Computer adaptive testing to assess impairing behavioral health problems in emergency department patients

Study Objective: To assess the prevalence of several impairing behavioral health domains in stable patients presenting to the emergency department (ED) through the use of computer adaptive testing and the association among the domains, standard assessments, and ED utilization. Methods: This was a single-center observational study of 828 randomly selected adult patients presenting to the ED from May 2019 to March 2020. The main outcomes of interest were the self-administered, validated computer adaptive assessments of suicidality, depression, anxiety, PTSD, and substance abuse using computer adaptive testing, the CAT-MHTM. We estimated the association among the CAT-MHTM subscales, standard assessments, and the number of ED visits in the year prior and 30 days after enrollment. Results: The proportion of those who scored above the threshold of low/mild risk were: 24.1% (suicidality), 8.3% (depression), 16.5% (anxiety), 12.3% (PTSD), and 20.4% (substance use). While the CAT-MHTM subscales were highly correlated with other self-report assessments, they were not highly associated with standard ED assessments of suicidality. When examining associations with ED use, for example, individuals who had two or more ED visits in the prior year had 51% increased odds of being in the intermediate-high suicide risk category (95% Confidence Interval [CI], 1.03-2.23) compared to those with zero prior ED visits. Conclusion: The CAT-MHTM can document the high prevalence of mental health conditions in the ED, which were missed by standard ED practices. Mental health problems are associated with ED utilization in a population of patients presenting largely for somatic complaints.

Simulated Computer Adaptive Testing Administration with Remote Proctoring for Offsite Assessment in Mathematics

<div><p>This study examines remote proctoring as emerging practice for ascertaining the validity of offsite test administration regarding test security. While Computer Adaptive Testing (CAT) has the potentials for greater precision in determining examinees ability level, its gains can be jeopardized with off-site testing if the test is not ensured. This study simulated CAT assessment while focusing on item administration, varying the option of using pre-test items and how it impacts students' ability estimation and item exposure. Monte-Carlo simulation was employed to generate data for answering the research questions raised for the study. The study's findings revealed that CAT administration was more consistent with no pre-test items once tightly controlled at ±2theta level, upon which recommendations were made. This finding is particularly germane, with more institutions moving their assessments online and rapidly becoming a new normal as an aftermath of the Covid-19 pandemic.</p></div><div><br></div>The data for this study were generated from computer simulations using SimulCAT, a free software package designed by Dr. K. C. T. Han of Graduate Management Admission Council.<p></p>

Simulated Computer Adaptive Testing Administration with Remote Proctoring for Offsite Assessment in Mathematics

<div><p>This study examines remote proctoring as emerging practice for ascertaining the validity of offsite test administration regarding test security. While Computer Adaptive Testing (CAT) has the potentials for greater precision in determining examinees ability level, its gains can be jeopardized with off-site testing if the test is not ensured. This study simulated CAT assessment while focusing on item administration, varying the option of using pre-test items and how it impacts students' ability estimation and item exposure. Monte-Carlo simulation was employed to generate data for answering the research questions raised for the study. The study's findings revealed that CAT administration was more consistent with no pre-test items once tightly controlled at ±2theta level, upon which recommendations were made. This finding is particularly germane, with more institutions moving their assessments online and rapidly becoming a new normal as an aftermath of the Covid-19 pandemic.</p></div><div><br></div>The data for this study were generated from computer simulations using SimulCAT, a free software package designed by Dr. K. C. T. Han of Graduate Management Admission Council.<p></p>

The problem of increasing the efficiency of computer adaptive testing for students in higher educational establishments

O desenvolvimento de testes adaptativos baseia-se em levar em conta as características individuais predominantes dos estudantes, ou seja, as características de estilo da atividade cognitiva, tornando possível aumentar a eficácia dos testes, torná-los mais atraentes e, finalmente, contribuir para um aprendizado mais eficaz. Neste contexto, o artigo apresenta os resultados de um estudo sobre a eficácia dos testes adaptativos de computador dos estudantes, baseado na consideração das características estilísticas de sua atividade cognitiva. Com base em informática e programação, foram desenvolvidas variações de itens de teste, as quais foram oferecidas a estudantes de graduação e pós-graduação da Herzen State Pedagogical University of Russia and ITMO University Saint-Petersburg. No decorrer do estudo, foi revelado que, como o resultado da aprovação nos testes adaptativos demonstraram uma melhora estável, a conveniência e a possibilidade de construir testes baseados na consideração das características estilísticas da atividade cognitiva dos estudantes foi comprovada experimentalmente. Da mesma forma, comprovou-se a hipótese sobre a eficácia do uso de questões do teste adaptativo em comparação com outros tipos de questões

A Review of Standardised Assessment Development Procedure and Algorithms for Computer Adaptive Testing: Applications and Relevance for Fourth Industrial Revolution

Teaching and learning have gone online in response to the pandemic, which reveals the need for accurately tailored educational assessments to ascertain the extent to which learning outcomes or objectives are achieved. Computer Adaptive Testing (CAT) is a technology-driven form of assessment that tailors items to a candidate's ability level with empirically proven benefits over the fixed-form computer based test. A systematic review was employed which shows that item bank is a key requirement for CAT and the items must through a rigorous item development process to ensure and maintain quality in terms of content, criterion constructs and internal consistency, determining the psychometric validation of behavioural measures while leveraging on variances of Item Response Theory (IRT). Following the item development stage is the need to compile validated items into administrable forms using advanced computer software for automatic test assembly and administration, such as FastTest which allows specifying empirically tried algorithms for CAT from start to termination of the test. This helps to ensure that assessment properly leverages the advantages that CAT holds. Furthermore, the review revealed that CAT has been widely applied with large-scale testing in various fields by educational, health and psychological professionals utilising different IRT models; however only in developed countries. This brings to bear the need for adoption in other parts of the world, for improvements in educational assessments. The interjections of 4IR with AI considering emerging technology aids the CAT algorithm for achieving expert and knowledge-based systems, being a requirement for survival in today’s world.