In Chapter 7, the author introduces both content analysis and basic statistical analysis to help evaluate the effectiveness of assessments. The focus of the chapter is on guidelines for creating and evaluating reading and listening inputs and selected response item types, particularly multiple-choice items that accompany these inputs. The author guides readers through detailed evaluations of reading passages and accompanying multiple-choice items that need major revisions. The author discusses generative artificial intelligence as an aid for drafting inputs and creating items and includes an appendix which guides readers through the use of ChatGPT for this purpose. The author also introduces test-level statistics, including minimum, maximum, range, mean, variance, standard deviation, skewness, and kurtosis. The author shows how to calculate these statistics for an actual grammar tense test and includes an appendix with detailed guidelines for conducting these analyses using Excel software.

In Chapter 5, the author lays out the principles of uniformity – the consistency of the setting, content, and scoring procedures – and reliability, which is the consistency and stability of assessment scores. The chapter details the aspects of setting, content, and scoring procedures in various assessment contexts and what measures test users should take to maintain their consistency across test takers and test administrations. The chapter includes a discussion of the role of test accommodations, and how researchers can balance the needs of test takers with the principles of uniformity and reliability. An important feature of the chapter is the introduction of assistive technologies, such as generative artificial intelligence for helping ensure uniformity in an assessment context. The chapter concludes with a brief introduction to the concepts of test-retest, parallel forms, and internal reliability.

In Chapter 10, the author introduces performance assessments: test activities that require test takers to use language in a manner similar to how they use language in the target language use situation. The chapter describes and discusses the appropriate uses of several types of tasks: prepared oral presentation, knowledge-based, retell, summary, synthesis, roleplay, interview, paired oral discussion, group oral discussion, elicited imitation, and picture tasks. The chapter also discusses the delivery of performance assessment tasks, including face-to-face, virtual, and computerized delivery models. The author compares and contrasts oral communication assessments in video-mediated and virtual environments. The chapter compares spoken dialog systems, electronic systems that can orally interact with humans, to complex language-processing models, such as ChatGPT, that generate language from large databases. The chapter includes an appendix for using ChatGPT to help create a performance assessment.