Tag: AI

Touro University TESOL Candidate Evangelia Diakoumakos’ Instructional Method Assignment for EDPN 673 – Methods and Materials for Teaching English as a Second Language

In current TESOL practice, the question is no longer whether artificial intelligence belongs in the classroom, but how it can be integrated without displacing the intellectual and pedagogical labor that defines effective teaching. This Instructional Method Assignment – Teaching a Mini-Lesson to an ML Audience for the Touro University TESOL/BLE course EDPN 673 – Methods and Materials for Teaching English as a Second Language is designed as a deliberate response to that tension. It positions AI not as a substitute for thinking, but as a collaborator within a broader ecology of embodied teaching, disciplinary knowledge, and reflective practice.

At its core, the assignment asks Touro University TESOL/BLE teacher candidates to inhabit a methodological tradition not abstractly, but physically. The simulated teaching video foregrounds the body as a site of pedagogy: gesture, proximity, pacing, and the handling of realia become constitutive elements of meaning-making. In this sense, the “method-pure” requirement is not merely technical. It is epistemological. It asks candidates to test what it means for a theory of language learning to be enacted through voice and movement in space, rather than summarized in prose.

Evangelia Diakoumakos Method Teaching Simulation Video

The written analysis, by contrast, reclaims the domain of intellectual work. Here, candidates situate their chosen method historically and theoretically, interrogating its assumptions, affordances, and limitations. This component resists the reduction of teaching to performance alone. It insists that pedagogical action must be grounded in critical awareness, particularly when methods are transported into multilingual, contemporary classrooms that differ significantly from their original contexts.

Evangelia D._ Total Physical Response (TPR) in ML instruction_ Method Analysis and Reflective Practice-2Download
Evanglia D_Digraph SlideshowDownload

Between these two domains lies the guided use of AI, specifically through structured co-creation with tools such as Microsoft Copilot. The reflective component makes visible an often invisible process: how ideas are iteratively shaped, challenged, and refined. In my view, this is where responsible AI use becomes pedagogically meaningful. Candidates are not rewarded for seamless outputs, but for evidencing discernment. They must demonstrate where AI supported clarity, where it introduced limitations, and where professional judgment required deviation from its suggestions.

The assignment, therefore, stages a productive dialectic. The physical performance of teaching resists abstraction; the analytical paper resists superficiality; and the AI collaboration resists passivity. Taken together, these elements model a form of teacher preparation that acknowledges technological change while maintaining a clear commitment to pedagogical intentionality.

Featured Touro University Candidate:

Evangelia Diakoumakos is an elementary school teacher in Brooklyn, who teaches a fourth-grade general education (ENL) class. As a teacher of a large multilingual learner population, she has developed an even stronger passion for language development and culturally responsive teaching. She is committed to creating an inclusive classroom where all students feel valued and supported in their learning.

“As a student nearing the completion of my master’s degree, one of the most rewarding experiences has been the ability to connect and apply concepts from my coursework at Touro directly to my classroom. My studies have not only transformed my instructional practices, but have also reaffirmed my love for language learning.”

Evangelia Diakoumakos, Touro University TESOL Candidate

Dr. Cowin publishes: “Narwhals, unicorns, and Big Tech’s messiah complex: A transdisciplinary allegory for the age of AI,” in The Journal of Systemics, Cybernetics and Informatics

“Silicon Valley’s faith in technology as the savior of humanity
echoes ancient myths of divine intervention.” Lanier (2013)

This essay investigates the Messiah Savior Complex in Big Tech, where artificial intelligence is presented as a redemptive force capable of solving humanity’s most urgent challenges. Using the historical analogy of the narwhal tusk trade, in which tusks were sold as unicorn horns to European elites, the analysis illustrates how myth-based narratives continue to influence technological realities. In contemporary discourse, these narratives take the form of hyperstitions, which are beliefs that become real through repetition, institutional reinforcement, and collective investment. Such dynamics obscure empirical scrutiny and displace critical engagement with the socio-technical realities of AI development. The essay argues that magical thinking and industry promotion often sustain these belief structures to deflect regulatory oversight and maintain public enthusiasm. Rather than rejecting technological progress, the paper calls for a transdisciplinary framework that treats AI as embedded in systems requiring accountability, transparency, and contextual awareness.

The unicorn horn deception was not merely a case of medieval gullibility but a sophisticated system that leveraged cultural symbols and created powerful incentives to maintain the existing illusion. Similarly, today’s AI narratives function as powerful mythologies that shape investment, policy, and public understanding. Cowin, J. (2025). Narwhals, unicorns, and Big Tech’s messiah complex: A transdisciplinary allegory for the age of AI. The Journal of Systemics, Cybernetics and Informatics, 23(7), 146–151. https://www.iiisci.org/journal/sci/Contents.asp?Previous=#/

Narwhals, unicorns, and Big Tech’s messiah complex_ A transdisciplinary allegory for the age of AI_The Journal of Systemics, Cybernetics and InformaticsDownload

Xavier Campoverde’s work with CoPilot and Materials Critique & Redesign for Touro University’s TESOL Course EDPN 673

The Touro University Copilot Grant supports my work as a faculty member in explicitly teaching teacher candidates how to use Copilot as an instructional design tool within a structured, standards-aligned pedagogical framework. In this course, Copilot is not introduced as an optional productivity aid. It is taught as a professional instructional resource whose use must be intentional, transparent, and grounded in TESOL theory, state standards, and multilingual learner pedagogy.

The instructional focus of this grant-funded work is on teaching candidates how to work with Copilot, rather than merely allowing its use. Candidates are guided through a faculty-modeled process that emphasizes instructional problem identification, constrained prompting, critical evaluation of AI-generated outputs, and revision based on professional judgment.

Instructional context and assignment purpose

The Copilot integration is based on a major assessment titled “Instructional Material Critique and Redesign with Infographic.” The assignment is designed to teach candidates how to critically analyze instructional materials and redesign them to improve accessibility and rigor for multilingual learners.

Materials may include complete texts or individual chapters from instructional resources commonly used in schools. The assignment explicitly teaches candidates how to engage in mastery-level material critique and redesign using established TESOL and multilingual education frameworks.

Explicit teaching of Copilot as an instructional design tool

Within this assignment, I explicitly teach candidates how Copilot can be used as a co-creative instructional design partner under faculty supervision and pedagogical constraints. Copilot is introduced through direct instruction and modeling, not discovery-based experimentation.

  • Generates draft instructional materials, not finished products
  • Requires human evaluation using research-based criteria
  • Must be revised to ensure linguistic accuracy, cultural responsiveness, and standards alignment

This explicit framing positions Copilot as part of the instructional design process, not as an authority or substitute for professional educators’ expertise.

Xavier Campoverde is a bilingual social studies teacher at the high school he attended growing up. He is passionate about ensuring that every student has the ability to learn based on their individual needs, building on what they already know, and establishing a safe learning environment for all. He is also a proud husband and father to two wonderful children.

I learned that being a TESOL educator means being an advocate, a designer, and a listener, using data, culture, and technology to ensure every multilingual learner can thrive. Xavier Campoverde, Touro University TESOL Candidate.

Materials Critique Redesign XavierDownload

Rachel Melamed master’s degree candidate in TESOL at Touro University: AI Literacy Through Method Embodiment


This assignment, Instructional Method Assignment – Teaching a Mini-Lesson to an ML Audience, required creating a simulated teaching video that demonstrates one specific language teaching method from our course readings. This is a pretend lesson where you act as the teacher presenting to an imaginary multilingual learner audience for EDPN 673 Methods and Materials for Teaching English as a Second Language. This course provides a historical overview of second language acquisition theories and teaching methods. Students learn how to apply current approaches, methods and techniques, with attention to the effective use of materials, in teaching English as a second language. Students will engage in the planning and implementation of standards-based ESL instruction, which includes differentiated learning experiences geared to students’ needs. Emphasis is placed on creating culturally responsive learning environments. Includes 15 hours of field work.

The assignment was designed to deepen TESOL candidates’ methodological expertise while positioning them to engage with artificial intelligence in purposeful and pedagogically sound ways. It reflects Touro University’s broader initiative to strengthen AI literacy across its programs through a Touro Faculty AI Grant headed and supported by Shlomo Engelson Argamon, Associate Provost for Artificial Intelligence and Professor of Computer Science, and Jamie Sundvall, Ph.D, Psy.D, LP, LCSW, Assistant Provost of Artificial Intelligence. Within this institutional landscape, the assignment serves as a structured model for preparing educators to work in learning environments where AI is increasingly integrated into curriculum, assessment, and multilingual support.

My motto, Education for 2060, emphasizes the development of shared spaces of competencies influenced by AI and large language models. As schools and districts integrate AI into core instructional processes, teacher education programs must develop candidates who can navigate these systems with ethical judgment and instructional precision. This assignment, therefore, balances two essential design principles: strong safeguards against unverified AI substitution and intentional guidance for targeted AI use.

The AI-resistant component centers on a six to seven-minute simulated teaching video that requires candidates to embody a single method from the course readings. By performing the method in a real physical space with realia, gesture, classroom presence, and teacher talk, candidates demonstrate the translation of theory into practice. This performance reveals decision-making, sequencing, and pedagogical rationale that cannot be delegated to AI, ensuring that candidates are evaluated on their own instructional competence.

Targeted AI use is built into the assignment through Copilot-supported planning and reflection. Copilot is positioned as a thinking partner that helps candidates examine the structural logic of the method, refine the flow of the activity, and interrogate their own understanding. Proof of work in the form of screenshots and reflective commentary ensures transparency and allows candidates to analyze the accuracy, limitations, and pedagogical value of AI-generated suggestions. In this way, the assignment teaches AI literacy as a reflective and evaluative process rather than a generative shortcut.

The written analysis links the performance to course theories, identifies the method features demonstrated in the video, and articulates how Copilot contributed to planning choices. This component reinforces conceptual understanding while modeling a professional stance toward responsible AI use.

By combining embodied demonstration with documented AI-supported thinking, the assignment prepares candidates for a future in which educators and AI systems occupy interconnected roles. It brings the work full circle by returning to the idea of shared spaces of competencies. Candidates learn to inhabit these spaces with confidence, contributing their own pedagogical judgment while engaging with AI in ways that enhance, rather than replace, their professional expertise.

Rachel Melamed is a high school teacher in Brooklyn, New York. She earned her bachelor’s degree in Inclusive Education from SUNY Cortland and is a first-generation graduate student pursuing her master’s in TESOL at Touro University. Growing up in a Russian-speaking household helped her develop a passion for teaching multilingual learners and shaped her approach to connecting with them in the classroom.

Using Copilot helped me rework a lesson I had taught before and make it more accessible for English language learners. I learned how small adjustments and simplified, repetitive language can make a big difference when designing lessons.

Rachel Melamed master’s degree candidate in TESOL at Touro University
Rachel M_Instructional Teaching method25Download

Touro University: TESOL Candidate Angelica Marziliano’s Analysis of Complex Texts with Complementary Copilot Review

This assignment reflects Touro University’s broader initiative to strengthen AI literacy across its programs through a Touro Faculty AI Grant headed and supported by Shlomo Engelson Argamon, Associate Provost for Artificial Intelligence, Professor of Computer Science & Jamie Sundvall, Ph.D, Psy.D. LP, LCSW, Assistant Provost of Artificial Intelligence

My motto, ‘Education for 2060,’ focuses on shared spaces of competencies shaped by AI and large language models. As schools, districts, and our students adopt AI tools for learning, assessment, curriculum development, and multilingual support, teacher education programs must equip our candidates with the knowledge and nuanced judgment needed to integrate these technologies ethically, strategically, and in alignment with sound principles of pedagogy and instructional design. The goal is not technological substitution but pedagogical enhancement. Responsible AI use requires a clear understanding of when and why an AI-supported process strengthens instructional decisions, particularly for multilingual learners who interact with complex academic texts across content areas.

The work of analyzing text complexity offers an ideal entry point for developing AI literacy in teacher preparation. Examining linguistic, cognitive, and cultural demands requires careful reasoning and structured evaluation. These skills align with high-quality instructional design and can be augmented by transparent AI tools that assist candidates in organizing ideas, checking coherence, and strengthening linguistic analysis without taking over intellectual labor. Within this assignment, targeted use of AI support mirrors the professional responsibilities teachers will face when adapting curriculum materials, planning differentiated instruction, and selecting resources for English Language Learners and Multilingual Learners. Candidates learn to pair human expertise with AI-supported review processes that promote accuracy, clarity, and reflective practice.

The integration of Microsoft Copilot for final review models responsible AI use that complements, rather than replaces, analytical work. Candidates are required to complete their paper independently and then invite AI-supported critique, focusing on coherence, alignment with APA standards, and clarity of argumentation. This mirrors practical praxis where educators may use AI tools to refine instructional plans, check alignment to standards, and evaluate materials before implementation. By engaging in this structured workflow, Touro University GSE candidates experience a practical application of AI literacy that reinforces their ability to evaluate complex text for ELL and ML access while maintaining professional accountability.

The broader purpose of embedding AI-supported review is to help our Touro University TESOL teacher candidates develop habits of mind that pair rigorous analysis with reflective metacognition. Engaging in text complexity analysis, considering reader and task variables, and examining linguistic challenges for multilingual learners requires nuanced evaluative skills. When paired with transparent and ethical use of AI as a secondary tool for refinement, candidates learn how exponential technologies can support differentiated lesson planning and curriculum construction. This fosters a readiness to lead in classrooms where multilingual learners depend on teachers who can leverage digital resources while upholding principles of equity, clarity, and culturally responsive practice.

Angelica Marziliano: I have been an educator for ten years, starting my career as a paraprofessional before transitioning to a general education teacher. Over the years, I’ve had the privilege of teaching a large and diverse student population, including many English Language Learners. I am currently pursuing my graduate degree in TESOL at Touro University to further support all students in reaching their full potential.

At Touro University, I learned that effective teaching means meeting each learner where they are, differentiating instruction so every student can reach their full potential.

Angelica Marziliano, Touro University, TESOL candidate
Angelica MarzilianoText Analysis 2025Download

Live from Arlington: GovAI Summit and AGENTIC 2025

Exclusive for Stankevicius by Dre. Jasmin (Bey) Cowin: Step into Arlington, Virginia, where innovation and policy meet within the Hyatt Regency Crystal City at Reagan National Airport. Modev’s flagship events, GovAI Summit and AGENTIC 2025,are taking place from October 27 to 29, 2025, bringing together experts in healthcare, finance, retail, manufacturing, hospitality/tourism, entertainment/media, government, educators, inventors, and technology leaders to shape the future of artificial intelligence across public and private sectors.

The GovAI Summit serves as the leading forum for implementing the White House’s 2025 AI Action Plan. It gathers federal decision-makers, policy analysts, and technical experts to examine how AI is transforming public service, from procurement and oversight to infrastructure, education, and workforce training. Discussions emphasize accountability and practical deployment, offering insight into how institutions and agencies adopt AI responsibly and effectively.

Running alongside, AGENTIC 2025 focuses on the practical application of autonomous AI in real-world enterprise settings. Attending are executives, developers, and innovation officers who drive AI adoption in large organizations. The sessions highlight strategies for integrating AI into daily operations, managing risks, and achieving measurable impact across teams and products.

In my session, Autonomous AI in U.S. Schools: Practical Realities, Policy Tensions, and Institutional Readiness, I drew on John Wyndham’s “The Kraken Wakes” as an allegory for systemic adaptation to new intelligence.

Read the full article: Cowin, J. (2025, October 30). Live from Arlington: GovAI Summit and AGENTIC 2025. Stankevicius. https://stankevicius.co/artificial-intelligence/live-from-arlington-govai-summit-and-agentic-2025/

Gov AI Autonomous AI in U.S. Schools GovAI PDF FinalDownload

Joyann Castilletti, Touro University TESOL Candidate, on her experience working with structured prompt engineering and AI

MS in Teaching English to Speakers of Other Languages
TESOL – New York is a state that speaks many languages. We need teachers who can find the common ground.

🏛️ As part of Touro University’s comprehensive initiative to introduce #AI #literacy to our students, I am engaged in a #Touro #University #grant focused on developing AI literacy in #TESOL candidates. My project-based approach empowers future educators to leverage AI as a strategic partner in curriculum design, bridging theoretical understanding with applied classroom practice.

Joyann Castilletti is a 7th–12th grade certified English teacher,  currently working as a permanent substitute teacher while pursuing her TESOL degree at Touro University. She is passionate about creating learning environments where every student feels seen, heard, and loved, and where each learner is supported in achieving success. She continues to inspire a love of learning in every English learner while equipping them with the skills to communicate confidently and effectively. 

Although my time at Touro has been brief, it has inspired me to reconnect with my cultural roots through my father and grandmother, celebrating the legacy that came before me. Through Touro’s TESOL graduate program, I’ve had the opportunity to engage with peers from diverse backgrounds, sharing experiences that have enriched me professionally and sparked conversations I might never have had otherwise. 

Joyann Castilletti, Touro University TESOL Candidate

Joyann Castilletti, Touro University TESOL Candidate, on her experience working with structured prompt engineering and AI:

Using this prompt showed me a few things about designing rubrics. For starters, specifics are key to a solid rubric. When I first started student teaching, every assignment I gave had some sort of rubric mainly to protect myself in case a student didn’t do too well. Since student teaching, I have still utilized rubrics but have worked towards making them more specific and rooted in whatever standard I was working on. The rubric that CoPilot and ChatGPT provided is a great jumping point if my students were doing this presentation. My biggest negative with this rubric is that since CoPilot is primarily analytic based, it does not allow for a holistic view of my students (especially since all of my key domains were also analytical). When I make my rubrics, I try to include some element that allows my students that may struggle with the assignment a chance to achieve highly in one category. Additionally, since this rubric was generated from a prompt it did not allow me to have student insight which I like to do (unless I took this rubric to the students and had a discussion about it with them for recommendations or suggested changes). I do like that CoPilot clearly establishes the format of “you do exactly this– you get this score”. When I make my rubrics, I tend to struggle with the verbiage to express exactly what I am looking for and to separate between each score point. With this said, by utilizing this format, I can create more efficient rubrics and change them as needed to make my accommodations.   

Joyann Castilletti 673 db 4 FinalDownload

TESOL Advanced Certificate Candidate at Touro University Angelee Bess’ Structured CoPilot Prompting & Developing AI Literacy in Teacher Candidates

As part of Touro University’s comprehensive initiative to introduce AI literacy across teacher education programs, I am engaged in a Touro University grant focused on developing AI literacy in TESOL candidates. My project-based approach empowers future educators to leverage AI as a strategic partner in curriculum design, bridging theoretical understanding with applied classroom practice.

Within this initiative, teacher candidates progress from mastering the fundamentals of curriculum mapping to designing comprehensive, differentiated learning sequences that reflect professional teaching standards grounded in research-backed principles.

My primary instructional goals are to:

  • Teach foundational and applied AI competencies,
  • Develop practical skills in standards-based curriculum design,
  • Showcase AI as a collaborative tool in instructional planning, and
  • Align deliverables with professional teaching standards.

Foundational AI Competencies

AI vocabulary is embedded throughout the project via explicit terminology such as prompt engineering, AI-assisted content structuring, LLM interaction, and iterative feedback loops. This structured language development ensures that candidates move from foundational comprehension to applied proficiency, demonstrating the ability to use domain-specific AI concepts meaningfully in curriculum contexts.

Ethical Thinking

Ethical reasoning is central to the project’s design. Candidates must maintain human oversight and exercise critical evaluation of AI-generated contributions for instructional quality and curricular coherence. By foregrounding professional judgment and ethical discernment, the project cultivates a nuanced understanding of AI’s potential and its limitations, underscoring the continued necessity of educator expertise.

In upcoming blog posts, I will showcase current student output, highlighting innovative examples of how TESOL candidates apply structured CoPilot prompting to create differentiated, AI-supported instructional materials. These exemplars demonstrate how AI literacy and pedagogical practice intersect to prepare a new generation of educators for the evolving digital landscape of teaching and learning.

Angelee Bess holds a Bachelor’s Degree in Science from Cornell University, a Master’s Degree in Childhood Education from Fordham University, and Extensions in both Early Childhood Education and Gifted Education. She is currently pursuing a TESOL Advanced Certificate at Touro University while working as a K-2 ENL Teacher at an elementary school in Brooklyn, NY. Angelee strives to create an inclusive environment that recognizes, embraces, and values the cultural and linguistic diversity of her students, helping them thrive both academically and socially. Her motto: “Be the change you wish to see in the world” – Mahatma Gandhi

Ms. Bess’ observation in working with CoPilot: “I was impressed by how quickly Copilot created a lesson tailored for Entering-level MLs. By including the grade level, topic, language proficiency, and support needs in my prompt, I received a mini-lesson with simplified text, a visual anchor chart, printable materials, a vocabulary table, and activity suggestions—all differentiated for beginner learners. I initially focused on Entering students to help plan for Stand-Alone ENL classes, but I can also see the value in using Copilot for Integrated settings. I plan to use similar prompts for other proficiency levels to support all MLs in my classroom. Copilot also gave the option to expand the mini-lesson into a full lesson plan with objectives, standards, and assessments, which makes it a powerful tool for creating instruction that connects to students’ experiences and supports their language development.”

Furthermore, Ms. Bess created anchor charts and visuals through structured prompting:

Teaching English to Speakers of Other Languages Certificate

New York’s classrooms are some of the most culturally and linguistically diverse in the country. Our TESOL certificate program prepares NYS-certified teachers to provide responsive, comprehensive education to students of every background.

Personal Opinion: Pedagogical Value of Discussion Boards in Online Courses
I utilize discussion boards as essential scaffolding tools in my online courses at Touro University, providing multilayered support for my master’s degree candidates’ academic development. These course discussion boards function as preparatory spaces where my teacher candidates can practice academic writing conventions, develop critical thinking skills, and experiment with disciplinary discourse before tackling more substantial assignments such as research papers or presentations. Through regular posting requirements, my candidates create meaningful artifacts that demonstrate their evolving command of academic English and pedagogical understanding, including proper APA citation practices which prepare them for graduate-level academic work. The iterative nature of discussion board participation enables me to track my candidates’ linguistic and academic progress throughout the semester, providing valuable opportunities to observe candidate growth over time and identify when coaching sessions are needed, particularly when I notice disconnects between course materials and student responses.

Student Angelee Publication EDDN 637 -1Download

Exclusive for Stankevicius: From Lewis’s Hideous Strength to Deepfakes and the Machinery of Belief

In my previous article for Stankevicius, “The Veldt 2.0: Your Smart Home Wants Your Children,” I drew on Ray Bradbury’s 1950 short story “The Veldt” to warn that the corporate arms race in artificial intelligence is no longer confined to laboratories and trading floors; it is creeping into nurseries and playrooms. I argued that when companies such as Mattel announce plans to embed OpenAI’s language and video models into children’s toys, the Moloch trap comes home. Bradbury’s fictional HappyLife Home, with its immersive nursery, serves as a blueprint for a smart-home ecosystem in which machines monitor and mediate children’s relationships. Negative highlights are privacy breaches, the risk that intimate recordings could be repurposed into deepfake child pornography, and the broader danger that children might form their first emotional attachments with responsive algorithms rather than with human caregivers.

This exclusive Stankevicius article extends that moral inquiry from the home to the public sphere. Deepfakes, convincing audio and video fabrications generated by machine-learning models, transform images and voices into programmable surfaces. They threaten to dissolve the link between what we sense and what is real. The problem is not merely technological; it is moral and political. Drawing on C. S. Lewis’s dystopian novel That Hideous Strength (1945) to explore how technocratic institutions manipulate belief. In the book the National Institute of Co‑ordinated Experiments (N.I.C.E.) attempts to recondition public opinion by flooding society with narratives that make disbelief costly.

Today’s stakes are high. Recent incidents highlight the significant advancements in technology and the continued inadequacy of institutional preparedness. In early 2024, as reported by CNN, the British engineering giant Arup revealed as $25 million deepfake scam, centered around a finance worker in Hong Kong who transferred 39 million dollars (HK$200 million) during a video meeting, believing she was speaking to her executives; the “colleagues” were AI‑generated. 

Cowin, J. (2025, October 9). From Lewis’s Hideous Strength to Deepfakes and the Machinery of Belief. Stankevicius. https://stankevicius.co/artificial-intelligence/from-lewiss-hideous-strength-to-deepfakes-and-the-machinery-of-belief/