Tag: education

Infographic by Dr. Jasmin (Bey) Cowin: Reading Error Root Cause Reference Sheet – From Student Error to Instructional Action

This infographic is designed for educators working with Emergent Writers and Newcomers to Literacy (EWNL), English as a Foreign Language (EFL), and TESOL learners across elementary, secondary, and adult contexts who are acquiring literacy in alphabetic writing systems. Its purpose is to support instructional decision-making grounded in the Science of Reading by linking observable reading errors to the specific cognitive and linguistic processes that underlie word recognition.

The organizing principle of the infographic, the instructional response must match the processing breakdown, not the surface error, reflects a central finding of reading science: word reading difficulties arise from identifiable breakdowns in component processes rather than from general language proficiency, motivation, or exposure to text. Decades of research demonstrate that effective reading instruction requires diagnosing which processing system has failed and responding at that level with targeted instruction (Gough & Tunmer, 1986; Moats, 2020).

The framework is structured around four empirically supported domains of word recognition: phonemic awareness, phonics knowledge, decoding behavior, and automaticity. These domains align with models of skilled reading that distinguish between language comprehension and word recognition, most notably the Simple View of Reading (Gough & Tunmer, 1986), and with research on orthographic mapping as the mechanism that enables accurate and fluent word reading (Ehri, 2014; Share, 1995).

Each panel in the infographic identifies a specific processing breakdown and pairs it with an instructional response that directly supports orthographic mapping. For example, phonemic gaps require oral phoneme manipulation without print, while phonics gaps require explicit instruction in sound–symbol correspondences. Weak decoding habits reflect reliance on context or partial visual cues, which research has shown does not support long-term word learning (Share, 1995). Lack of automaticity reflects constrained working memory during reading and calls for accurate repeated practice rather than new phonics instruction (LaBerge & Samuels, 1974).

  1. Working Memory Capacity: Readers have limited working memory. Non-automatic word recognition quickly exhausts this capacity, hindering comprehension.
  2. Role of Practice: The goal of practice is to make decoding and word recognition so fast and accurate that it becomes automatic.
  3. Focus on Fluency: Instead of introducing new rules, practice should focus on increasing the speed and ease with which known skills are applied.

For multilingual learners, including EFL and TESOL students of all ages, this distinction is essential. Research indicates that decoding difficulties in second-language readers often mirror those of monolingual learners and should be addressed through the same evidence-based instructional approaches, while keeping language comprehension supports separate (August & Shanahan, 2006; Lesaux et al., 2007).

The instructional decision check reinforces a diagnostic stance toward reading errors, treating them as data that inform instruction. This approach aligns with Science of Reading principles that emphasize precision, systematic instruction, and alignment between assessment and response.

References

Touro University TESOL Candidate Jennifer Taranto’s Fieldwork for EDDN 637 – Second Language Learners and the Content Areas

MS in Teaching English to Speakers of Other Languages

Course Description
Students will become acquainted with and practice effective approaches, methods, and strategies for teaching and evaluating English language learners in the content areas (ELA, Social Studies, Math and Science). Throughout the course, students will explore the impact of culture and language upon classroom learning. Special challenges in teaching and assessment in each content area will be discussed. Examination and analysis of curriculum materials and instructional strategies for creative teaching and learning in grades Pe-K-12. Includes content-specific lesson planning that addresses the New York State Student Content Learning Standards with emphasis
on English Language Arts, English as a Second Language, and content area instruction. Course content includes demonstrations, simulated activities, and field observations in Pre-K-12 classrooms. The course also examines how the teaching of English to non- native speakers can be integrated with the teaching of cognitive skills in all content areas. Students will be offered a variety of methods and materials to integrate ESL standards throughout all content areas for classroom use. Includes 15 hours of fieldwork. Includes 15 hours of fieldwork. 3 credits

Jennifer Taranto: I’m graduating with my TESOL certification this June, and I can’t wait to bring everything I’ve learned into the classroom. After 17 years as a paraprofessional and now three years as a special education teacher, I’ve learned that every student shines when given the right scaffolds and support. Teaching in a 12:1 classroom keeps me on my toes, challenges me to be creative, and reminds me why I love this work every single day.

“During my 15 hours of ENL field observations, I learned that effective teaching goes beyond delivering content; it’s about creating a learning environment where all students can participate and feel confident. Seeing how intentional scaffolding, clear instruction, and ongoing support help English learners access content showed me the real impact thoughtful teaching can have on student engagement and success.” Jennifer Taranto, Touro University TESOL Candidate

Ms. Taranto wrote in her fieldwork paper:

“Throughout these lessons, teachers consistently integrated explicit language objectives, modeled think-alouds, provided sentence frames and word banks, and designed opportunities for oral rehearsal prior to writing, moves that reflect core sheltered instruction practices for making content comprehensible while advancing language development (Echevarria, Vogt, & Short, 2017; Kareva & Echevarria, 2013). The instructional materials throughout the lesson followed a purposeful multimodal approach. The segregation lesson utilized historical photographs, while picture cards and sentence strips helped students learn sentence structure and the past tense, and emojis aided them in understanding the meanings of adjectives and their effects.” Jennifer Taranto, Touro University TESOL Candidate

In my opinion, this passage clearly crystallizes her fieldwork insights for several reasons.

First, it demonstrates analytic synthesis rather than description. Jennifer moves beyond listing observed practices and explicitly names how those practices function within a sheltered instruction framework. The linkage between observed classroom moves and theoretical constructs such as comprehensible input, multimodality, and oral rehearsal signals disciplinary competence and analytic maturity.

Second, this section demonstrates a tight alignment between the data and the framework. She does not merely cite the SIOP Model, but illustrates its components through concrete instructional examples, such as think-alouds and sentence frames. This alignment indicates that she synthesized SIOP as an enacted pedagogy rather than an abstract checklist.

Third, the passage captures fieldwork-specific insight that could only emerge from sustained observation. The reference to emojis, historical photographs, and sentence strips reflects attention to how teachers translate abstract language demands into tangible semiotic supports. This is a hallmark of strong qualitative fieldwork analysis, as it foregrounds instructional decision-making in context.

637 Field Work Paper Fall fieldwork (1)Download

Journal of Invitational Theory and Practice publishes Transdisciplinary Dialogues on AI in Education: Earth, Air, Water, Fire as Metaphors for Change

I am delighted to announce that our article was published!

Dacey, C. M., Cowin, J., & de los Reyes, J. (2026). Transdisciplinary dialogues on AI in education. Journal of Invitational Theory and Practice, 31, 60–80. https://doi.org/10.26522/jitp.v31i.5420

Abstract: The authors integrate the classical elements – earth, air, water, and fire – within post-human perspectives to explore the multifaceted integration of Artificial Intelligence (AI) in educational contexts. A transdisciplinary approach invited a fertile dialogue among three academic experts from distinct fields of study, who then examined the transformative impact of AI in education: transcending traditional anthropocentric perspectives. In the ‘Earth’ metaphor, the narrative likens AI’s role to Earth’s stabilizing properties. It critically analyzes AI simulations in various disciplines, emphasizing AI’s support in fundamental learning and cognitive development, yet maintaining skepticism about its effects on embodied cognition and experiential learning. Addressing ‘Water’, the authors underscore the need for fluid, adaptable educational governance in response to AI integration. This element resonates with post-human ideas of fluidity and hybridity, urging educational systems to be responsive while expressing concerns about rapid technological changes and their wider implications, calling for thoughtful policy revisions. The focus in ‘Fire’ shifts to AI’s transformative effects on educational governance, intertwining ethical and data privacy issues. The authors critique the potential centralization of power of educational technology companies and the importance of preventing educational inequities and biases. Transitioning to ‘Air’, the focus is upon AI’s exponential impact on pedagogy, just as air facilitates communication. The authors examine AI’s potential for personalizing learning and enhancing interactive dynamics. Examining this element also highlights the importance of algorithmic transparency and the risks of diminishing human roles in education. Finally, the authors examine and interpret the United Nations’ Agenda 2030through a post-human perspective, advocating for an educational governance model and framework that acknowledges the interplay between human, non-human, and technological entities, thereby emphasizing the need for transdisciplinary perspectives on AI in education to capture the Zeitgeist of the Fourth Industrial Revolution.

Transdisciplinary Dialogues on AI in EducationDownload

Touro University TESOL Candidate Carly Croteau’s Student Work Demonstrating Disciplined Copilot Use

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.

Instructional Materials Critique and Redesign

This assignment centers on material analysis as a core professional skill. Candidates critically examine two instructional materials at different grade levels to investigate how linguistic demands, discourse expectations, and access points for multilingual learners vary across instructional contexts. This comparative approach is designed to move candidates away from generic notions of “ELL strategies” and toward a disciplined analysis of language use, text complexity, and opportunities for meaning-making. In my view, this kind of analytic work is foundational to effective TESOL practice and is often underemphasized in methods coursework.

Within the context of the AI grant, Copilot is used in a deliberately structured way. It functions as a generative drafting tool that supports instructional redesign, not as an instructional authority. Candidates identify a specific instructional limitation in a selected material, use Copilot to generate a redesign artifact, and then evaluate and revise that output using WIDA English Language Development Standards, New York State Next Generation Learning Standards, and established TESOL frameworks. The requirement to critique and modify AI generated content foregrounds professional judgment and exposes the limitations of automated outputs in addressing linguistic precision and cultural responsiveness.

The infographic component extends this work by requiring candidates to synthesize analytic findings into a visual support that could plausibly mediate content access for multilingual learners. This element emphasizes multimodality as an instructional practice rather than a design exercise. Taken together, the assignment models an approach to AI use that is critical, standards aligned, and grounded in the everyday instructional decisions TESOL educators must make.

Carly Croteau is in her second-to-last semester at Touro University. She serves in her Fourth Year of Teaching as a fourth-grade general education teacher within an ENL classroom. Carly shared a quote to describe her Touro Journey: “I’ve learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.” by Maya Angelou

Carly Croteau’s exemplary submission demonstrates a precise, standards-aligned critique of both materials and a redesigned artifact that clearly addresses an identified linguistic barrier for multilingual learners. Her use of Copilot is transparent and disciplined, with revisions that reflect strong TESOL knowledge and well-justified instructional decision-making.

EDPN 673 Instructional Material Critique (1).docxDownload

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

Touro TESOL Candidate Madison Derwin’s Field Observations and Reflections

Fieldwork reflection is a critical component of TESOL candidate growth because it functions as the primary mechanism through which theoretical knowledge is transformed into professional judgment. In EDDN 635, curriculum development and classroom management are not treated as abstract constructs but as situated practices shaped by technology, policy, and the linguistic realities of multilingual learners. Reflective fieldwork allows candidates to systematically examine how instructional decisions, technological tools, and classroom management strategies interact to support or constrain language development in real educational settings.

From a pedagogical standpoint, structured reflection promotes metacognition, professional noticing, and evidence based reasoning. By observing classrooms, libraries, and technology infrastructures, and by engaging with ICT specialists and educators, candidates learn to analyze curriculum design choices in relation to student needs, institutional constraints, and state level policies. Reflection deepens this analysis by requiring candidates to connect observations to course readings, TESOL principles, and research on technology mediated instruction. In my opinion, this deliberate linking of theory, observation, and analysis is what moves candidates beyond description toward informed instructional decision making.

Ultimately, reflective fieldwork supports the development of adaptive, reflective practitioners who can design technology integrated curricula that are linguistically responsive, pedagogically sound, and contextually appropriate. For TESOL candidates, this process strengthens professional identity, sharpens analytical skills, and lays the foundation for sustained growth in an increasingly complex and technology driven educational landscape.

Madison Derwin holds a Bachelor’s Degree in Inclusive Childhood Education from SUNY Cortland. She is currently pursuing a Master’s Degree in TESOL and working as a 4th-grade Teacher’s Assistant at an elementary school on Long Island. Her goal as an educator is to create an inclusive, supportive learning environment that empowers every student to reach their full potential and thrive both academically and socially. She shared a favorite quote: “I’m not telling you it’s going to be easy- I’m telling you it’s going to be worth it.”- Art Williams

EDDN 635 Reflection Paper Madison Fall 25Download

Madison Derwin 673 fall 25 MultimediaDownload

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

Master’s Degree in TESOL Candidate at Touro University Carly Croteau’s Submission: Simulation Teaching, Embodiment, and AI Literacy

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.

Carly Croteau is in her second-to-last semester of the Master’s Degree in TESOL at Touro University and is currently in her fourth year of teaching as a fourth-grade general education teacher in an ENL classroom. Her favorite quote: “I’ve learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.” by Maya Angelou

I was first introduced to Copilot during a district professional development session and encountered it again this semester in my TESOL coursework at Touro University. I find Copilot to be a valuable support for both educators and students when used with clear, well-structured prompts. I see it as a helpful aid that can enhance instructional work, but not as a replacement for the professional judgment and intellectual effort that teachers and learners bring to the process.

Carly Croteau, Master’s Degree in TESOL candidate at Touro University

Carly Croteau Grammar Translation Method Video (teaching simulation)

Carly Cannotated-EDPN67320Method20Supporting%20MaterialsDownload
Carly C_EDPN 673 Instructional Method Assignment- Written AnalysisDownload

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