Test
In this phase of learning design, a sample group of users is selected to test the e-learning module. A research methodology is developed to identify the type of data to be collected for measuring the course’s impact. Based on the findings, the design can be refined further by adapting the methodology and making adjustments to the course content.
Research Methodology
The project’s research methodology outlines the types of data to be collected, such as quantitative data (e.g. average time to complete the course), qualitative data (e.g. user feedback, emotions, and behaviors), or a mixed approach. For this project , a qualitative approach was used to gather initial feedback from participants.
To assess participant’s feelings, attitudes, and behaviors toward the micro-learning strategy, a six-question questionnaire was developed. The questions focused on the use of micro-learning, AI, and performance support. Researcher reflections from the anonymous questionnaires are summarized in the memos below.
Results and Future Iteration
The initial feedback from the questionnaires was overwhelmingly positive. Participants appreciated the flexibility of micro-learning and its emphasis on breaking content into manageable chunks. They were also very receptive and saw the value of AI in learning, highlighting its ability to support immediate knowledge application through features like quizzes and generated scenarios, among other things.
With additional time, resources, and availability, further testing could be conducted to generate more robust results. If the findings remain positive, they could support micro-learning as an effective design principle for broader adoption within the mortgage industry. Below are some potential revisions to the course and research methodology.
Develop an interactive PDF using Adobe InDesign to create a virtual binder for seamless access to government regulations, complete with links to define technical terms and provide additional resources.
Further refine the AI chatbot, ensuring thorough testing and validation for accurate responses and intuitive interpretations of user queries.
Employ a mixed-methods approach, integrating both qualitative and quantitative data collection methods.
Conduct a second round of qualitative data collection through surveys administered weeks or months after the initial testing to assess whether users maintained positive perceptions of the micro-learning strategy.
Perform quantitative data analysis to evaluate the tangible impact of micro-learning, such as reduced training completion time without compromising—and potentially enhancing—performance.
Design testing with control groups (using standard training programs) and variable groups (using micro-learning modules) for both current employees and new hires.