provide a two paragraph response to this post and Extend or constructively challenge this post and tell if you are extending or challenging: My doctoral research focuses on how educational leaders adopt machine learning using the Technology Acceptance Model (Davis, 1989). For this type of study, Likert-scale measures such as perceived usefulness and perceived ease of use are especially useful. Within this context, t-tests can provide insight into specific comparisons. For example, I might test whether perceived usefulness improves after an onboarding program or whether administrators and IT managers differ in their average intention to adopt machine learning tools. These types of tests complement correlational or regression analyses by providing straightforward evidence about group mean differences (Green & Salkind, 2017). Hypothetical Examples for Each t-Test One-sample t-test. I could test whether the mean perceived usefulness score among K-12 administrators is greater than the neutral midpoint of 3.0 on a 5-point scale. This would show whether leaders see value in adopting machine learning beyond a neutral position (Green & Salkind, 2017). Paired-samples t-test. Another example would be measuring whether IT managers' perceived usefulness scores increase from pre-training to 30 days after training on machine learning dashboards. This approach would assess the effect of training within the same group (Green & Salkind, 2017). Independent-samples t-test. Finally, I could test