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A proven and experienced instructional designer, solution architect and natural storyteller.

Learning and Development Professional based in Atlanta, Georgia

Contact: mark.oglesby1@gmail.com

Phone: 770-851-7380

Artificial Intelligence

  1. Click, explore, and play—this interactive game keeps you engaged as you learn by doing.

  2. Test your settings and see the results—this press trapping simulation lets you fine-tune color overlap for clean, accurate prints.

  3. Follow each label step-by-step through the press—see how every stage shapes the final print.

  4. See how artwork is split into separate color layers—each one prepared for precise flexographic printing.

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Topic

AI-Enhanced Interactive Learning – Flexographic Print Process

Modality

Self-paced eLearning (Articulate Rise)

Audience

Prepress technicians and production teams

Business Challenge

Learners struggled to understand the sequential flexographic printing process using static visuals alone.

Solution

Developed a Rise-based eLearning module enhanced with AI-generated interactive graphics to simulate each stage of the flexographic press workflow. Built interactive components using HTML, CSS, and JavaScript, supported by AI-assisted prototyping in Gemini Canvas.

Tools

Articulate Rise, Gemini Canvas, HTML, CSS, JavaScript

Design Approach

  • Deconstructed flexographic workflow into interactive learning stages
  • Used AI tools to generate visuals and prototype interactions
  • Built custom interactive graphics with HTML, CSS, and JavaScript

Results

  • Improved understanding of flexographic workflow
  • Increased engagement compared to static materials
  • Reduced reliance on instructor-led explanations

Role

Instructional Designer – AI-Enhanced Interactive Learning Development

Project Link

View Module

  1. A 10-stage AI-driven instructional design workflow presented as a guided, step-by-step process built with Gemini Canvas.

  2. An automated workflow built in n8n that connects research, structuring, and content generation for instructional design.

  3. A local LLM converting instructional content into speech for eLearning delivery through a text-to-speech pipeline.

  4. Instructional content structured and generated using Google NotebookLM for eLearning development workflows.

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Topic

AI Workflow Automation

Modality

Automated Content & Research Workflows

Audience

Instructional design teams, SMEs, and learning operations stakeholders

Business Challenge

Manual research and content production workflows limited scalability and slowed instructional design output.

Solution

Designed and deployed AI-powered automation workflows to streamline research, content generation, and production tasks using LLM APIs and structured orchestration.

Tools

n8n, OpenAI API, Gemini API, Perplexity API, LLM-based automation tools

Approach

  • Built complex automated workflows for research and content generation
  • Integrated multiple LLM APIs for structured AI outputs
  • Deployed and maintained self-hosted n8n instances
  • Automated repetitive instructional design tasks and content pipelines

Results

  • Reduced time spent on research and content drafting
  • Improved consistency and scalability of instructional workflows
  • Enabled continuous, automated content generation pipelines

Role

Instructional Designer – AI Automation & Workflow Engineer

Interactive Demo

Create ID content prompts

  1. Generative AI producing context-aware visuals that align with learning content, replacing generic stock imagery with more relevant and tailored illustrations.

  2. AI-generated visuals illustrating complex processes and concepts with clarity, replacing abstract ideas with detailed, structured imagery and photography.

  3. Instructional design content structured, analyzed, and generated using Google NotebookLM.

  4. AI-driven audio editing used to correct mistakes, reduce environmental noise, and improve clarity in recorded content.

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Topic

AI-Assisted Content Creation

Modality

AI-Enhanced Development Workflow

Audience

Instructional designers, SMEs, and learning stakeholders

Business Challenge

Slow content development cycles limited rapid creation and iteration of learning assets across formats.

Solution

Built an AI-driven workflow for generating instructional content, visuals, and audio using structured prompt engineering and multi-model tools.

Tools

ChatGPT (OpenAI), Gemini, Perplexity, NotebookLM, TTS tools, AI image tools, Ollama for local LLM use.

Approach

  • Advanced prompt engineering for structured outputs
  • AI-generated outlines, scripts, and visuals
  • NotebookLM for synthesis and structuring
  • Local LLM setup for controlled experimentation

Results

  • Faster content drafting and iteration
  • Improved consistency across learning assets
  • Rapid multi-format prototyping (text, visual, audio)

Role

Instructional Designer – AI Content Workflow Specialist

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