552.
Digital Media Production
Introduction to eLearning Project
Course Description: This course explored the foundational principles of digital media design through the hands-on application of industry-standard tools, including Adobe Dreamweaver, Photoshop, Camtasia, and WordPress. Emphasizing visual aesthetics, accessibility, and usability, the curriculum focused on the end-to-end development of responsive, functional websites using HTML5 and CSS3. Rather than treating software skills in isolation, the course culminated in comprehensive multimedia projects that integrated graphic design, video editing, and web development to drive effective digital communication and strong instructional outcomes.
Grade: A
The topic of this micro eLearning project is the integration of Artificial Intelligence (AI) into classroom instruction. The module is designed to help educators understand the practical applications of these emerging technologies and use them as pedagogical assets to modernize instructional delivery, increase student engagement, and improve academic performance.
The target learners are District 1 middle school educators, most of whom have more than 15 years of teaching experience and proven success with traditional instructional methods. While they are familiar with online teaching tools, few have experience with AI. This module is tailored to their background, providing accessible, scenario-based training that respects their expertise while equipping them with new skills.
The context in which this micro eLearning will be used is District 1’s professional development program. The module will be implemented during scheduled training sessions and accessed through the district’s learning management system (LMS). It is designed as a microlearning experience, allowing teachers to complete short, focused lessons asynchronously, followed by collaborative peer-review sessions to apply their learning in practice.
The intended learning outcomes of the module are threefold: first, educators will be able to apply AI tools to redesign lesson plans that enhance student engagement and support personalized learning; second, they will evaluate the impact of AI integration on student performance using provided metrics and rubrics; and third, they will design classroom activities using AI tools that promote higher-order thinking skills such as analysis and synthesis.
The completed micro eLearning module can be accessed at the following URL:
https://691a98403d12abfedc4a8262--splendorous-monstera-e07f8c.netlify.app/
Micro eLearning Production
The analysis phase of this project began with identifying a critical performance gap in District 1’s 8th grade schools, where student outcomes had fallen below national averages despite significant investments in Artificial Intelligence (AI) technologies. The module was developed to bridge this gap by equipping educators with practical strategies to integrate AI into instruction. A needs analysis revealed that the target audience, middle school educators with over 15 years of experience, were highly skilled in traditional methods but lacked exposure to emerging technologies. Therefore, the training was designed to respect their expertise while providing accessible, hands-on practice with AI tools.
In the design phase, I created a storyboard in PowerPoint to map learning objectives, lesson flow, and instructional strategies. Each module section was explicitly tied to one or more objectives, such as redesigning lesson plans, evaluating the impact of technology integration, and designing higher-order thinking activities. The design decisions were guided by Bloom’s taxonomy to scaffold objectives from application to evaluation and design. A microlearning format was chosen to respect teachers’ limited time, with short, focused modules that emphasized practical application. Multimedia elements such as audio, video, and animation were incorporated to model AI affordances and increase engagement, while scenario-based learning was used to foster reflection and transfer of knowledge.
During development, I employed a range of technologies to bring the storyboard to life. Authoring tools such as Articulate Rise, Adobe Captivate, and Storyline were used to create interactive demos and scenario-based videos. Canva Education and Genially supported the design of infographics and interactive visuals, while Google Forms and Microsoft Forms facilitated evaluation surveys. Dashboard simulations were embedded to allow teachers to explore sample student data. The published module is available at the provided Netlify link, and screenshots of the storyboard and interactive dashboards were used as artifacts to illustrate the development process.
The pilot test and revision phase involved peer feedback, which highlighted the need for stronger alignment between activities and Bloom’s higher-order domains, as well as simplifying technical jargon for educators unfamiliar with AI. Based on this feedback, I added guided practice prompts with step-by-step scaffolding, simplified definitions of AI, and incorporated concrete classroom examples. Accessibility was also enhanced by ensuring all videos included captions and transcripts.
Implementation will occur during District 1’s professional development workshops, with delivery through the LMS. Teachers will complete modules asynchronously over a two-week period, followed by a synchronous peer-review session where they share redesigned lesson plans. This blended approach ensures flexibility while fostering collaboration and accountability.
Evaluation will be conducted through pre- and post-assessments to measure changes in teacher confidence and student engagement. Student performance metrics such as test scores and project quality will be tracked over one semester. Teacher feedback surveys and analytics dashboards will provide ongoing evaluation data, ensuring the module’s effectiveness and informing future iterations.
Reflecting on this process, technology played a dual role as both the medium and the message. By embedding AI tools within the module itself, educators experienced firsthand how these technologies can transform instruction. Authoring tools enabled the creation of interactive, scenario-based learning experiences that would be impossible in static formats, while technology ensured scalability and consistent quality across multiple schools. One key lesson learned was that brevity with intentionality defines microlearning; every activity must be purposeful and directly tied to an objective. Experienced educators value efficiency, so designing short, high-impact modules required stripping away excess theory and focusing on practical application.
I am proud of how the module balances respect for teacher expertise with innovation. Rather than overwhelming educators with technology, the design scaffolds their learning and demonstrates how AI can enhance, not replace, their professional judgment. The alignment between objectives, activities, and assessments reflects purposeful instructional design. If I could change one aspect, I would incorporate more collaborative elements earlier in the module. While peer review is included at the end, embedding opportunities for teachers to co-design AI activities during the learning process would foster deeper engagement. This could be achieved by integrating breakout discussions or shared lesson repositories within the LMS.
For the Project Title, "AI In Classroom," the Authors and Contributors include unlimitedGIGs (YouTube) as the original content creator, with review and analysis conducted by Douglass Aaron Wilson. In the Context of the Project Work, this multimedia asset was reviewed to evaluate the integration of artificial intelligence within instructional environments. The project outlines how AI serves as a tool to address systemic performance gaps through targeted educational interventions. It explores the practical applications of AI in accelerating personalized learning while identifying the ethical limitations and privacy concerns that must be managed when deploying technological solutions at scale.
Regarding the Description of which phase(s) of IDD&E this product represents, the video primarily aligns with the Analysis and Implementation phases of the ADDIE model, as well as the evaluation of instructional delivery systems within the Seels and Glasgow framework. The Analysis phase is represented through the discussion of how AI provides real-time analytics to identify learning gaps and engagement issues before they escalate into larger problems. Furthermore, it touches on the Implementation phase by highlighting how AI automates routine instructional tasks, such as grading quizzes and sorting responses, which supports the delivery of instruction by freeing up time for more meaningful teacher-student interactions.
In a Short reflection and self-assessment of the product, reviewing this instructional asset reinforced the critical balance between technological efficiency and human oversight in complex learning and development programs. While AI enables highly personalized learning paths by analyzing data to recommend tailored resources, optimizing human performance requires more than automated data synthesis. The video's warning that an over-reliance on AI can erode professional judgment and overlook nuanced classroom dynamics is a critical takeaway, along with the reality that AI systems can introduce bias and raise student data privacy concerns. Engineering effective learning environments requires strategic execution and an analytical perspective to ensure these tools are applied ethically. Moving forward in directing cross-functional instructional design initiatives, these insights will serve as a reminder to advocate for AI as a supportive mechanism to scale efficiency, rather than a replacement for rigorous, human-centered evaluation and instructional leadership.
