## 5 Discussion
### Comparison with Alternative Methods  
The traditional experimental determination of \(g\) often relies on specialized equipment like photogate timers or handheld stopwatches, posing challenges in achieving precise time interval measurements, especially at sub-second scales. In contrast, the methodology presented in this study leverages the built-in microphone of a smartphone for precise time measurements during free fall experiments. Comparison with conventional sensor-based methods reveals distinctive advantages of utilizing smartphone audio recording. The smartphone's ubiquitous presence and integrated capabilities offer a more accessible and convenient approach to experimental physics, particularly in educational settings where accessibility to specialized equipment might be limited. This method obviates the need for additional costly equipment, streamlining the experimental setup and reducing resource constraints in educational laboratories. Furthermore, the integration of SPARKvue, facilitating real-time display and analysis of sound parameters like sound level, sound intensity, and period values, enhances the experimental process. This seamless integration provides a user-friendly interface, enabling direct and accurate time measurements through sound recordings, eliminating the complexities associated with traditional sensor setup and calibration. Moreover, while traditional methods require specific equipment calibration and meticulous setup, the smartphone-based approach offers a more straightforward setup process. The smartphone's capability to capture and analyze audio signals associated with the initiation and termination of free fall events simplifies the experimental procedure, making it more accessible to a wider spectrum of learners without compromising on accuracy. However, it is essential to acknowledge that this method might present limitations in certain experimental conditions or environments where ambient noise or variability in sound emissions could affect the accuracy of time measurements. Additionally, while our study exhibits promising results, further comparative studies across diverse experimental scenarios could provide a comprehensive evaluation of its efficacy in various contexts. Therefore, it is sufficient to conclude that while traditional sensor-based methods have long been the cornerstone of experimental physics, the adoption of smartphone audio recording represents a novel and accessible alternative. The comparison highlights the advantages of smartphone-based methodologies, showcasing their potential to revolutionize experimental setups, particularly in educational environments, by offering a balance between accessibility, accuracy, and simplicity. Table 2 delineates the prevailing methodologies employed in gauging the \(g\), notably through free fall and pendulum experiments. These methods deploy a spectrum of sensors--acceleration, microphone, IR, ultrasonic, proximity, magnetometer, and ambient light sensors--integrated within contemporary smartphones or interfaced with external apparatus such as personal computers and Arduino boards. Our conducted experiment yields a remarkable relative error of merely 0.18%, a notable achievement eclipsing the majority of scholarly references in this domain. Notably, Reference [32] reports a marginally lower value of 0.10%. Nevertheless, our proposed approach heralds greater adaptability and elegance in execution. The uncertainty range of our experiment, \(\pm\)0.01% m/s\({}^{2}\), stands narrower than that of Reference [32], signifying heightened precision in delineating gravitational acceleration. This affirms the constricted scope around the computed value, thereby augmenting the accuracy and trustworthiness of our proposed framework. Our methodology stands out for its precision and adaptability in ascertaining gravitational acceleration. While Reference [32] marginally reduces relative error, our approach distinguishes itself through its simplicity and a narrower uncertainty range, indicative of heightened precision.