The practical demonstration in this project uses irregular English verbs because they are cognitively demanding: learners cannot simply add -ed. They must notice patterns, memorize exceptions, practice pronunciation, connect meaning to context, and use AI ethically as a reflective support tool.

This project was initially imagined as a video-based response for EDLD 5317. At the beginning, one explanatory video seemed sufficient to communicate the movement from feedback to feedforward to self-feedforward. However, as the work developed, the project itself revealed that one video could not hold the full didactic route.

The development of the videos, Gamma/ePortfolio structure, AI process documentation, irregular verb demonstration, discussion reflections, and Pedagnosis Technique required a broader structure. The project therefore evolved into a media work series.

This Gamma/ePortfolio page is part of a media work series created for EDLD 5317 — Digital Environments. The series includes a long-form video discussion, a complete ePortfolio/Gamma website, a practical instructional demonstration, AI-supported process tables, discussion reflections, and a full reference list. Each component builds on the previous one, forming a complete scholarly and professional communication environment — not a single isolated artifact.

This document is organized as a complete build plan for the EDLD 5317 Media Project and the required ePortfolio/Gamma post. It includes the concrete instructional object that the multimedia artifact will teach: irregular English verbs through music, movement, visual patterning, AI-supported self-checking, and self-feedforward reflection.

The following items must be inserted before final submission. They are intentionally marked so they are easy to find when the page is moved into Gamma or the ePortfolio.

Feedback can tell me what happened. Feedforward can suggest where to go next. But self-feedforward asks a deeper question: can I evaluate my own route, revise my own action, and continue my own development? In this project, I apply that question to one difficult English learning task: irregular verbs.

This media project was created for EDLD 5317 as part of my publication journey. The assignment asks for a podcast or long-form video discussion connected to an ePortfolio post, supported by context, resources, citations, and links to the publication draft and innovation plan. I interpret this not simply as a media-production task, but as an opportunity to communicate scholarship to an authentic professional audience.

The format developed into a media work series that includes a video component, a Gamma/ePortfolio page, an instructional demonstration, AI process tables, a reflection framework, and references. The video is one component of the series, not the whole project.

This project matters because many educational systems teach learners how to complete tasks before they teach learners how to interpret the learning route. A learner may receive comments, corrections, scores, or suggestions and still not know what to do next. The problem is not always motivation. Sometimes the problem is that the process is invisible.

This is why self-regulated learning matters: the learner must become able to monitor, evaluate, and adjust the learning process rather than depend only on external correction (Zimmerman, 2002).

Harapnuik describes feedforward as a formative and forward-looking process that gives learners pathways for improvement and growth, contrasting it with traditional feedback that often remains backward-looking and focused on what was wrong (Harapnuik, 2020). Hattie and Timperley (2007) also emphasize that effective feedback helps learners understand where they are going, how they are going, and where to go next. These perspectives are foundational for this project.

My extension is that feedforward should not remain only an external message from the professor, teacher, peer, coach, leader, or AI tool. The most powerful feedforward is the one the learner learns to perform internally. I call this self-feedforward. Self-feedforward is not self-praise or private motivation. It is a disciplined process in which the learner examines evidence, identifies what changed, locates what is missing, revises the route, and decides the next responsible action.

Pedagnosis Technique is a pedagogical assessment process developed through Patricia Silva's metacognitive and didactic framework. The concept emerges from metacognition, but it is adapted for education as a form of pedagogical diagnosis, didactic discernment, and instructional evaluation.

The word diagnosis comes from the Greek diagnōsis, meaning discernment or distinguishing, from diagignōskein, meaning to distinguish or "to know apart" (Online Etymology Dictionary, n.d.). In this project, the term is adapted educationally. Diagnosis does not refer to a medical, psychological, or clinical diagnosis. Instead, it refers to a didactic process of discerning the learner's starting point, identifying barriers, interpreting evidence, and choosing the next instructional route.

Pedagnosis is therefore not clinical diagnosis. The teacher is not diagnosing the student's mind, personality, mental health, or private internal state. The teacher is reading educational evidence over time.

In simpler terms, Pedagnosis helps the teacher ask two questions at the same time:

This creates a dual mirror. One side reflects student growth. The other side reflects the teacher's didactic route.

In ClockSkill language, Pedagnosis helps the teacher discern Clock Skew: the misalignment between the learner's current readiness and the pedagogical time of the instructional route. When a learner struggles, the Pedagnosis question is not, "What is wrong with this student?" The stronger question is, "Where is the route misaligned, and what evidence can help me synchronize the next instructional step?" (Zimmerman, 2002; Panadero, 2017; Ellis et al., 2014; Hattie & Timperley, 2007).

This route shows that Pedagnosis does not replace self-feedforward. It extends it. The student learns to evaluate and revise their own learning route, while the teacher learns to evaluate and revise the didactic route (Ellis et al., 2014; Hattie & Timperley, 2007).

A concept becomes educationally useful when the learner knows how to practice it. Pedagnosis therefore requires that every methodology include exercises, mediation, and self-evaluation.

In this framework, learning is not reduced to receiving information. Learning becomes a documented cycle:

This cycle matters because it makes the learning route visible. The learner does not simply say, "I understand." The learner shows what changed, what was revised, what strategy helped, and what next step is needed.

Many educational concepts are powerful because they create hope. A learner may read a book, hear a motivational message, attend a coaching session, or encounter a new methodology and feel inspired for a moment. That hope matters. However, hope alone does not guarantee transformation.

The problem is not that these concepts are weak. The problem is that many concepts are received as inspiration without a clear didactic route for practice, mediation, measurement, self-evaluation, and transfer. When the learner or teacher does not know how to use the concept step by step, the initial hope may fade. The concept remains admired, but not operationalized.

The Applied Digital Learning program describes learning as collaborative, learner-centered, active, authentic, and oriented toward meaningful change through significant learning environments and COVA: choice, ownership, voice, and authentic learning opportunities (Harapnuik, n.d.-a; Harapnuik et al., 2018). This project follows that logic because the media artifact is not created only for the instructor. It is created for educators, language learners, instructional coaches, team leaders, and EdTech professionals who want to understand how feedback becomes self-directed learning.

The learner's mindset is also essential because it frames learning as more than information transfer. Harapnuik (2024) emphasizes changing thinking about learning, changing one's approach to learning, and changing the learning environment. That aligns with the practical design of this project: the learner does not only memorize a list of verbs; the learner changes the learning environment by using music, movement, visuals, peer explanation, AI self-checking, and reflection.

AI is used as a reflective and production-support tool, not as a replacement for human authorship. In this project, AI can help learners organize irregular verb forms, generate practice sentences, check whether a verb was used correctly, create a short quiz, suggest a memory association, or provide feedforward after a learner produces an example. However, the learner must still verify, revise, pronounce, use, and explain the verb.

EDUCAUSE's AI Ethical Guidelines identify principles that are directly relevant to this project: beneficence, justice, respect for autonomy, transparency and explainability, accountability and responsibility, privacy and data protection, nondiscrimination and fairness, and assessment of risks and benefits (EDUCAUSE, 2025). EDUCAUSE Review also frames ethical AI in higher education around autonomy, disclosed authorship, creativity, and the right to reject AI assistance when appropriate (Gunder et al., 2025).

Accessibility is not added at the end as a compliance feature. It shapes the design from the beginning. The project uses captions, transcript planning, headings, short sections, tables, high-contrast text, descriptive link labels, and a chronological structure. These choices support multiple means of representation, action and expression, and engagement, consistent with Universal Design for Learning principles (CAST, 2018).

The most important accessibility decision is cognitive accessibility. Irregular verbs can become overwhelming because they seem like disconnected exceptions. To reduce cognitive load, this project groups verbs by meaning, sound, pattern, movement, and use. The goal is not to decorate grammar; the goal is to make the learning route visible.

The multimedia design is grounded in the idea that media should deepen learning, not merely enhance appearance. The video explains the conceptual argument. The Gamma/ePortfolio page provides context, citations, tables, and links. The irregular-verb demonstration shows the process in practice. The tables slow down conceptual distinctions. The captions and transcript make the work more accessible.

Mayer's Cognitive Theory of Multimedia Learning argues that learners process information through verbal and visual channels and benefit when words and visuals are coordinated to reduce extraneous cognitive load and support meaningful processing (Mayer, 2021). Paivio's dual coding theory also supports the use of verbal and nonverbal representations when they are meaningfully connected (Paivio, 1986). Movement-based second-language learning, including Total Physical Response, adds a kinesthetic dimension to comprehension and memory (Asher, 1969).

My ideal audience includes graduate learners, English learners, ESL teachers, instructional coaches, team leaders, and educational technology leaders who are working with AI, multimedia, portfolios, and professional learning. The goal is not to reject feedback. The goal is to teach learners how to metabolize feedback into self-feedforward and professional authorship.

I plan to share this project through my ePortfolio, LinkedIn, and future professional conversations about educational technology, didactics, and AI-supported language learning. Engagement matters, but I do not want engagement to mean only views. I want the project to create a professional conversation about how learners become able to evaluate their own learning process.

This media project connects to my publication draft by making the argument more accessible to a broader professional audience. The draft examines the missing didactic narrative and asks why it matters from the perspective of a learner, educator, and developing team leader. The media artifact translates that argument into an audiovisual and practical demonstration: if the missing didactic narrative is the problem, self-feedforward is one way the learner begins to construct the route internally.

Recommended length: 14 to 18 minutes. Format: talking-head video with slides, or podcast with visual companion page. Tone: reflective, scholarly, clear, and professional.

This block is the concrete teaching demonstration that makes the media project more than theory. It shows what the learner will actually learn and how the process works didactically.

The music/movement component is intentionally simple so the learner's cognitive energy stays on the verb pattern rather than on performance. The rhythm can be spoken, clapped, or accompanied by a simple beat. The purpose is retrieval, not entertainment.

These tables show exactly how a learner can use AI without losing authorship. The learner does not ask AI to "do the work." The learner asks AI to help check, explain, generate practice, and support reflection. The learner remains responsible for verification and final understanding.

These prompts are designed to keep the learner in the author position. Each prompt asks AI to support a specific learning function without replacing the learner's judgment, memory work, or authorship.

The Pedagnosis Heat Map translates student evidence into teacher self-metacognition and instructional adjustment. It is not a grading tool. It is a didactic mirror that helps the teacher read patterns across the class and decide the next responsible instructional step.

Pedagnosis is not about making learners, teachers, or systems perfect. It is about helping them recover alignment when the learning route becomes skewed. In ClockSkill language, Clock Skew is the misalignment between the learner's current readiness and the pedagogical time of the instructional route.

The goal is not perfection. The goal is recovery. A learner may misunderstand, pause, overgeneralize, resist, or lose direction. A teacher may move too fast, assume prior knowledge, choose an ineffective tool, or fail to make the route visible. A system may produce confusion because the process is not documented clearly enough.

Pedagnosis helps learners, teachers, and systems read evidence and recover the route faster and more responsibly.

The larger argument becomes concrete in the irregular verb demonstration. A student error is not only a problem. It is evidence for route construction. If the learner writes goed, the teacher identifies overgeneralization of the regular -ed rule and may select modeling, contrastive examples, retrieval practice, rhythm, or gesture. If the learner writes I have wrote, the teacher identifies confusion between simple past and past participle and may select sentence frames, comparison practice, AI-supported self-checking, or oral rehearsal. This is Pedagnosis in action: the evidence selects the method, the method becomes a route, the route produces new evidence, and the evidence guides the next revision.

Pedagnosis also helps demystify the fear of artificial intelligence. AI, computers, applications, platforms, and digital systems are tools. They can accelerate processes, organize information, generate alternatives, support revision, and help learners practice. However, they do not replace human discernment, ethical judgment, creativity, authorship, care, or didactic responsibility.

Contemporary society often invests enormous energy in training computers to become faster, more responsive, and more human-like. Pedagnosis asks a parallel educational question: how can human beings strengthen their own longitudinal capacity to observe, interpret, revise, collaborate, recover, and transfer learning?

The goal is not to expect tools to become human. The goal is to use tools responsibly while developing the human capacities that tools cannot replace. In this framework, AI is not feared as a replacement and not romanticized as a solution. It is positioned inside the didactic route.

Pedagnosis also reframes the relationship between school, life, and career. Learning does not end when a course ends. The same process of evidence, reflection, revision, and transfer continues across professional life.

A learner who documents growth over time is also building professional identity. The portfolio becomes more than an academic archive. It becomes a developmental curriculum vitae: a living record of projects, evidence, decisions, revisions, skills, reflections, and transferable competencies.

This is especially important in a society shaped by AI and rapid technological change. Human beings need to document not only what they produced, but how they learned to adapt, evaluate, revise, collaborate, and recover alignment when systems change.

The portfolio is not only a school assignment. In Pedagnosis, the portfolio becomes a lifelong evidence system. It documents how a person learns, revises, reflects, transfers, and grows across school, career, and life.

This applied example is included as an above-and-beyond extension of the media project. It demonstrates what the didactic route looks like in practice — not as a replacement for the main project, but as a concrete illustration of the framework.

This applied example is included as an above-and-beyond extension of the media project. The central project remains focused on feedback, feedforward, self-feedforward, AI ethics, multimedia learning, accessibility, and professional authorship. However, because my argument is that learners need a visible didactic route, I wanted to demonstrate what that route can look like in practice.

In this applied example, students do not simply memorize irregular verbs. They design an Irregular Verb Campaign in which they teach one or more irregular verbs to their classmates through a creative, multimodal artifact. They may use music, movement, visual art, poetry, collage, rhythm, storytelling, slides, video, performance, or another appropriate medium. The teacher does not prescribe the creative form. The teacher guides the learning route.

Note: This campaign is a proposed future implementation of the framework. It demonstrates how the didactic route could be expanded into a multimodal student project. Anonymous peer review is a planned extension, not yet implemented.

Each student or small group chooses one irregular verb or one irregular verb pattern. Examples may include:

Note: The anonymous peer review process described here is a planned future extension of the Irregular Verb Campaign. It has not yet been implemented. The language below describes how this process would work when implemented.

In a future implementation, the peer review process would be anonymous for the student receiving the feedback. This would protect the identity of the reviewer and help the class focus on the quality of the information rather than on who gave the feedback.

The purpose of anonymity would be didactic. It would reduce social pressure, protect the student who gives feedback, and direct attention to the usefulness of the feedback itself. When implemented, peer review would become feedforward by helping the learner identify the next responsible action. Feedback would be most useful when it helps learners understand where they are going, how they are going, and where to go next (Hattie & Timperley, 2007). Peer assessment can also support learning when students evaluate work, compare criteria, and use feedback to improve performance (Topping, 1998).

Each student maintains an AI process diary. The purpose of the diary is not to prove that AI created the work. The purpose is to document thinking, research, revision, and decision-making.

AI should function as a reflective support tool inside the learning route. It may help students ask questions, compare examples, organize ideas, generate practice prompts, or reflect on revision decisions. However, AI does not replace the student's responsibility to verify, revise, explain, and present the final work. This preserves human agency and aligns with ethical AI use, especially transparency, accountability, privacy, fairness, and responsible judgment (EDUCAUSE, 2025; Tammets & Ley, 2023).

In a future implementation, after drafting, AI documentation, revision, and a planned anonymous peer review cycle, students could present their final irregular verb campaign to the class. The presentation is designed as if the student were teaching the verb to an audience.

The following responses address the Showcase & Reflect discussion prompts for EDLD 5317. Each response connects the media project to the broader scholarly and professional argument developed throughout this document.

This project now requires field research and testing. The next stage is not only to refine the concept, but to observe how Pedagnosis functions in a real educational environment over time.

The proposed doctoral direction is a longitudinal study of Pedagnosis inside a middle school context over approximately three years. This setting is significant because the original observation and creation of the project emerged from a middle school educational environment and from direct reflection on how learners respond to correction, support, evidence, AI, and didactic routes.

The following table outlines the proposed research design for the next stage of Pedagnosis development.

Pedagnosis is a discipline of educational discernment. It helps education move from problem-pointing to route-building, from motivation to method, from concept to didactic pathway, from tool-dependence to human authorship, and from static products to longitudinal growth. Its purpose is not to make learners or systems perfect, but to help them recover alignment through evidence, reflection, revision, and transfer. The next stage of this work is field research: to observe, test, and refine Pedagnosis longitudinally in the educational environment where the original insight began.

This project is also connected to my personal and professional portfolio: https://plscesar.wixsite.com/portfolio-pro-1

In many ways, I am living evidence of the idea behind this work. I am part of the infinite mosaic of learning — a mosaic that begins when we are born and continues until the end of life. Human beings have always learned, adapted, questioned, created tools, and reorganized themselves in order to survive, evolve, and contribute to the world. Learning is not only something we do in school. Learning is one of the oldest human acts.

Pedagnosis emerges from this understanding. It recognizes that education is not only about receiving information, completing assignments, or producing final products. Education is a lifelong process of questioning, discerning, revising, transferring, and becoming. Every learner carries evidence of growth. Every teacher carries evidence of practice. Every portfolio can become a living record of formation.

Technology and artificial intelligence are part of this human journey, but they do not replace it. AI needs human evolution as much as humans now need ethical and intelligent tools. The more human beings learn, reflect, organize knowledge, and ask better questions, the more technology can support discoveries in health, disease prevention, social organization, education, creativity, and personal development. Tools become more meaningful when human beings become more conscious of how to use them. (EDUCAUSE, 2025; Tammets & Ley, 2023).

For this reason, Pedagnosis does not position AI as the center of learning. It positions human discernment as the center. AI can process, organize, calculate, and accelerate possibilities. But the human being still gives meaning, ethical direction, purpose, care, interpretation, and responsibility. The future of education is not human versus technology. It is human growth through responsible tools.

This is the philosophical center of my work: we are not finished beings. We are lifelong learners inside an unfinished mosaic. Each question, error, insight, revision, relationship, tool, and discovery becomes one more piece of the larger human design. Pedagnosis helps us read those pieces with more attention. It helps us transform experience into evidence, evidence into route, route into growth, and growth into contribution. (Dewey, 1938; Zimmerman, 2002).

This section closes the project sequence by applying the central argument of this media project to my own academic journey. If learning should not be evaluated only by final products — but by the visible process of development, revision, evidence, reflection, authorship, and transformation — then the most honest way to test that argument is to apply it to myself first.

To do that, I used my own M.Ed. academic trajectory as an experiential case study. I submitted my course artifacts, Gamma projects, portfolio pages, PDFs, and AI-supported reflective dialogue to an external AI-assisted evaluation. The result is the External AI-Assisted Evaluation Report, a qualitative cross-artifact analysis of my academic growth, thinking process, creativity, methodology awareness, and emerging doctoral readiness.

The central evaluator finding reads: "Patricia Silva demonstrates strong emerging doctoral-level thinking. Her current stage is best described as advanced conceptual formation moving toward doctoral research readiness."

The report documents how my work evolved across courses, professors, Gamma artifacts, portfolio pages, PDFs, and AI-supported reflective dialogue. It evaluates conceptual originality, interdisciplinary synthesis, creative academic design, AI-supported metacognition, and the ability to transform assignments into a larger research direction. It also identifies areas for continued development, including methodological precision, literature mapping, and formal academic organization.

Including this report in the project is not self-promotion. It is evidence. It shows that self-feedforward is not only a theoretical construct I argue for in this media project. It is a process I have lived, documented, and made visible across my own academic trajectory. AI was used transparently as an evaluative support tool, consistent with ethical AI principles of transparency, accountability, and human agency (EDUCAUSE, 2025).

The full report is available as a linked PDF. It is recommended reading for anyone who wants to understand not only what this project argues, but how the argument was lived.