Prompt Engineering

This xAPI-enabled micro e-learning experience was created for curious lifelong learners who wanted to dip their toes in the new wave of generative AI applications to get desired responses in their personal or professional lives. Ask me how a curious teenager and a senior citizen inspired me to cough up this project!

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My audience included a diverse range of age groups, experiences, and skill levels. I determined the goal and the base skill level after conducting the learners’ analysis. The goal was to learn the basics of writing effective prompts to get the desired response. After brainstorming some ideas I designed a customized solution.


My learners were avid users of search engines which was their base skill level and the device they all had in common was a cell phone. There was a lack of knowledge. After evaluating some ideas, I imagined that the best solution was to create a gamified bite-size learning activity. In order to cater to a wide range of audiences, in my gamified e-learning activity I gave choices to learners on how to engage with the content and access it whenever and wherever they want.

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My Process

I started by conducting the learners' analysis. While the entire process was underpinned by SAM (Successive Approximation Model). I also used the ARCS model of motivation for content development. In my preparation phase, I conducted interviews with learners, collected background information on learners and created a storyboard. After that, it was a fast-paced iterative design and development phase that included feedback from fellow instructional designers. The final version was released and improved after feedback from end-users.

Preparation Phase

I interviewed and observed the end-users to learn about their strengths and weaknesses, and their prior knowledge. I  carefully mapped out goals and outlined the text, visuals, and programming details for each screen using a text-based storyboard in my preparation phase of the project. Although there was a slight change in the plan after the iterative development phase, having this document was important in making sure to keep the goal and end user in mind from the start. 

Snapshot of Storyboard

Iterative Design Phase

During this phase, I used Adobe Firefly and ChatGPT to generate images and some parts of content for my course respectively. I shortlisted a few images and finalized them after receiving feedback from other instructional designers in the community. I also adapted the course content to suit my learners' needs. I selected and changed content, based on my understanding of the learners' prior knowledge. I imagined that to make learning more meaningful and engaging for all ages and ability levels gamified format is a great strategy to use for a piece of text-based information that can be connected to learners' prior knowledge. I designed feedback screens with visuals for better retention and to reach out to all learning styles. I also used visual cues by using a different color in the example text to match the information in the tip.

Iterative Development Phase

In this final stage, I brought everything together. I used Articulate Storyline 360 for this purpose. This phase went through many feedbacks and iterations. I developed the first version of my project and then gave it to end-users for feedback. Based on the feedback I made changes to the design and content of the project. For example, I used tab interaction to provide access to tips for effective prompt writing before the challenge as well. I also used lighter shades of buttons to emphasize the action I wanted users to take.

Full Development

I also used xAPI triggers to collect user data and connect to the Veracity Learning Record System (LRS). This data would help me analyze user performance data and provide insights on future development and improvement of this project. I chose not to embed chatGPT into the project because of some security and privacy concerns.

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