Scoring high-dimensional assessments (e.g., > 15 traits) can be a challenging task. This paper introduces the multilabel neural network (MNN) as a scoring method for high-dimensional assessments. Additionally, it demonstrates how MNN can score the same test responses to maximize different performance metrics, such as accuracy, recall, or…

As the field of higher education has used several methods to assess college teaching, the validation of these measures and how they relate to each other has been sparse. This study drew on data from a multi-institutional study of 587 college courses to examine the efficacy of two methods of measuring college teaching (class observation and…

Practitioners and researchers interested in understanding student achievement, its predictors, and how it relates to other student outcomes are likely unaware of how the source information about achievement may offer subtly different pictures. This study applies multitrait-multimethod (MTMM) confirmatory factor analysis (CFA) within a structural…

The "Kobayashi Maru" is a training simulation that has its roots in the Star Trek series notable for its defining characteristic as a no-win scenario with no "correct" resolution and where the solution actually involves redefining the problem. Drawing upon these characteristics, we designed a board meeting simulation for an…

This paper examines how different test methods may tap different aspects of second language knowledge. It employs multiple-choice (MC) and constructed response (CR) items which yield distinct or convergent information in the computer delivered testing of English in its presentation of this factor. In order to examine the effects of test method, a…

Cultural differences between faculty and their students can create important challenges that affect the quality and efficacy of online teaching and learning. The objectives of this study were to: (a) create and pilot test an assessment for online faculty to measure culturally responsive teaching knowledge (CRT) and culturally responsive…