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Endang Susantini; Yurizka Melia Sari; Prima Vidya Asteria; Muhammad Ilyas Marzuqi – Journal of Education and Learning (EduLearn), 2025
Assessing preservice' higher order thinking skills (HOTS) in science and mathematics is essential. Teachers' HOTS ability is closely related to their ability to create HOTS-type science and mathematics problems. Among various types of HOTS, one is Bloomian HOTS. To facilitate the preservice teacher to create problems in those subjects, an Android…
Descriptors: Content Validity, Mathematics Instruction, Decision Making, Thinking Skills
Backes, Ben; Cowan, James – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2020
Prior work has documented a substantial penalty associated with taking the Partnership for Assessment of Readiness for College and Careers (PARCC) online relative to on paper (Backes & Cowan, 2019). However, this penalty does not necessarily make online tests less useful. For example, it could be the case that computer literacy skills are…
Descriptors: Predictive Validity, Test Validity, Computer Assisted Testing, Comparative Analysis
Peltier, Corey; Vannest, Kimberly J.; Tomaszewski, Brianne R.; Morin, Kristi; Sallese, Mary Rose; Pulos, Joshua M. – Exceptionality, 2022
The current study examined the criterion validity of a computer adaptive universal screener with an end-of-year state mathematics assessment using extant data provided by a local education agency. Participants included 1,195 third through eighth graders. Correlational analyses were used to report predictive and concurrent validity coefficients for…
Descriptors: Adaptive Testing, Computer Assisted Testing, Screening Tests, Mathematics Tests
Nina Charlotte Johanna Welsandt; Fabio Fortunati; Esther Winther; Hermann Josef Abs – Empirical Research in Vocational Education and Training, 2024
Background: Authentic situations are considered a source of learning due to their real world relevance. This can encourage learners to acquire new knowledge. Increasing digitisation and associated resources, such as professional development opportunities for teachers, technology tools, or digital equipment for schools enable the development and…
Descriptors: Test Construction, Test Validity, Evaluation, Educational Technology
Ying Xu; Xiaodong Li; Jin Chen – Language Testing, 2025
This article provides a detailed review of the Computer-based English Listening Speaking Test (CELST) used in Guangdong, China, as part of the National Matriculation English Test (NMET) to assess students' English proficiency. The CELST measures listening and speaking skills as outlined in the "English Curriculum for Senior Middle…
Descriptors: Computer Assisted Testing, English (Second Language), Language Tests, Listening Comprehension Tests
Sarintan N. Kaharu; Yusdin Gagaramusu; Azizah Azizah; Nurul Kamisani; Nurgan Tadeko; Jusman Mansyur – Pegem Journal of Education and Instruction, 2024
This study aims to develop an online test that can be used to characterize students' conception of objects in static fluid. The test developed by carried out several stages, namely: modified previous essay test and formed the Tier-1 of multiple-choice questions with options taken from the findings previous studies; combined the reasons for…
Descriptors: Test Construction, Scientific Concepts, Concept Formation, Computer Assisted Testing
Latifi, Syed; Gierl, Mark – Language Testing, 2021
An automated essay scoring (AES) program is a software system that uses techniques from corpus and computational linguistics and machine learning to grade essays. In this study, we aimed to describe and evaluate particular language features of Coh-Metrix for a novel AES program that would score junior and senior high school students' essays from…
Descriptors: Writing Evaluation, Computer Assisted Testing, Scoring, Essays
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
Porter, Tenelle; Molina, Diego Catalán; Blackwell, Lisa; Roberts, Sylvia; Quirk, Abigail; Duckworth, Angela L.; Trzesniewski, Kali – Journal of Learning Analytics, 2020
Mastery behaviours -- seeking out challenging tasks and continuing to work on them despite difficulties -- are integral to achievement but difficult to measure with precision. The current study reports on the development and validation of the computer-based persistence, effort, resilience, and challenge-seeking (PERC) task in two demographically…
Descriptors: Mastery Learning, Resilience (Psychology), Difficulty Level, Computer Assisted Instruction
Goodwin, Amanda P.; Petscher, Yaacov; Tock, Jamie; McFadden, Sara; Reynolds, Dan; Lantos, Tess; Jones, Sara – Assessment for Effective Intervention, 2022
Assessment of language skills for upper elementary and middle schoolers is important due to the strong link between language and reading comprehension. Yet, currently few practical, reliable, valid, and instructionally informative assessments of language exist. This study provides validation evidence for Monster, P.I., which is a gamified,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Language Tests, Vocabulary
Myers, Matthew C.; Wilson, Joshua – International Journal of Artificial Intelligence in Education, 2023
This study evaluated the construct validity of six scoring traits of an automated writing evaluation (AWE) system called "MI Write." Persuasive essays (N = 100) written by students in grades 7 and 8 were randomized at the sentence-level using a script written with Python's NLTK module. Each persuasive essay was randomized 30 times (n =…
Descriptors: Construct Validity, Automation, Writing Evaluation, Algorithms
Schneider, M. Christina; Agrimson, Jared; Veazey, Mary – Educational Measurement: Issues and Practice, 2022
This paper presents results of a score interpretation study for a computer adaptive mathematics assessment. The study purpose was to test the efficacy of item developers' alignment of items to Range Achievement-Level Descriptors (RALDs; Egan et al.) against the empirical achievement-level alignment of items to investigate the use of RALDs as the…
Descriptors: Computer Assisted Testing, Mathematics Tests, Scores, Grade 3
Los, James E.; Witmer, Sara E.; Roseth, Cary J. – School Psychology Review, 2022
Scores from computer-based tests are increasingly used to inform a variety of school- and student-level decisions. An underlying assumption is that the associated scores represent effortful responding by each student with respect to the tasks presented. An innovative method for examining evidence for this assumption involves an examination of item…
Descriptors: Student Motivation, Tests, Middle School Students, Computer Assisted Testing
New York State Education Department, 2023
The instructions in this manual explain the responsibilities of school administrators for the New York State Testing Program (NYSTP) Grades 3-8 English Language Arts and Mathematics Tests. School administrators must be thoroughly familiar with the contents of the manual, and the policies and procedures must be followed as written so that testing…
Descriptors: Testing Programs, Mathematics Tests, Test Format, Computer Assisted Testing
Russo-Ponsaran, Nicole M.; McKown, Clark; Karls, Ashley; Wu, Irene Y. H. – Grantee Submission, 2021
Virtual Environment for Social Information Processing (VESIP™) is a web-based social information processing assessment developed for youth in grades 3-7. VESIP was developed to address: (1) the broader assessment of social information processing in a variety of socially challenging situations; and (2) the need for technically strong and scalable…
Descriptors: Computer Assisted Testing, Interpersonal Competence, Computer Simulation, Test Reliability