Cheating on tests is not only an ethical issue, but also adversely affects test validity. In this study, we administered a questionnaire to working people in their 20s and 30s who had taken an employment examination via a web test. We then asked whether they had ever cheated on an employment examination using direct questioning and item count technique. The survey found that between 1.9% and 5.1% had experienced cheating. This percentage is not small. For web testing to become more widely used as a tool to properly measure examinees' abilities, it is necessary to further improve the methods of preventing and detecting cheating.

This study investigates the influence of nonverbal information and psychological factors on interview ratings in holistic admission process of Japanese universities. Mock interviews were conducted with 22 first-year students from a private university’s business administration department. An integrated analysis of interview ratings, nonverbal cues (personality traits, facial expressions, school life skills), and final grades revealed three key findings. First, school life skills had no relationship with interview ratings, while certain facial expressions had a direct relationship, and some personality traits related to ratings indirectly. Second, final grades were not linked to interview ratings but were directly related to school life skills. Third, although there was no direct relationship between interview ratings and final grades, an indirect link was found through shared personality traits. These findings contribute to the understanding of how nonverbal information and psychological factors influence interview evaluations in university admissions.

Due to the declaration of a state of emergency in the wake of the 2020 coronavirus pandemic, recording speech sounds for listening comprehension was impossible for two months. With this in mind, we investigated the feasibility of using text-to-speech (TTS) based on deep learning as an alternative method in an emergency. We created a test by synthesizing English speech using Google's Tacotron 2 based on the script for the listening section of The Common Test for University Admissions. In the experiment, 246 first-year students at national and public universities in the Tokyo metropolitan area answered a listening test with mixed synthesized speech. Along with the results of the experiment, we will also consider the advantages of using synthesized speech, which is not just a replacement for the recording process but also has the potential to be used for mass production of audio items.

This study examined how the acquisition of mathematical skills by the second year of junior high school can be explained by mathematical abilities and learning strategies at the sixth grade of elementary school, as well as by socioeconomic status and school districts at the first year of junior high school. Four attributes were identified: “calculation,” “conceptual understanding,” “geometric manipulation,” and “logical reasoning.” A cognitive diagnostic model incorporating explanatory variables was estimated using Bayesian inference with the MCMC method. The results show that students with higher mathematical abilities in sixth grade were 3 to 7 times more likely to acquire all attributes. Students with well-developed learning strategies in sixth grade had slightly higher odds of acquiring “calculation” and “conceptual understanding.” However, students receiving school financial aid in the first year of junior high school had approximately 30-40% lower odds of acquiring “calculation” and “conceptual understanding.” Even after controlling for these covariates, the odds of acquiring the attributes varied by up to six times across school districts.

As the competition for student recruiting among universities intensifies, both domestically and internationally, research has been conducted on marketing strategies implemented by higher education institutions. These studies can be classified into five categories: 1) marketing strategies, 2) marketing communication, 3) branding, 4) globalization, and 5) ethics in higher education marketing. By surveying relevant research within these categories, the main focal points can be extracted. These studies have demonstrated the broad scope of higher education marketing research, relying on marketing theories that have evolved in the business realm while also underscoring disparities between Japanese research and that of other countries. The study concludes by outlining the future direction of research on higher education marketing in Japan.

Item writing is one of the expensive and time-consuming processes in test development. Recently, automatic question generation using artificial intelligence has gained attention as a way to reduce the burden of item writing. Traditional automatic question generation methods have heavily relied on manually designed templates and rules, while question generation methods based on neural networks, including large language models, have recently become popular and have demonstrated the capability to generate high-quality items. Furthermore, advances in multimodal data processing technologies enable the generation of test items involving images, knowledge graphs, equations, programming code, and more. Additionally, controllability in automatic question generation over various aspects, such as difficulty and item types, has become another focus of recent research. Consequently, this paper provides an overview of such latest neural automatic question generation methods and discusses their limitations and future challenges.

Local independence is a fundamental assumption of item response theory (IRT), allowing the factorization of the joint distribution of responses. However, it’s often violated in real-world data due to model misspecification, environmental factors, structural dependencies, and shared factors within clusters, leading to local dependence (LD). Traditional LD diagnostics, such as Yen’s Q₃ and contingency table independence tests, have improved with resampling, and novel indices have emerged. Existing IRT models, which typically address dependencies through less interpretable parameters, have been extended to simultaneously handle person and item dependencies and represent complex structures while preserving interpretability via nuisance dimension projection and copula functions. This study reviews recent LD diagnostics and modeling improvements, highlighting key practical considerations and suggesting future research directions.