Everett Rogers' Diffusion of Innovation Curve is a model that categorizes adopters of innovations into five segments based on their readiness and speed to adopt new technologies and ideas. These segments are Innovators, Early Adopters, Early Majority, Late Majority, and Laggards. This model helps understand how different groups within a society or organization adopt new ideas, which can significantly impact strategies for managing change. It provides insights into the characteristics of each group, aiding in tailored communication strategies to enhance the adoption process (Rogers, 1962).
The Early Majority in Rogers' Diffusion of Innovation Curve are individuals who adopt new technologies and ideas after the Innovators and Early Adopters have done so. Characteristically, the Early Majority are more deliberate before adopting innovations, often requiring evidence that the innovation works and offers practical benefits. They tend to be more connected within their community than the earlier groups and rely heavily on recommendations and evidence from peers whom they trust. Their cautious approach helps ensure that any new technology is stable and proven before they adopt it, acting as a bridge between the more enthusiastic early adopters and the more skeptical later adopters (Rogers, 1962).
I identify with the Early Majority group. For the last 20 years, I have worked primarily on existing enterprise eLearning platforms. My work has focused on methodically integrating newer technologies once they demonstrate clear, tangible benefits. This approach requires a measured, cautious adoption strategy to minimize disruption and maximize the value of improvements to both learners and the educational framework. Understanding my position on the adoption curve tailors my professional development and project selection, directing me toward areas ripe for innovation. One such area is PHP’s development and hosting ecosystem.
PHP remains a cornerstone of web development, powering a substantial portion of the web. As of the latest reports, PHP is utilized by 75% of all websites whose server-side programming is known, underscoring its pervasive use and significance in the digital landscape (W3Techs, 2023). Popular Learning Management Systems like Moodle are built on PHP, highlighting the language’s enduring role in educational technology. There is a pressing need for modernization among aging PHP web applications, ensuring they remain secure, efficient, and capable of integrating with modern technologies to meet evolving user expectations and technological standards.
Cautiously merging the new with the old is exemplified by my advocacy of the Roadrunner Application Server. Roadrunner incorporates the speed and efficiency of Golang with the widespread, established use of PHP. Roadrunner enhances PHP's capabilities by keeping PHP workers in memory and thus reducing the overhead associated with the typical start-up and teardown of PHP processes for each request. This improves performance and extends PHP's lifecycle in the modern web ecosystem by combining it with contemporary technology. (Roadrunner Documentation, 2021).
In the early 2000s, I deployed and contributed to developing the ATutor Learning Content Management System (LCMS) as part of a state-wide eLearning initiative in Oklahoma. ATutor was selected because of its commitment to accessible content creation and user experience (ATutor Documentation, 2003). The open-source project behind the ATutor LCMS has stalled recently and needs a codebase update and renewed development interest. Roadrunner’s unique environment allows the existing ATutor PHP codebase to thrive while opening the door to Golang development alongside the original feature set.
Building on this foundation, I am pursuing a project to fork and modernize ATutor using Golang and the Roadrunner application server. This project aims to revitalize ATutor by enhancing its performance and scalability, ensuring it continues serving educational needs effectively. By integrating Roadrunner, the LCMS will benefit from faster processing times and reduced resource consumption, critical for handling contemporary web traffic and user demands. Even as I list the benefits, a little voice asks, “What projects has it been used on? How many concurrent connections are supported? Who vouches for this stack?” Those questions prove that I am certainly not an Early Adopter but also more of a risk taker than a Late Majority professional.
For risk-averse Early Majority thinkers, a lab or simulated environment for skill development is preferred. I’ve started designing a test environment for the ATutor project to assess code changes' reliability, scalability, and maintainability. This environment simulates real-world HTTP traffic, allowing comprehensive testing across various codebases. This systematic testing not only supports the integration of new features but also safeguards the stability and performance of the upgraded system.
When planning HTTP load testing to ensure the robustness of code changes, particularly for something as critical as a Learning Management System like ATutor, selecting the right tools is crucial. Apache JMeter is highly recommended for its ability to simulate heavy loads on static or dynamic resources and analyze overall performance under different load types. Another excellent choice is Gatling, known for its high performance and detailed analytics capabilities. Gatling’s efficient resource usage and powerful scripting capabilities make it a preferred option for simulating complex user behaviors in web applications.
The psychological and motivational guardrails typical of the Early Majority mindset influence my selection of new tools and the development of a testing framework. Recognizing and understanding my risk tolerance in adopting technology is essential for my efficacy and satisfaction in learning design and instructional technology integration. This reflective awareness of my position on Rogers' adoption curve is instrumental in guiding my professional development and ensuring that innovations align with practical, established benefits in educational settings.
References
Rogers, E. M. (1962). Diffusion of Innovations. Free Press.
Roadrunner Documentation. (2021). Retrieved from https://docs.roadrunner.dev/docs
ATutor Documentation. (2003). Retrieved from https://atutor.github.io/atutor/docs/
W3Techs. (2023). Usage Statistics of Server-side Programming Languages for Websites. Retrieved from https://w3techs.com/technologies/overview/programming_language