Educational Technology and Change Journal

By Jim Shimabukuro (assisted by ChatGPT)
Editor

Introduction: For a better grasp of the advancements in GPT-4, I’ve asked ChatGPT to explain, in language aimed at 10th-grade high school students, the critical differences between GPT-3.5 (current free version) and GPT-4 (paid version). Keep in mind that I have been and am using the free GPT-3.5 version in all my articles on chatbots — along with other free chatbots such as Claude, Gemini, Copilot, and Perplexity.

To clarify the explanations, I’ve asked ChatGPT to provide actual examples of how 10th graders might apply these advanced features to real-world learning activities in typical courses such as English, Math, History, Art, and Science.

As this conversation progressed, I realized the power of chatbots in developing curricula and lessons. I’m sure many if not most educators are already making use of this potential. Along the same lines, students could use chatbots to plan their school assignments and projects. This article focuses on high school students, but I believe the ideas can be scaled to lower grades and college as well.

Disclaimer: I am not affiliated with OpenAI or any of its partners. This article reflects my independent research and perspective, and is not endorsed, reviewed, or influenced by OpenAI in any way. -js

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Claude)
Editor

(Also see Review of “OpenAI (2023), GPT‑4 Technical Report” [4 March 2024] and A Review of Ouyang et al.’s 2022 Paper aka “InstructGPT”.)

Introduction: For this article, I collaborated with three chatbots: Gemini (Google Bard), ChatGPT (GPT-3.5 free; GPT-4, OpenAI), and Claude (Sonnet 4, Anthropic). I asked each to come up with five seminal works in the development of chatbots. Three were mentioned by two chatbots, so I ended up with a list of twelve. They are listed below by their date of publication. Three were published before 2000, and only one between 2000 and 2014. Five were published between 2015 and 2019, and the remaining three, 2020 and after. Thus, 67% were published in the last ten years.

1. “Computing Machinery and Intelligence” by Turing (1950).
2. “ELIZA—A Computer Program for the Study of Natural Language Communication Between Man and Machine” by Weizenbaum (1966).
3. “Procedures as a Representation for Data in a Computer Program for Understanding Natural Language” by Winograd (Often referred to as the SHRDLU dissertation) (1971).
4. “Social Dialogue With Embodied Conversational Agents” by Bickmore & Cassell (2005).
5. “A Neural Conversational Model” by Vinyals & Le (2015).
6. “Attention Is All You Need” by Vaswani et al (Google Brain Team) (2017).
7. “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding” by Devlin et al. (2018).
8. “Language Models Are Unsupervised Multitask Learners” by Radford et al. (2019).
9. “A Unified Framework of Five Principles for AI in Society” by Floridi & Cowls (2019).
10. “Language Models Are Few-Shot Learners” by Brown et al. (2020).
11. “Constitutional AI: Harmlessness from AI Feedback” by Bai et al (2022).
12. “Training Language Models to Follow Instructions with Human Feedback” by Ouyang et al. (InstructGPT Paper, 2022).

See the chatbot listings below for details about each work. I’m drawn to the latest, especially Brown et al. and Ouyang et al. I’ll follow up this article with chatbot-generated reviews of these two.

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Claude)
Editor

Introduction: I was curious to see how a chatbot would work with a first-year college student who has hated math since high school and is now struggling to pass a required course in algebra. I decided to focus on a male student but asked the bot, at the end of the process, if it would use the same approach with a female student. The chatbots tested were ChatGPT, Claude, and Gemini. As usual, to better understand the philosophical roots of the bots’ approach to tutoring, I asked them to provide explanations and references for their pedagogical decisions. The subject matter is math, but I believe the instructional approach would generalize, with a few tweaks, to other disciplines. The purpose of this article is to give readers a feel for how the human-bot collaboration might work out and a sense of its potential effectiveness, and the goal is to encourage them to make the leap — if they haven’t already — into chatbotting as an invaluable tool in their academic and professional skill set. Finally, another more practical purpose is to get a better feel for the strengths of these three chatbots by experiencing how they might approach the same pedagogical problem, with the caveat that chatbot performances often vary quite a bit from chat to chat. -js

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By Jim Shimabukuro (assisted by Copilot, ChatGPT, Gemini, Perplexity, Claude, Pi, and You.com)
Editor

Introduction: In this article, I presented the same prompt to seven chatbots to observe the range of responses and share the results with readers. The chatbots, in order, were: Copilot, Perplexity, ChatGPT, Gemini, Claude, Pi, and You.com. I’ll let you be the judge of how well each bot initiated communication with a preschooler. -js

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Claude)
Editor

Summary: This article explores how traditional academic disciplines will transform over the next 50 years due to AI integration and global challenges. The author uses ChatGPT and Gemini AI to analyze current core disciplines and project future changes. The piece examines how AI will be integrated into academic divisions, with projections showing computer science achieving 95-100% integration by 2075, while humanities may reach 60-75% integration. The analysis suggests that rigid departmental boundaries will dissolve, replaced by problem-focused, interdisciplinary fields addressing climate change, consciousness studies, and space exploration. The timeline spans from 2025-2035’s “Convergence Decade” through 2065-2075’s “Transcendence Decade,” with new disciplines emerging like neuroengineering, synthetic biology, and eventually cosmic consciousness studies. The article identifies 20 key leaders and institutions driving these changes, including Fei-Fei Li at Stanford and organizations like MIT’s CSAIL, emphasizing that technological convergence and societal demands for cross-disciplinary solutions will fundamentally reshape higher education’s structure and purpose. (Claude)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Claude)
Editor

Summary: The article explores the emerging concept of “AI natives” as a successor to “digital natives,” representing a fundamental shift in how humans interact with technology. Marc Prensky, who coined the term “digital native,” is now pioneering the concept of AI natives as the next human evolutionary leap. This transition marks the beginning of Generation Beta in 2025, representing the first truly AI-native generation. Unlike digital natives who primarily consume and share information through digital platforms, AI natives collaborate with artificial intelligence as cognitive partners, learning through dialogue and iterative refinement rather than traditional search and discovery methods. The article presents responses from ChatGPT, Gemini, and Claude, each offering different perspectives on this generational shift. Key differences include AI natives’ approach to problem-solving through AI reasoning engines, their development of AI literacy and prompt engineering skills, and their expectation of personalized AI tutoring experiences. The implications for educational institutions are profound, requiring fundamental restructuring of curricula, assessment methods, and pedagogical approaches to accommodate learners who will enter higher education empowered by AI collaboration capabilities. (Claude)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Claude)
Editor

Introduction: I collaborated with Gemini, ChatGPT, and Claude on this report. Prompt: Will there come a time when many if not most students will complete the requirements for a college degree without stepping foot on a college campus and taking professor-led courses, relying primarily on partnerships with chatbot mentors and advisers? If yes, please identify colleges or individuals that are pioneering this effort. Also, provide a 50-year timeline, in 10-year increments, to explain and illustrate how this might play out between 2025 and 2075. Please append an annotated list of references, in APA style, that informed your response. -js

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Claude)
Editor

Summary: The article explores whether a highly motivated 15-year-old could successfully drop out of traditional school and use AI chatbots to develop a personalized curriculum, earn a high school equivalency diploma, and gain admission to competitive colleges. The piece presents comprehensive responses from three AI models (Claude, ChatGPT, and Gemini) that largely agree this path is feasible but challenging. The proposed strategy involves obtaining a GED or HiSET through AI-powered tutoring, using chatbots for curriculum development, assessment, and academic support, and leveraging AI tools like Khanmigo, Socratic by Google, and various educational platforms. The responses detail how AI could provide 24/7 personalized instruction, generate custom lesson plans, and offer real-time feedback across multiple subjects. All three AI models emphasize that success would require exceptional self-motivation, strong family support, and strategic planning. They highlight the importance of building a compelling college application portfolio through independent projects, standardized test preparation, and finding human mentors for recommendation letters. The article suggests that exponential improvements in AI technology through 2025-2029 will make this approach increasingly viable, with enhanced personalization, multimodal learning integration, and predictive analytics transforming the educational landscape fundamentally. (Claude)

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By Jim Shimabukuro  (assisted by ChatGPT and Claude)
Editor

Summary: This article presents a creative writing experiment using ChatGPT to generate a 3,000-word story beginning titled “Homeless Awakening.” The narrative follows a homeless Asian man sitting motionless on Ala Moana Boulevard near Honolulu Harbor, who gradually awakens from a catatonic state. The story chronicles his slow emergence from silence through small interactions with Mr. Leung and his daughter Mei from the nearby Golden Lily restaurant. As the man begins helping at the restaurant, hints emerge of his wealthy past and family betrayal in China. The narrative ends with mystery surrounding his true identity and circumstances. (Claude)

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By Jim Shimabukuro (assisted by Claude and Perplexity)
Editor

Summary: This is a narrative generated by the Claude chatbot in response to a creative prompt exploring AI’s capabilities in storytelling. The story follows a homeless Asian man on Honolulu’s Ala Moana Boulevard, described in vivid sensory detail as he endures the harsh sun in silence and isolation. Despite his ragged appearance, hints of a refined past and possible family betrayal in China emerge. The narrative captures his gradual awakening from numbness, beginning with minute acknowledgments of food and water from passers-by, and culminating in his first tentative connection with David from the Golden Dragon restaurant, suggesting a possible path toward human connection and redemption. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT and Claude)
Editor

Summary: The article explores how AI systems will revolutionize peer review in online, asynchronous writing classes over the next 20 years. AI will serve as a central orchestrator, managing draft distribution through intelligent matching algorithms, providing real-time feedback assistance to student reviewers, and offering structured rubrics with adaptive prompts. The technology will enable seamless draft sharing via integrated platforms, with AI analyzing review quality through metrics like specificity and constructive tone. Students will access personalized dashboards showing their progress as both writers and reviewers, while instructors gain comprehensive analytics to identify struggling students and optimize curriculum. Current initiatives include UC Davis’s PAIRR program, which combines human and AI feedback, and tools like EvaluMate and Reviewriter that scaffold peer review quality. The vision presents a future where AI enhances rather than replaces human collaboration, creating more efficient, equitable, and analytically-driven writing instruction environments that benefit both students and educators. (Claude)

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By Jim Shimabukuro (assisted by ChatGPT and Perplexity)
Editor

Summary: This article discusses how artificial intelligence will transform the workflow of online college composition instructors. AI will automate record-keeping, such as scoring participation, quizzes, readings, draft submissions, and peer reviews, and provide real-time dashboards summarizing student activity. Chatbots will deliver personalized reminders and “nudges,” while AI-generated preliminary feedback will free instructors for more in-depth critique. Over the next two decades, AI tools like Stanford’s SEFL and WriteAssist at UC Berkeley will offer clear, rubric-aligned feedback on student drafts and track writing progress across assignments. Systems will monitor how students respond to feedback and adapt interventions accordingly. Leading institutions—including Georgia State University, Northeastern, and UC Berkeley—are piloting these innovations, with AI increasingly supporting adaptive module assessment, student monitoring, and data-driven teaching, ultimately allowing instructors to focus more on higher-order mentoring and instruction. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Perplexity)
Editor

Summary: The article outlines the evolving qualifications essential for college presidents leading higher education into an AI-dominated future over the next five decades. It identifies five core competencies: profound AI fluency and strategic vision for transformation; architecting ethical AI governance; adaptive and resilient leadership; catalyzing interdisciplinary collaboration and ecosystem building; and acting as a global digital diplomat. The author details how these capacities must grow in sophistication with each successive decade as AI systems move from supporting administrative efficiency to fundamentally reshaping the institutional mission, human-AI relations, and even engaging with non-human intelligences. In 2025–2035, presidents are expected to pilot AI literacy and basic policy. By 2065–2075, leaders will need philosophical depth about AI, existential responsibility, and planetary-scale collaboration. The article underscores that proactive, ethically grounded, and visionary presidents will be indispensable for navigating vast societal and institutional change driven by AI. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT and Perplexity)
Editor

Summary: The article explores the concept of AI rhetoric—the persuasive and expressive use of AI in the creation and analysis of texts—and traces its deep alignment with classical rhetorical principles like ethos, pathos, and logos. It details how prompt engineering has become central to writing, turning prompts into acts of rhetorical invention and arrangement. The article identifies academic leaders and programs at Stanford, University of Mississippi, and others that are integrating AI rhetoric into writing and communication curricula. A 100-year timeline is presented, showing a progression from foundational prompt literacy and AI-critique (2025–2045), to collaborative writing studios with AI (2045–2065), adaptive AI rhetoric tutors (2065–2085), civic algorithmic rhetoric (2085–2105), and multidisciplinary cultural co-authorship (2105–2125). Ultimately, the article forecasts a future in which human writers and AI systems collaboratively shape civic discourse, ethical expression, and cultural narratives as core aspects of education. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Perplexity)
Editor

Summary: The article identifies the five leading U.S. universities in 2125 for their adaptability and leadership amid exponential advances in artificial intelligence. These institutions—MIT, Stanford, Carnegie Mellon, Arizona State, and UC Berkeley—are selected for their rich AI research legacies, innovative culture, and commitment to ethical, interdisciplinary approaches. The article outlines a 100-year timeline of critical actions: from the 2020s’ mandatory AI literacy curricula and campus-wide integration of adaptive AI learning systems, to mid-century advances such as personal AI mentors, global research networks, and campus repurposing as immersive AI learning labs. By the 2070s and beyond, these universities pioneer AI-driven career navigation, AGI (artificial general intelligence) governance, and planetary-scale human-AI collaboration. Their ongoing evolution—grounded in ethics, democratization, and participatory governance—ensures they not only pace with but actively shape AI’s societal impact, preparing students for meaningful, co-evolving futures with advanced intelligence. (Perplexity)

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By Jim Shimabukuro  (assisted by ChatGPT, Gemini, and Perplexity)
Editor

Summary: By 2125, traditional staff roles in education—administrators, instructors, and support services—will be profoundly transformed due to the integration of AI, neurotechnology, decentralized governance, and learner-centered systems. Routine and administrative functions such as scheduling, content delivery, and technical support will be automated through adaptive AI learning environments. Human roles will shift to distinctly human domains: instructors become “cognitive architects” and “co-mentors,” guiding identity, ethics, emotional resilience, creativity, and complex decision-making, while administrators evolve into “learning systems stewards,” orchestrating AI-human governance networks. Support staff morph into “neuro-navigators” and well-being designers, specializing in mental health and motivation. Future educators train alongside AI, focusing on empathy, narrative intelligence, and ethical reasoning, with certification involving immersive simulations, real-world interventions, and reputation-based assessments. The human contribution in education becomes more specialized, centering on relational, emotional, and ethical leadership, while AI ensures scalability, speed, and objectivity. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Perplexity)
Editor

Summary: By 2125, the traditional division between “college-bound” and “non-college-bound” educational paths will be replaced by highly personalized, modular learning journeys designed around each learner’s interests, abilities, and neurocognitive profile. Rather than following set sequences, students navigate individualized “learning arcs,” guided by AI mentors and passion-discovery tools, with credentials verified by digital reputation, demonstrated skills, and decentralized learning records. For example, one student might pursue abstract, research-oriented challenges in AI-enhanced pods and global science guilds, while another engages in hands-on fabrication and applied apprenticeships, earning skill tokens through real-world projects. Career integration begins early—via immersive simulations and interdisciplinary collaborations—and learners fluidly move among paths as life circumstances and interests evolve. By career entry, both students achieve high expertise and agency in their domains, demonstrating that the binary educational divide of past centuries is obsolete, replaced by dynamic, purpose-driven paths accessible to all. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Perplexity)
Editor

Summary: By 2125, education is projected to be profoundly transformed by AI, global connectivity, biotechnology, and neuroscience, making traditional, place-bound schools largely obsolete. Instead, learners will engage in hyper-personalized experiences shaped by full-sensory immersive technology (like AR/VR and brain-computer interfaces) and superintelligent AI serving as mentors and administrators. For elementary education, children will learn in AI-coached community pods that emphasize real-time cognitive tracking, creative play, and global collaboration, often with digital or human emotional mentors. Secondary education will center on global learning guilds organized around interests, with students earning micro-certifications through real-world simulations and interdisciplinary projects, guided by both AI and human experts. Higher education evolves into “cognitive universes”—virtual or nature-based hubs supporting identity-driven, project-based learning, where reputation and demonstrable skill outweigh degrees. Some elite physical institutions may persist as heritage centers or community spaces, but most education becomes decentralized, lifelong, and inseparable from everyday life. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT and Gemini)
Editor

My Query: Besides ChatGPT and Gemini, are there other free and reputable chatbots that provide similar services? If there are, please list them along with their strengths and weaknesses.

Yes, besides ChatGPT and Gemini, several other free and reputable AI chatbots offer similar services — such as writing assistance, tutoring, coding help, and general Q&A. Below is a curated list of top contenders, along with their strengths and weaknesses (as of mid-2025):

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By Jim Shimabukuro (assisted by ChatGPT and Perplexity)
Editor

Summary: The article details the essential skills students need in 2025 to excel academically with the support of AI tools like ChatGPT, Gemini, Claude, and Copilot. AI-literate students collaborate strategically with chatbots, using them as cognitive partners rather than shortcuts. Key hallmarks include crafting precise, structured prompts; refining chatbot responses through iterative dialogue; understanding academic integrity by transparently disclosing AI usage; utilizing AI for research tasks like generating summaries and citations; and seamlessly integrating these tools into personal workflows for time management and productivity. Importantly, students must maintain critical thinking, questioning AI outputs for assumptions, accuracy, and bias, and ensuring their final work reflects their own analytical voice. The article provides concrete examples from real courses—ranging from English to Biology and Computer Science—showing how responsible AI use enhances brainstorming, research, style coaching, and technical problem-solving, while upholding originality and ethical standards. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Perplexity)
Editor

Summary: Limited access to high-speed, reliable internet is already a significant factor slowing the adoption of AI-powered teaching, research, and administration in higher education. This digital divide—especially pronounced at smaller, rural colleges and among low-income students—threatens to widen educational and opportunity gaps as institutions with robust infrastructure accelerate ahead. The article outlines several expected changes over the next two decades: substantial campus network upgrades (such as Wi-Fi 7, private 5G/6G networks, and on-premises edge computing) will support bandwidth-intensive AI uses. Colleges will expand direct residential broadband and device access for students, and new tuition models may bundle “connectivity fees” to fund off-campus internet solutions. Nationally, public and private initiatives—including BEAD funding, satellite internet, and 6G rollouts—will target universal broadband as a prerequisite for equitable AI integration. By 2045, remaining barriers will likely shift from raw access to persistent issues of affordability and skills, as technical limitations recede. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT, Gemini, and Perplexity)
Editor

Summary: Over the next 10–20 years, AI will significantly reshape human-development theories in higher education, pushing classic frameworks—from Piaget and Vygotsky to Chickering—toward more adaptive and hybrid models. Theories will move beyond viewing development as an individual process, instead conceptualizing learning and identity as co-evolving within human+AI ensembles. For example, “Hybrid Intelligence” frameworks see cognition as a collaboration between human and AI, redefining agency and self-authorship as relational and negotiated. Knowledge is shifting from being solely in the human mind to existing in interconnected networks that include both humans and intelligent algorithms, as depicted in emerging models like “Algorithmic Connectivism.” These changes demand new forms of metacognitive skills, ethical reasoning, and lifelong adaptability, as learners must critically assess, collaborate with, and leverage AI. Ultimately, future theories will focus on dynamic, co-participatory development, where AI acts not just as a tool but as an active partner in intellectual, moral, and identity growth. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT and Gemini)
Editor

Introduction: I collaborated with ChatGPT and Gemini on this article. Prompt: In the next 10-20 years, how will AI impact jobs as college instructors, administrators, and staff? Will many lose their jobs? Will other types of jobs emerge? -js

ChatGPT’s Response

The next two decades in a nutshell

• **AI will not make universities “teacher‑free,” but it will reshuffle the work. Routine, rules‑based tasks in teaching, administration and campus services are the first to go; work that is relational, strategic or creative becomes more valuable.
Continue reading →

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By Jim Shimabukuro (assisted by ChatGPT and Perplexity)
Editor

Summary: The article examines how AI is transforming peer review in online composition courses. Advanced AI systems now manage key aspects of the peer-review process: automated assignment and matching of peer reviewers, guided and scaffolded feedback prompts tailored to each draft’s needs, and real-time assistance to maintain clarity and constructiveness in comments. Drafts are shared seamlessly via integrated cloud-based platforms, supporting version control and flexible anonymity options. Reviewers use interactive, AI-enhanced interfaces for inline comments and complete adaptive rubrics generated by AI. All feedback undergoes quality assessment via AI, tracking specificity, tone, and usefulness, which is then logged and displayed on student and instructor dashboards. Human-centered initiatives like UC Davis’s PAIRR project blend traditional and AI review, fostering reflection and equity. Ultimately, the article presents a near future where hybrid human–AI peer review improves writing quality, engagement, and learning equity. (Perplexity)

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By Jim Shimabukuro (assisted by ChatGPT and Perplexity)
Editor

Summary: The article explores whether AI tools like ChatGPT can meaningfully substitute for human writing teachers in college settings. Using a sample student error, the author shows how AI quickly and accurately identifies grammar, spelling, and punctuation mistakes, providing corrective explanations and revision tips. The discussion then shifts to educational implications: while AI can efficiently handle mechanical corrections and free instructors from time-consuming markups, key concerns arise around pedagogy and student learning. The article questions whether reliance on AI will truly help students internalize good writing habits or simply encourage dependency on automated fixes. Ultimately, the piece suggests that while AI’s language abilities can improve, its best use is as a supplement—handling routine errors—so that human instructors can devote more time to higher-order feedback, personal mentoring, and fostering critical thinking and creativity in writing, rather than being replaced outright. (Perplexity)

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