interests, educators can empower non-majors to appreciate biology’s relevance and develop skills beyond the classroom. When students see content as meaningful and tied to their lives and careers, they are more likely to engage, retain knowledge, and apply it. This approach enhances understanding and equips them with critical thinking and problem-solving skills essential in any profession. By “Making the Classroom YOUnique,” educators can foster an environment where students feel valued, leading to greater motivation, academic achievement, and personal growth. A “YOUnique” approach helps students connect with the subject matter and realize their potential as learners in the biology classroom, regardless of their major. 

Jack Sytsma is a doctoral graduate teaching assistant in the Division of Biology at Kansas State University. While his research is at the forefront of understanding how plants respond to climate, Jack is equally passionate about teaching. He finds great fulfillment in educating and mentoring undergraduate students, particularly in courses that bridge ecological principles with real-world applications. With aspirations of becoming a teaching professor in biology, Jack aims to inspire the next generation of scientists by fostering curiosity and a deeper understanding of the subject.

Robert ‘Robbie’ Bear is a Senior Biology Instructor in the Division of Biology at Kansas State University. Robbie started teaching 33 years ago as an undergraduate and ever since then he has synthesized his experiences on either side of the podium into his pedagogy of an inquiry-based student centered learning. He is currently teaching his dream course and finds happiness and purpose in people discovering the importance of Biology in their life. In the remaining years of his career, Robbie wants future educators (the Jack Sytsma’s) to have the foundational pedagogy that allows them to explore, grow, and succeed as teachers.

Eve S. McCulloch, PhD, is a teaching associate professor in the Division of Biology at Kansas State University. Eve has been teaching biology courses for 12 years, ranging from introductory to upper-level classes. Eve’s research background is in mammalogy, ecology, and conservation genetics. She is in her dream job, working to support undergraduate students both in and outside of the classroom. Eve is passionate about making the biological sciences accessible to students of all backgrounds and fields of interest, and promoting undergraduate student success while at university at beyond.

References  

Armstrong, N., and S. M. Chang. “Teaching Non-Majors Biology: Pedagogical Challenges and Opportunities.” Journal of College Science Teaching (2007).

Beers, S. F., and M. Jensen. “Integrating Science and Literacy: Enhancing Understanding of Science Through Interdisciplinary Instruction.” Science Scope 32, no. 2 (2009): 20-27.

Brewer, C. A., and D. Smith. Vision and Change in Undergraduate Biology Education: A Call to Action (2011).

Chaplin, S. “Assessment of the Impact of Case Studies on Student Learning Gains in an Introductory Biology Course.” CBE—Life Sciences Education 8, no. 3 (2009): 297–306.

Cooper, K. M., et al. “The Impact of Active Learning on Retention of Non-Majors in Biology” (2019).

Cotner, S., S. Thompson, and R. Wright. “Do Biology Majors Really Differ from Non–STEM Majors?” CBE—Life Sciences Education 16, no. 3 (2017): ar48.

D’Andrea, M. L., and D. M. Mertens. “Creating Meaningful Connections: The Role of Guest Speakers in the Classroom.” Journal of College Science Teaching 35, no. 1 (2006): 40–45.

Dewi, C.A., and S. Rahayu. “Implementation of Case-Based Learning in Science Education: A Systematic Review” (2023).

Driessen, E. P., K. E. Walker, T. Hallman, A. Casper, S. L. Eddy, J. R. Schneider, and A. K. Lane. “‘It’s Been a Process’: A Multiple Case Study of Biology Instructor Efforts to Reform Their Sex and Gender Curriculum to be More Inclusive of Students with Queer Genders and Intersex Students.” CBE—Life Sciences Education 23, no. 4 (2024): ar51.

Freeman, S., et al. “Active Learning Increases Student Performance in Science, Engineering, and Mathematics.” Proceedings of the National Academy of Sciences 111, no. 23 (2014): 8410–8415.

Gormally, C., and A. Heil. “A Vision for University Biology Education for Non-Science Majors.” CBE—Life Sciences Education 21, no. 4 (2022): es5.

Haak, D. C., J. HilleRisLambers, E. Pitre, and S. Freeman. “Increased Structure and Active Learning Reduce the Achievement Gap in Introductory Biology.” Science 332, no. 6034 (2011): 1213-1216.

Labov, J. B., and S. R. Singer. “Community Colleges in the Evolving STEM Education Landscape” (2010).

Marx, M. A., R. L. Glaser, C. E. Moran, and K. P. Tucker. “A Creative Model for an Interdisciplinary Approach to Service-Learning.” Integrative and Comparative Biology 61, no. 3 (2021): 1028-1038.

Morales, E., and R. Boulware. “A Cross-Disciplinary Approach to Teaching Biology and Environmental Science: The Intersection of Biology and Policy.” Journal of College Science Teaching 49, no. 6 (2020): 40–47.

Rice, L., J. M. Barth, R. E. Guadagno, G. P. Smith, and D. M. McCallum. “The Role of Social Support in Students’ Perceived Abilities and Attitudes Toward Math and Science.” Journal of Youth and Adolescence 42, no. 7 (2013): 1028–1040.

Tobias, S. They’re Not Dumb, They’re Different: Stalking the Second Tier (1990).
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March 12, 2025
Tired of Awkward Silences? Upgrade your Think-Pair-Share – Faculty Focus

I’ve tried a few different techniques for class discussions over the years, some that I’ve written about previously in Faculty Focus. In recent years, I’ve dialed in a 3-step process for discussion in my face-to-face classes, which has helped me create an engaged classroom climate. It’s Think-Pair-Share (TPS), with some upgrades.

I refined my TPS process after attending Jeremy Rentz’s workshop “Put Your Hammer Down” (detailed in the Best of the 2021 Teaching Professor Conference). His key idea was “The person doing the learning is the person doing the work.” I thought about how to get my students to do more “work” in my large lecture-based classes. Although I knew the active learning benefits of a technique like TPS, I struggled to implement it well. There were often too many awkward silences for TPS to be as engaging as I would have liked. After Jeremy’s workshop, I made some upgrades to TPS that invigorated it for students and for me.

Step #1: Think
Upgrade: Discussion Bubbles

Instead of posing my discussion question after I’ve covered the content on my slide, I now put the question in a Discussion Bubble next to the content. Prior to implementing this, I would review the slide and then pose my question, either a specific one, or something general like “anyone have anything to add?” Then there would be the awkward silence while students think, and I would try to be chill. Having a Discussion Bubble primes students to think and be ready to share (in small or large groups) once I’m done reviewing the slide. It not only decreases the awkwardness (which seems to feed off itself), but it also increases small and large group discussion participation.

Sometimes these discussion bubbles include a polling question that I use to record and display students’ opinions (e.g., Do you prefer a, b, or c?). Students can then see that they are not alone in their views and are more confident to share their perspectives in Steps 2 and 3.

Step #2: Pair
Upgrade: 1-Minute Timer

I give students one minute to talk with classmates about their thoughts on the discussion bubble or their answer to the polling question. On the very first day, I tell students that I will use my watch to set a 1-minute timer and that we’ll have a few of these in every class. I believe that these short, reliable segments help students feel safe and avoid too-lengthy, awkward small-talk. At the end of the one-minute paired discussion, I don’t check to see if they need more time as I have large classes, and the level of discussion is variable. In recent course surveys (classes of 90-175 students), about 70% of students wanted to keep these 1-minute discussions and only 13% wanted to change them (some were undecided). Further, about 44% of students agreed that these 1-minute discussions helped them feel more connected to their classmates (42% had mixed or neutral feelings) and 63% said they were comfortable sharing in class. So, it’s not perfect for everyone, but it’s benefiting many students. Also, I don’t have students pair off every time that I have a discussion bubble—sometimes I skip Step 2 and go straight to Step 3.

After Step 1 and maybe 2, I incentivize large group discussion with an extra credit point for sharing aloud. I’ve written previously about my Fired-Up and Ready to Discuss process, which involves giving students up to 1 point each class (and 3-5 points total for the semester) for sharing aloud. I have undergraduate teaching assistants present and poised to enter the student’s point into the gradebook as soon as they say their name and share (and if they forget, they can find the teaching assistants after class). It’s an immediate reward that encourages sharing in a large class. Only about ½ of students in my large classes share aloud and earn Fired-up Points, but in a class of 100 students, getting 50 to talk aloud is enough to create an engaging classroom climate. In recent surveys, 70% of the students want to keep Fired Up (and only about 10% want to change it).

This upgraded TPS not only helps students “do the work,” but it also makes for a fun and engaging class. It gives my lectures a predicable rhythm that creates psychological safety for student engagement. It also helps me stay confident and relaxed, which isomorphically encourages students to relax and take the risk to share their thoughts.

Dr. Ashley Harvey is a professor in the Department of Human Development and Family Studies at Colorado State University (CSU). Since 2007, she has taught more than 10,000 students across 15 different courses in over 150 undergraduate and graduate sections. Dr. Harvey has spoken at TEDx, is a licensed marriage and family therapist, and earlier in her career worked at the CSU Veterinary Teaching Hospital as a grief counselor and educator.

References

Harvey, Ashley. “An activity that promotes engagement with required readings, even in large classes.” Faculty Focus. February 2017. https://www.facultyfocus.com/articles/effective-teaching-strategies/activity-promotes-engagement-required-readings-even-large-classes/

Harvey, Ashley. “Fired up and ready to discuss.” Faculty Focus. February 2020. https://www.facultyfocus.com/articles/effective-classroom-management/fired-up-and-ready-to-discuss/

Rentz, Jeremy. “Put the hammer down and build your teaching toolbox.” The Best of the 2021 Teaching Professor Conference. October 2021. https://www.magnapubs.com/wp-content/uploads/2021/10/free-report-Best-of-TPC-2021-opt.pdf

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March 10, 2025
Tired of Awkward Silences? Upgrade your Think-Pair-Share – Faculty Focus

I’ve tried a few different techniques for class discussions over the years, some that I’ve written about previously in Faculty Focus. In recent years, I’ve dialed in a 3-step process for discussion in my face-to-face classes, which has helped me create an engaged classroom climate. It’s Think-Pair-Share (TPS), with some upgrades.

I refined my TPS process after attending Jeremy Rentz’s workshop “Put Your Hammer Down” (detailed in the Best of the 2021 Teaching Professor Conference). His key idea was “The person doing the learning is the person doing the work.” I thought about how to get my students to do more “work” in my large lecture-based classes. Although I knew the active learning benefits of a technique like TPS, I struggled to implement it well. There were often too many awkward silences for TPS to be as engaging as I would have liked. After Jeremy’s workshop, I made some upgrades to TPS that invigorated it for students and for me.

Step #1: Think
Upgrade: Discussion Bubbles

Instead of posing my discussion question after I’ve covered the content on my slide, I now put the question in a Discussion Bubble next to the content. Prior to implementing this, I would review the slide and then pose my question, either a specific one, or something general like “anyone have anything to add?” Then there would be the awkward silence while students think, and I would try to be chill. Having a Discussion Bubble primes students to think and be ready to share (in small or large groups) once I’m done reviewing the slide. It not only decreases the awkwardness (which seems to feed off itself), but it also increases small and large group discussion participation.

Sometimes these discussion bubbles include a polling question that I use to record and display students’ opinions (e.g., Do you prefer a, b, or c?). Students can then see that they are not alone in their views and are more confident to share their perspectives in Steps 2 and 3.

Step #2: Pair
Upgrade: 1-Minute Timer

I give students one minute to talk with classmates about their thoughts on the discussion bubble or their answer to the polling question. On the very first day, I tell students that I will use my watch to set a 1-minute timer and that we’ll have a few of these in every class. I believe that these short, reliable segments help students feel safe and avoid too-lengthy, awkward small-talk. At the end of the one-minute paired discussion, I don’t check to see if they need more time as I have large classes, and the level of discussion is variable. In recent course surveys (classes of 90-175 students), about 70% of students wanted to keep these 1-minute discussions and only 13% wanted to change them (some were undecided). Further, about 44% of students agreed that these 1-minute discussions helped them feel more connected to their classmates (42% had mixed or neutral feelings) and 63% said they were comfortable sharing in class. So, it’s not perfect for everyone, but it’s benefiting many students. Also, I don’t have students pair off every time that I have a discussion bubble—sometimes I skip Step 2 and go straight to Step 3.

After Step 1 and maybe 2, I incentivize large group discussion with an extra credit point for sharing aloud. I’ve written previously about my Fired-Up and Ready to Discuss process, which involves giving students up to 1 point each class (and 3-5 points total for the semester) for sharing aloud. I have undergraduate teaching assistants present and poised to enter the student’s point into the gradebook as soon as they say their name and share (and if they forget, they can find the teaching assistants after class). It’s an immediate reward that encourages sharing in a large class. Only about ½ of students in my large classes share aloud and earn Fired-up Points, but in a class of 100 students, getting 50 to talk aloud is enough to create an engaging classroom climate. In recent surveys, 70% of the students want to keep Fired Up (and only about 10% want to change it).

This upgraded TPS not only helps students “do the work,” but it also makes for a fun and engaging class. It gives my lectures a predicable rhythm that creates psychological safety for student engagement. It also helps me stay confident and relaxed, which isomorphically encourages students to relax and take the risk to share their thoughts.

Dr. Ashley Harvey is a professor in the Department of Human Development and Family Studies at Colorado State University (CSU). Since 2007, she has taught more than 10,000 students across 15 different courses in over 150 undergraduate and graduate sections. Dr. Harvey has spoken at TEDx, is a licensed marriage and family therapist, and earlier in her career worked at the CSU Veterinary Teaching Hospital as a grief counselor and educator.

References

Harvey, Ashley. “An activity that promotes engagement with required readings, even in large classes.” Faculty Focus. February 2017. https://www.facultyfocus.com/articles/effective-teaching-strategies/activity-promotes-engagement-required-readings-even-large-classes/

Harvey, Ashley. “Fired up and ready to discuss.” Faculty Focus. February 2020. https://www.facultyfocus.com/articles/effective-classroom-management/fired-up-and-ready-to-discuss/

Rentz, Jeremy. “Put the hammer down and build your teaching toolbox.” The Best of the 2021 Teaching Professor Conference. October 2021. https://www.magnapubs.com/wp-content/uploads/2021/10/free-report-Best-of-TPC-2021-opt.pdf

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March 10, 2025
Increasing Classroom Engagement – Faculty Focus
In undergraduate classrooms, instructors encounter a variety of students with diverse backgrounds and different personalities. Since discussion-based learning, both in-person and virtual, remains important, teachers should find ways to encourage student engagement in classroom activities and discussions. Student engagement is also critical to the success of students who are more self-directed and specialized, as it allows them to dive deeper into course material within their specialized areas of interest.

When more students are engaged, class conversations become richer, enhancing student learning. For instance, introverted students may have strong opinions and much to contribute but may hesitate to share during class. Students, whether introverted or not, might feel uncomfortable or uninterested in joining group discussions for various reasons. It is the instructor’s challenge to create a comfortable class environment. Not only will students benefit, but instructors can feel more at ease in their own classrooms.

Genuine connections between students are based on trust, which can be encouraged in several ways. Trust-building connections are fostered in an environment with instructor presence and constructive feedback. Students benefit from instructor buy-in, effort, and intention.

To boost classroom interaction and active participation, instructors can include proven strategies in their “teaching toolkit” to foster empathetic connections among their students. Here are some suggestions for your consideration:
- Outline course guidelines clearly. Students need to understand what is expected of them in your course. If class participation standards are set from the beginning—with appropriate explanations regarding “why”—student buy-in should increase. After students understand course expectations, instructors should make every effort to give students timely and constructive feedback. Doing so keeps students accountable and reinforces the course guidelines.
- Model reflective listening. When students participate in a class discussion, instructors should make eye contact, give full attention, and provide visual cues to show understanding. Taking a moment to paraphrase or ask clarifying questions shows engagement and listening on the instructor’s part.
- Encourage reflective listening. Help reduce distractions when students speak. Invite students to validate each other’s responses. Brief instructor participation when students are having group discussions and modeling behavior you seek to encourage can go a long way.
- Praise appropriately. Offer brief, genuine praise when students reflectively listen to each other and provide gentle reminders when appropriate.
- Creatively introduce group discussions. Mix things up. Consider having students draw questions from a hat for discussion or assign a different group member to lead the discussion for each question. You may wish to time discussions or set goals so student groups stay focused and on task.
- Use a variety of classroom activities, but don’t overdo it. Include a group discussion or short activity during every class period. Recognize that classroom activities are like seasoning on food—a little is great, but too much can be overwhelming. Classroom activities should drive home the purpose of the course material being covered. In-class activities can break up what may be perceived as monotony by students.
- Encourage students to interact with new classmates. Student groups should rotate frequently to ensure that everyone has the opportunity to interact with different individuals. You may wish to randomly assign groups to mix students up.
- Invite alternative views. Be sensitive to different perspectives and alternate points of view. Help students recognize that conflicts can be resolved without contention. Students don’t have to agree on a particular topic or point of view, but they do need to show respect to others. To help students and teachers better understand the importance of respecting different perspectives, share a mantra with your students, such as: “Seek to understand before seeking to be understood” to emphasize the value of listening and understanding others’ viewpoints before expressing one’s own views to foster a more respectful and open-minded classroom environment.
- Use peer feedback grading. Learning to give constructive feedback is a skill students can learn with practice. Prompting from the instructor can go a long way when it comes to feedback. Making suggestions such as having students include pros and cons or commenting only on things that are in the student’s control may be helpful.
- Share stories. Who doesn’t enjoy an interesting and relevant story? Stories help students remember information in a fun way. Collect stories that illustrate key principles and important points you’re trying to teach. Stories are relatable and can put listeners at ease.
- Encourage students to share their own stories. Classrooms consist of diverse individuals with a multitude of different stories and perspectives. Sharing stories is an excellent way for students to learn more about the worldviews of others.
- Use appropriate humor. Laughter creates connection. Including tasteful humor in activities and discussions can improve student buy-in and retention. An easy place to start could be to include a joke or riddle-of-the-week for your class to contemplate.
- Invite student feedback. Make course consistency and fairness a priority. Students need to feel they are valuable and their opinions matter. After receiving excellent feedback, instructors should seriously consider making appropriate changes.
Recognize that potential pitfalls can also accompany increased student engagement. Classroom challenges may include:
- Uneven participation or nonparticipation. Some students may attempt to dominate activities and discussions. In any group, some individuals will always be more talkative while others will be quieter.
- Inconsistent results. No two student groups are ever the same. What works in one class may fail spectacularly in another. Stay flexible and be ready to move on if something isn’t working.
- Time management. Activities may take longer than anticipated, so be conscious of the clock. Setting a timer can be helpful to keep everyone on task.
- Student conflicts. Disagreements can lead to conflict, so it’s important to foster a culture of classroom respect to minimize conflict and prevent personal attacks.
- Overwhelmed introverts. Some students may feel uncomfortable speaking and participating in group activities, but be patient and gently encourage their involvement.
- Increased preparation time. Successful activities often need advance planning and materials, so keeping a list of activity and discussion ideas can help avoid last-minute scrambling.
While practice doesn’t necessarily make perfect, expect to have some less-than-perfect experiences as you adjust your teaching style to incorporate some of these techniques. Keep what works—jettison the rest. With forethought and practice, you can make your classrooms more open and inviting to your students.

Dr. Allie Hamstead DC is an Assistant Professor of Clinical Sciences at Sherman College of Chiropractic. She specializes in perinatal and pediatric care. She graduated from the University of South Carolina in 2007 and Sherman College in 2012. She is a practicing chiropractor in Simpsonville, South Carolina and mother to four daughters.

Kenneth L. Alford is a professor of Church History and Doctrine at Brigham Young University and a Colonel, U.S. Army (Retired). He has authored/edited 13 books and over 200 articles.
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February 21, 2025
Motivational Force: Building a Foundation for Student Success – Faculty Focus

Eighteen students crammed themselves into a stuffy classroom assigned for my first-year seminar course on a sunny day in September. With desk tops touching and knapsacks piled high, we maneuvered through introductions and the kind of icebreakers that research indicates can strengthen learning outcomes. At one point, I asked these college newcomers to share academic and career aspirations. Their responses were a tribute to the dreams of young minds: future pediatric nurses, speech pathologists, and more than one veterinarian were gathered in our small, unassuming space.

These students appeared motivated to learn—a direct contrast to the disengagement narrative that permeates today’s education circles. But despite the enthusiasm, research points to a far more sobering reality: approximately half of all college students fail to graduate within six years of enrollment. Those rates can be even more perilous for certain cohorts, including recipients of Pell Grants, the federal financial aid awarded to undergraduate students demonstrating need.

Many of the students gathered in my classroom fit within this most vulnerable category and would likely face the types of hurdles that can diminish learning resolve. Academics demands coupled with the pull of daily life can negatively tip the balance of student outcomes, siphoning away student motivation, according to educational scholar Howard McClusky. His Theory of Margin framework likens student motivation to the calibration of “loads,” versus the counter force of resources, or what he refers to as “power.” Students with sufficient margin between these competing forces have the capacity to take on new challenges, including the hard work of learning; students with insufficient margin fall into overwhelm and have a higher rate of failure.

Determined to hold onto and even strengthen the learner motivation that was apparent on day one of my class, I was committed to the following motivational practices that could lessen the load and promote the type of power needed to make it to the finish line. Here’s what that looked like:

Community lies at the heart of successful student outcomes, so emphasizing the relational aspect of learning became a guiding principle for the class. Leveraging the energy of the first few weeks when enthusiasm is especially strong is an opportunity to forge group connections and cultivate peer-to-peer support. Research points to these informal bonds as a vital form of power, so beginning on the first day of class, my students were placed in groups determined by common areas of academic focus and career aspiration. To override reticence to working collaboratively, we spent class-time setting up What’s App groups and practicing the type of outreach and response that familiarized group members with the act of reaching out to one another.

Career Readiness has become a valued currency in today’s higher education sector, not only because it helps ease entry into the workforce but also serves to more deeply bind education with employment. Our class therefore included assignments requiring students to research their future fields. Using the U.S. Bureau of Labor Statistics website, students were able to deepen understanding of specific fields in terms of industry growth, income, and even entry requirements. Anchoring aspirations with real-world realities was an opportunity to guide students towards their stated goals in real and relevant ways which further enhanced their learning motivation.

Continual Reflection invites students into their learning journeys while also kick-starting metacognition, thereby contributing to learning motivation and success. The simple act of inviting students to think about their learning process can deepen engagement while helping to nudge knowledge acquisition into retention, the goal of good teaching. Reflection can be as simple as dedicating the last few minutes of class to having students write about what they learned and what they would like to revisit for better understanding. We undertook this exercise in almost every one of our 15 weeks. In addition, students captured their reflections via electronic portfolios that served as a permanent record of their progress.

Harnessing the drive and energy needed to maintain motivation over the course of a semester can present challenges, particularly in our post-pandemic years when factors of isolation, stamina, and access to optimal learning environments have taken their toll. We encountered many stumbling blocks over the course of the semester, but in the end each of my 18 students reached the finish line of the course. Countering learning head winds requires an understanding of the complex phenomenon of learner motivation and then committing to evidence informed practices that can maintain—even strengthen—the energy and drive to succeed. That can mean more work and effort in the classroom, but for instructors committed to student success, this is its own deeply satisfying motivational force.

Juli S. Charkes, EdD, has been a classroom instructor for the past 14 years, teaching organizational leadership, communications, and media studies at both the undergraduate and graduate levels. From 2021 to 2025, she directed the Center for Teaching and Learning at Mercy University, where she oversaw faculty development and strategy across 100 academic programs.

References

Ash, S. L., & Clayton, P. H. (2009). Generating, deepening, and documenting learning: The power of critical reflection in applied learning. Journal of Applied Learning in Higher Education, 1(1), 25-48.

Biney, I. K. (2022). McClusky’s Theory of Margin and its implications on adult learners in higher education institutions. Journal of Adult and Continuing Education, 28(1), 98-118. https://doi.org/10.1177/1477971421989337

National Center for Education Statistics. (2022). Undergraduate Retention and Graduation Rates. Condition of Education. U.S. Department of Education, Institute of Education Sciences. Retrieved May 31, 2022, from https://nces.ed.gov/programs/coe/indicator/ctr.

Sasan, J. M. V., Tugbong, G. M., & Alistre, K. L. C. (2023). An exploration of icebreakers and their impact on student engagement in the classroom. International Journal of Social Service and Research, 3(11). https://ijssr.ridwaninstitute.co.id/index.php/ijssr/article/view/566

Schön, D. A. (1983). The reflective practitioner: How professionals think in action. New York: Basic Books.

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February 17, 2025
Why Data Alone Won’t Improve Retention – Faculty Focus
Data has become the cornerstone of decision-making and institutional strategy in today’s higher education landscape. From tracking retention rates to measuring academic performance, data offers a clear, quantifiable view of how students and institutions are progressing. This reliance on numbers has driven many colleges to focus heavily on metrics in an effort to improve outcomes, streamline operations, and secure funding. However, while data provides valuable insights, it fails to capture the deeper, more personal factors influencing student success. The focus on numbers alone ignores relationships’ essential role in retention and persistence. Without considering the emotional and social aspects of a student’s educational journey, particularly the connections they build with faculty and peers, institutions risk overlooking the things that keep students engaged, motivated, and ultimately enrolled. Simply put, data is not enough. To truly support student success, we must move beyond the metrics and prioritize the human connections that make higher education meaningful.

Recent research underscores that while data is essential for tracking trends and setting benchmarks, relationships are the heartbeat of student success. As community colleges across the United States struggle with declining retention rates, it has become increasingly clear that institutional focus should not be limited to numbers alone. Instead, a holistic approach that prioritizes human connection is necessary to improve retention and academic persistence, particularly in community colleges, which serve a diverse population of non-traditional learners.

The Power of Human Connection in Education

While it is easy to get lost in numbers, community colleges must recognize that each data point represents an individual with unique needs, motivations, and challenges. Research has shown that students who feel connected to their college, especially through positive faculty-student relationships, are likelier to persist and succeed academically. Tinto’s Theory of Departure (1997) and Pascarella and Terenzini’s (2005) Influence Theory emphasize the importance of student-faculty interactions in fostering academic success. Students who experience strong, supportive relationships with faculty and staff are more likely to be retained, persist, and ultimately graduate.

Tinto (1997) and Pascarella and Terenzini’s (2005) theories support the idea that retention is not just about the data points we collect but also about the relational aspects that foster a sense of belonging. Students feel valued when the college community (not just faculty) takes the time to know their students, understand their struggles, and provide mentorship both in and outside the classroom. This emotional and psychological support can make all the difference in a student’s decision to stay in college, particularly for those in community colleges who may already juggle work, family obligations, and financial challenges.

Data Tells Only Part of the Story

Data provides a snapshot of institutional performance, but it often fails to capture the complexity of the student experience. While retention rates may point to the success or failure of a program or intervention, they do not provide the rich, qualitative insights needed to understand why students leave or stay. For instance, a student’s decision to withdraw from school is rarely based on a single factor that can be quantified, such as failing a class or missing a certain number of credits. There are often deeper issues at play, such as lack of engagement and support, personal struggles, or isolation.

In fact, studies have shown that the absence of relationships is a significant contributing factor to student departure. Students who don’t feel connected to their professors or college community are more likely to disengage and eventually drop out. On the other hand, when colleges invest in building personal connections with their students, whether through mentoring, frequent communication, or simple expressions of care, students are more likely to persist through difficult times.

Creating a Culture of Belonging

To truly foster student success, community colleges need to prioritize building a culture of belonging that extends beyond academic achievement. Faculty and staff should be encouraged to engage with students in meaningful ways that extend past classroom interactions. This could mean learning about a student’s goals and challenges, offering office hours for one-on-one consultations, or simply providing feedback on how a student is progressing—academically and personally.

Building student relationships requires intentionality and support from institutional leaders. Administrators must recognize that professional development programs should not solely focus on pedagogical techniques but also on the importance of relational skills. Equipping faculty and staff with the tools to build rapport with students, understand their diverse needs, and provide emotional support is as crucial as ensuring they effectively deliver instructional content.

Recommendations for Practice

While data is still essential, community colleges should balance it with creating solid student relationships. Providing opportunities for professional development in relational practices can improve student engagement and retention.
1. Foster Emotional Intelligence: Colleges should invest in developing emotional intelligence among faculty and staff. This includes empathy, active listening, and the ability to offer support during times of stress. These skills are vital for creating environments where students feel understood and valued.
1. Implement Holistic Student Support Services: Students need more than just academic support. Community colleges should expand their support services to include counseling, mentorship programs, and peer support networks. This can help students build relationships with faculty and peers, which can be a powerful motivator for retention.
1. Encourage Faculty-Student Engagement Outside the Classroom: Encouraging faculty to engage with students outside the classroom through office hours, mentoring programs, and informal interactions can significantly enhance student-faculty relationships and foster a sense of belonging.
1. Implement a Customer Service Model: This can significantly enhance student retention by prioritizing personalized, responsive support throughout their academic journey. By offering clear communication, accessible resources, and proactive outreach, institutions create an environment where students feel valued and supported.
Data alone will never provide the full picture of student success. While it can help track progress and identify trends, the key to improving retention rates and fostering student success lies in the relationships cultivated between students, faculty, and staff. By building a supportive, inclusive environment that prioritizes human connection, community colleges can improve retention rates and ensure their students are set up for long-term academic and personal success.

Ultimately, while the importance of data cannot be overlooked, the need for strong, positive relationships should be placed at the forefront of retention strategies. It is the relationships built within the classroom and beyond that truly make a lasting impact on students’ educational journeys.

Dr. Rebecca L. Conley is an accomplished educator and higher education leader, currently serving as the Dean of Teaching and Learning at Ivy Tech Community College. With over a decade of experience in academia, Dr. Conley specializes in fostering innovative teaching environments, promoting faculty development, and driving student success initiatives. She earned her Doctor of Education in Higher Education Leadership from the American College of Education and is recognized for her expertise in curriculum development, accreditation, and strategic planning. A passionate advocate for education, Dr. Conley combines her professional achievements with a commitment to community service and lifelong learning.

References

Pascarella, Ernest T., and Patrick T. Terenzini. 2005. “How College Affects Students: A Third Decade of Research.” San Francisco: Jossey-Bass.

Tinto, Vincent. 1997. “Leaving College: Rethinking the Causes and Cures of Student Attrition.” Chicago: University of Chicago Press.
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January 20, 2025