Learning Design Portfolio

Applied Adult Learning Principle: Social Cognition and Communities of Practice: Situated cognition (or social cognition) holds that learning is inseparable from the context in which it occurs. Lave & Wenger have made an enormous contribution to organizational culture in the United States and Canada through the development of our conception of communities of practice. The real gift of their research is that it helped people recognize that learning isn't an individual cognitive exercise.

Adult professionals who participate in communities of practice benefit from the culture of that community in ways that deepen their knowledge and professionalization. I differ from Lave and Wenger in that I am not a strict constructionist but I value their insight. In learning design, especially in particular contexts, I consider how I can facilitate the development of communities of practice (Lave & Wenger, 1991).

This particular design used a blended format with xAPI files exported from Rise for learning content sections. The design has seven stages: 1) Course overview, which is like a syllabus but also includes information about how to use the platform 2) Introductory Exercise - this helps learners start to use the social features of the learning platform and get to know each other (using the forum) 3) Learning Content sections - opportunity for interested adults to grow in knowledge about the various topics 4) Instructor Facilitated Section: cohort is together with a facilitator fielding questions about content and bringing up challenging issues about it. By drawing on the knowledge the cohort already has this kind of facilitation can help professionalize as each learner is participating and able to contribute - it's not a didactic session.

This pattern is repeated with 5) Learning Content II 6) Instructor Facilitated II 7) Concluding Exercise. Using a cohort model and encouraging participants to grow as communities of practice makes this learning experience different than one that is merely didactic. There are elements to the learning content that are more didactic but that is only a small part of the larger course design.

Technical design: This platform was built using the open source version of WordPress, extending it with an LMS called Learndash. The course content was developed using Articulate and those files were exported/imported as xAPI (rather than SCORM). The choice for xAPI was for deeper learner analytics and the relative drag of SCORM files. LearnCAT also utilizes WooCommerce for payment/registration and has a security extension that includes MFA and DDoS protection. This and various forms are automated to send data to Google Sheets.

Adult Learning Principle: Scaffolded Practice & Andragogy: While andragogy has been challenged in different ways, Scholars demonstrate that Knowlesian andragogical principles are still considered widely applicable. Studies have demonstrated that their use yields better results than merely didactic approaches.

The chatbot's conversational architecture provides graduated, responsive scaffolding, an approach that can adapt to the level of understanding of the learner and provide support based on that foundation. There is a significant body of literature that supports scaffolding for young and adult learners.

Cyril wasn't built to be a standalone course but rather a resource within a course to use as a knowledge base but also to help make drafts of OCIA pastoral plans based on the literature it has access to. The larger course has only been prototyped but methodologically it facilitates pastoral practice away from the screen rather than learning in a way where learners are not in the actual reality where OCIA takes place. All of my course design considers the benefits and dangers of using screens in the learning process. I find creative ways to faciliate learning activities that take place off screen and unlike some profit based tools don't seek to keep users dependent upon the screen. There are many tools for keeping learners engaged on screen, but as Catholic we have a responsibility to orient people towards real relationships. This personalist philosophy is part of my design approach.

Technical Design: Cyril is built on a scalable Angular 21 framework, utilizing Angular Material and Tailwind CSS/PostCSS for a modern, responsive UI. The core learner experience is powered by the Google Gemini API, with provider interchangeability. A key feature is the RAG-style knowledge base, which leverages Firebase Firestore to enable administrators to update training data dynamically from within the application. Geospatial capabilities are integrated via Leaflet.js, facilitating interactive parish mapping.

Data Orchestration & Deployment: The system streamlines administrative tasks through automated workflows connecting Firebase, SendGrid, Google Sheets, and various Google APIs. The deployment architecture has matured from an initial Cloud Run prototype to a robust production environment on a Virtual Private Server (VPS). A custom build automation script handles the orchestration of the full stack: 1) Landing Page: React-based frontend. 2) Chat Interface: Angular application. 3) Backend: Express API, managed via PM2 to ensure persistent performance and high availability.

Applied Adult Learning Principle: Self-Directed Learning. Adults seek out informal learning environments to fulfill specific personal and professional growth needs. According to self-directed learning theory, adult learners are highly self-motivated and prefer to take ownership of their instructional paths. Rather than following a rigid, linear curriculum, self-directed adults thrive when they can actively explore resources and seek answers just-in-time. This autonomy is particularly crucial for neurodivergent learners, such as those with ADHD, who can become disengaged by repetitive, elementary instruction and instead require immediate, stimulating, and meaningful engagement with complex tasks.

In LXPython, this principle is operationalized by bypassing typical low-ceiling introductory tutorials in favor of immediate, high-cognitive-load coding challenges. By embedding official technical documentation alongside an interactive python runtime and an agentic AI tutor, the application functions as an adaptive, non-linear workspace. Learners are not forced into a compulsory, lock-step sequence; instead, they choose their own projects, test their code in real-time, and leverage the AI facilitator to resolve conceptual gaps on their own terms. This design respects the learner's self-concept as an independent problem-solver, facilitating deeper metacognitive awareness and active schema construction.

Technical Design LXPython is technically designed as an Angular 21 learning application with a modern TypeScript frontend, Angular Material/CDK UI primitives, Tailwind/PostCSS styling, and optional server-side rendering through Angular SSR with a small Express host. Its core interactive feature is an in-browser Python runtime powered by Pyodide, which lets learners execute Python code directly in the client without depending on a remote execution server. The interface also embeds Monaco Editor for structured coding exercises, which makes the platform feel closer to a lightweight IDE than a static course page.

On the data and intelligence side, LXPython uses Firebase Authentication and Cloud Firestore to persist learner profiles, chat history, learning progress, memories, code attempts, forum posts, and user secrets. The teaching layer is implemented as an AI learning agent service that builds responses from user profile data and stored learning history, then calls an LLM API to generate calibrated instructional guidance. In practice, that means the system is architected as a stateful adaptive learning environment: browser-based code execution for immediate practice, Firestore-backed learner state for persistence, and an AI facilitation layer that personalizes explanations, feedback, and progression over time.

Applied Adult Learning Principle: Data-Driven Metacognition (Winne & Baker, 2013). By analyzing behavioral patterns, instructional designers can adjust learning paths in real-time to match the learner's actual cognitive state rather than a presumed pace.

The purpose of using the xAPI file type instead of SCORM was to better understand and respond to learner activity. This can facilitate learning for the learner but also give administrators vital information about learner behavior in particular learning environments.

Data-driven metacognition can be understood in a different ways, e.g. when adult learners realize there is some awareness of and accountability for their activity in a learning environment they are more likely to reflect upon and adjust how they think about it in ways that influences behavior positively for learning.

However, when the system doesn't provide those insights due to an error and/or gets in the way of learner progression, it has a negative impact. When utilizing technologies to facilitate learning, a big part of that can be addressing bugs and shortcomings of these various technologies. This plugin I developed is one tool to do that.

Evidence-Based Design: xAPI (Experience API) packages generate structured learning event statements that record user activity in the form of data, often with timestamps, results, context, and completion metadata. Unlike SCORM, which is tightly coupled to an LMS runtime, xAPI statements can be sent from multiple environments and learning experiences, but they require a Learning Record Store (LRS) to receive, validate, store, and query those statements for analytics. The LRS is what makes xAPI useful at scale: it serves as the system of record for engagement, progression, completion, and behavioral data, enabling reporting across learning modules, platforms, and user contexts rather than confining analytics to a single course shell.

The xAPI Statement Monitor was developed as a diagnostic layer to identify breakdowns between xAPI content, the LRS, and LearnDash course progression logic. In practice, it was used to trace malformed or missing statements, monitor whether expected completion and progress events were actually being transmitted, and compare those events against LearnDash’s own progression and completion states inside WordPress. This made it possible to detect where learner analytics and LMS completion behavior were diverging, isolate issues in statement formatting or delivery, and support more reliable reporting on whether learners had actually progressed through course activities as intended.

Adult Learning Principle: Reflective Practice. Formation-oriented learning depends on repeated attention, self-examination, and the integration of text, habit, memory, and community identity. Carmelito supports this through daily logging, guided reflection, and a library structured around sources that matter to the learner's vocation.

Technical Design: Carmelito is designed as an authenticated formation system rather than a generic journaling app. Its architecture separates per-user formation records, daily practice logs, progress metrics, legislative source material, and library metadata so that spiritual practice, textual study, and long-term growth can be represented as related but distinct domains. The dashboard layer summarizes formation activity without reducing the experience to entertainment metrics: it surfaces patterns such as prayer rhythm, reading progress, practice consistency, and source engagement in a way that supports reflection rather than competition.

The library and legislative reference areas are structured as a curated knowledge system. Source documents can be organized by language, origin, formation category, chapter, and canonical or legislative function, which allows the application to support both browsing and targeted retrieval. AI assistance is intentionally bounded to study support: helping interpret, summarize, search, or connect texts while leaving discernment, spiritual direction, and moral judgment with the learner and community. The interface uses a restrained dark visual system, persistent navigation, and clear domain separation so the application remains quiet, durable, and useful for repeated formation work.

Adult Learning Principle: Connectivism (Siemens, 2005). In a digital age, learning occurs not just within the individual, but across the networks and relationships that individuals maintain within their organization.

Connectivism argues that in networked digital environments, learning resides in the connections between nodes — people, resources, and organizations — and that the capacity to maintain and traverse those networks is itself a core competency. Utilizing these connected networks becomes integral to learning.

Connectivism is a contemporary theory of learning that can be applied to professional settings that are highly dependent upon connected organizational structures (nodes) for success.Research shows that connectivist principles provide a coherent architecture for leadership and organizational development in digital contexts. In addition, empirical research demonstrates that connectivism-informed design strengthens learners' capacity for adaptive, networked knowledge construction in complex institutional environments.

Technical design: ● The DRM (Diocesan Relationship Manager) is a web-based information system designed to model the organizational, pastoral, and administrative complexity of a Catholic diocese. Technically, it combines a Laravel backend with a modern JavaScript frontend to manage structured entities such as contacts, clergy, parishes, organizations, forms, calendars, and custom data fields. Its architecture supports both internal administrative workflows and public-facing data collection through configurable forms, while maintaining relational links between people, roles, institutions, and ministry activities. This makes it possible to move beyond isolated spreadsheets or basic CRM records and instead manage diocesan life as an interconnected system.

From an engineering standpoint, the platform is built for extensibility and operational visibility. It uses database-backed models and migrations to represent diocesan structures, supports authenticated staff workflows, and includes configurable entity types and custom fields so the data model can evolve without redesigning the application from scratch. Additional features such as liturgical calendar integration, workflow-oriented dashboards, and structured form submissions position the DRM not just as a contact manager, but as a diocesan operations platform capable of supporting communication, planning, reporting, and long-term institutional knowledge.

Adult Learning Principle: Cognitive Load Theory (Sweller, 1988). Linux administration asks beginners to coordinate vocabulary, syntax, filesystem concepts, privilege boundaries, and consequences all at once. The design reduces extraneous load by separating the command domain list, the active scenario, the practice terminal, and the glossary into predictable regions of the interface. Learners can focus on the current objective without losing access to supporting reference material.

Active Retrieval and Spaced Repetition: The primary learning path is recall-first. Command names are hidden behind practical scenarios such as checking kernel release, inspecting filesystems, managing users, or reviewing services. Learners can attempt the command in the mock terminal, then mark the card as Again, Good, or Mastered. Progress is persisted locally, allowing review and mastery counts to accumulate across sessions.

Scaffolding: Each card includes layered support: a conceptual hint, a syntax/flag hint, and a revealable correct execution. This keeps the learner in the problem space longer before showing the answer. Alternative modes support different stages of learning: the sandbox shell favors production-like recall, multiple choice lowers difficulty for recognition practice, and true/false checks help learners test conceptual distinctions.

Technical Design: The application is a static HTML and JavaScript learning tool with an embedded command database of 103 Linux administration tasks. Each command object includes category, scenario, hints, accepted command variations, explanation, and mock terminal output. The interface renders command lists, filters, card state, study modes, terminal output, and the bottom cheat sheet directly from that structured data.

The mock bash terminal simulates realistic interaction patterns without giving learners unrestricted system access. It supports typed command evaluation against accepted variants, command history navigation, help and hint commands, mock output, permission-denied feedback for missing elevated privileges, and a sudo password prompt flow. This lets learners rehearse administrative command behavior safely inside the browser.

The glossary is not a separate document bolted onto the activity. It is generated from the same command database as the flashcards, which keeps practice content and reference content aligned. Searching the cheat sheet lets learners recover terminology when needed, while clicking a command routes them back into the corresponding practice card.

Adult Learning Principle: Socio-cultural Learning. Learning is shaped by language, community, history, tools, symbols, practices, institutions, and social context. These presentations use those elements as the center of the instructional design rather than treating history as a neutral list of dates, events, or isolated facts. The learner is invited to ask how people made meaning inside a cultural world and how that world can still be interpreted through names, places, artifacts, and inherited stories.

The Mesoamerican presentation uses cultural-historical framing to help learners read social practices in context: ritual life, settlement patterns, visual symbols, political organization, material culture, and the interpretive limits of looking at another culture from the outside. The design moves from broad context to concrete examples so learners can build a mental model before encountering more specific evidence.

The family heritage presentation uses a similar method at a more personal scale. Instead of presenting the Schoedel name as a static genealogical label, it frames family-name research as socio-cultural inquiry. The presentation connects surname, place, German regional history, migration, family memory, and identity formation so learners can see how a name becomes a doorway into larger historical forces.

Evidence-Based Design: The project combines narrative learning, cultural-historical context, source-supported interpretation, and visual emphasis. It is built for informal adult learning: the learner can enter through curiosity, family identity, cultural questions, or historical interest, then move toward a more disciplined interpretation of evidence and context.

Technical Design: The presentations use a structured visual format with themed navigation, sectioned long-form text, image-led orientation, readable hierarchy, and reference organization. The design separates overview, interpretation, evidence, and reflection so the learner is not asked to absorb every detail at once. This structure supports scanning first, then deeper reading.

Both presentations use socio-cultural history to make connections. The Mesoamerican work connects cultural systems to social meaning; the Schoedel family-name work connects heritage research to Germany, migration, memory, and identity. In both cases, the instructional pattern is the same: begin with an artifact or name, locate it within a broader social world, and help the learner form meaningful connections across time, place, and community.