Evaluation is a cornerstone topic in NLP. However, many criticisms have been raised about the community’s evaluation practices, including a lack of human-centered considerations about people’s needs for language technologies and their actual impact on people. This “evaluation crisis” is exacerbated by the recent development of large generative models with diverse and uncertain capabilities. This tutorial aims to inspire more human-centered evaluation in NLP by introducing perspectives and methodologies from human-computer interaction (HCI), a field concerned primarily with the design and evaluation of technologies. The tutorial will start with an overview of current NLP evaluation practices and their limitations, then introduce the “toolbox of evaluation methods” from HCI with varying considerations such as what to evaluate for, how generalizable the results are to the real-world contexts, and pragmatic costs to conduct the evaluation. The tutorial will also encourage reflection on how these HCI perspectives and methodologies can complement NLP evaluation through Q&A discussions and a hands-on exercise.