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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
Ahmad, Nor Shafrin; Zaharudin, Rozniza; Khairani, Ahmad Zamri – International Journal of Educational Methodology, 2022
Anger is a topic that requires intervention from teachers, counsellors, psychologists, parents, and all communities. The expressions of anger are subjective and sometimes hard to identify. Thus, anger should be measured more objectively, while the expressions need to be examined closely. The purpose of this study is to provide valid confirmation…
Descriptors: Psychological Patterns, Test Validity, Psychometrics, Adolescents
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
Sher Muhammad Awan; Rashid Hussain; Khalid Saleem – Pakistan Journal of Distance and Online Learning, 2024
The objective of this study was to find effect of Jazz smart classroom's online quiz on academic achievement of students at secondary school level. Experimental design was used in which two groups were selected one was control and other was experimental group. Experimental group was given a treatment of six weeks by using Jazz Smart Classroom's…
Descriptors: Educational Technology, High School Students, Computer Assisted Testing, Academic Achievement
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
Jeremiah T. Stark – ProQuest LLC, 2024
This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…
Descriptors: High School Students, Graduation Rate, Predictor Variables, Predictive Validity
Yue Huang; Joshua Wilson – Journal of Computer Assisted Learning, 2025
Background: Automated writing evaluation (AWE) systems, used as formative assessment tools in writing classrooms, are promising for enhancing instruction and improving student performance. Although meta-analytic evidence supports AWE's effectiveness in various contexts, research on its effectiveness in the U.S. K-12 setting has lagged behind its…
Descriptors: Writing Evaluation, Writing Skills, Writing Tests, Writing Instruction
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
Larranaga, Mikel; Aldabe, Itziar; Arruarte, Ana; Elorriaga, Jon A.; Maritxalar, Montse – IEEE Transactions on Learning Technologies, 2022
In a concept learning scenario, any technology-supported learning system must provide students with mechanisms that help them with the acquisition of the concepts to be learned. For the technology-supported learning systems to be successful in this task, the development of didactic material is crucial--a hard task that could be alleviated by means…
Descriptors: Computer Assisted Testing, Science Tests, Multiple Choice Tests, Textbooks
Lei Jiang; Na Yu – Education and Information Technologies, 2024
This research aims to address the challenges of digital transformation in education by understanding the digital competence of teachers through a mixed-methods approach. The grounded theory is employed to develop the Teachers' Digital Competence Model (TDCM), which is structured around three facets: development, pedagogy, and ethics. Within these…
Descriptors: Educational Technology, Teacher Competencies, Technological Literacy, Ethics
Katrin Klingbeil; Fabian Rösken; Bärbel Barzel; Florian Schacht; Kaye Stacey; Vicki Steinle; Daniel Thurm – ZDM: Mathematics Education, 2024
Assessing students' (mis)conceptions is a challenging task for teachers as well as for researchers. While individual assessment, for example through interviews, can provide deep insights into students' thinking, this is very time-consuming and therefore not feasible for whole classes or even larger settings. For those settings, automatically…
Descriptors: Multiple Choice Tests, Formative Evaluation, Mathematics Tests, Misconceptions
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
Delnoij, Laurie E. C.; Janssen, José P. W; Dirkx, Kim J. H.; Martens, Rob L. – International Journal of Assessment Tools in Education, 2022
Informed study decisions are pivotal for student retention in higher online education. A self-assessment prior to enrolment has been proposed as a promising approach to enable informed decision-making and to build resources for retention. To determine whether such a self-assessment affects the decision-making process as intended, thorough and…
Descriptors: Computer Assisted Testing, Self Evaluation (Individuals), Decision Making, Test Validity
Bernis Sütçübasi; Tugçe Balli; Herbert Roeyers; Jan R. Wiersema; Sami Çamkerten; Ozan Cem Öztürk; Baris Metin; Edmund Sonuga-Barke – Journal of Attention Disorders, 2025
Objective: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of intrinsic patterns of brain connectivity revealed during resting state using machine learning…
Descriptors: Elementary School Students, Secondary School Students, Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorders