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Maria Aristeidou; Simon Cross; Klaus-Dieter Rossade; Carlton Wood; Terri Rees; Patrizia Paci – Journal of Computer Assisted Learning, 2024
Background: Research into online exams in higher education has grown significantly, especially as they became common practice during the COVID-19 pandemic. However, previous studies focused on understanding individual factors that relate to students' dispositions towards online exams in 'traditional' universities. Moreover, there is little…
Descriptors: Higher Education, Computer Assisted Testing, COVID-19, Pandemics
Digital SAT® Score Relationships with Other Educational Measures: Early Convergent Validity Evidence
Marini, Jessica P.; Westrick, Paul A.; Young, Linda; Shaw, Emily J. – College Board, 2022
This study examines relationships between digital SAT scores and other relevant educational measures, such as high school grade point average (HSGPA), PSAT/NMSQT Total score, and Average AP Exam score, and compares those relationships to current paper and pencil SAT score relationships with the same measures. This information can provide…
Descriptors: Scores, College Entrance Examinations, Comparative Analysis, Test Format
Froehlich, Laura; Sassenberg, Kai; Jonkmann, Kathrin; Scheiter, Katharina; Stürmer, Stefan – Journal of Computer Assisted Learning, 2023
Background: The use of e-exams in higher education is increasing. However, the role of student diversity in the acceptance of e-exams is an under-researched topic. In the current study, we considered student diversity in terms of three sociodemographic characteristics (age, gender, and second language) and three dispositional student…
Descriptors: Student Diversity, Student Attitudes, Computer Assisted Testing, Student Characteristics
Devisakti, A.; Muftahu, Muhammad – International Journal of Information and Learning Technology, 2022
Purpose: The advancement of technology in the last decades transformed the education from mortar and brick into online teaching and learning. It also changed the assessments from paper-based to technology-supported assessments. This study aims to examine how technology support student's online assessments in higher education institutions from…
Descriptors: Educational Technology, Technology Uses in Education, Undergraduate Students, Expectation
Wang, Zhen; Cao, Yang; Gong, Shaoying – Journal of Educational Computing Research, 2023
Although learner characteristics have been identified as important moderator variables for feedback effectiveness, the question of why learners benefit differently from feedback has only received limited attention. In this study, we investigated: (1) whether learners' dominant goal orientation moderated the effects of computer-based elaborated…
Descriptors: Goal Orientation, Feedback (Response), Cues, Student Characteristics
Xin Wei – Educational Researcher, 2024
This study investigates the relationship between text-to-speech (TTS) usage and item-by-item performance in the 2017 eighth-grade National Assessment of Educational Progress (NAEP) math assessment, focusing on students with disabilities (SWDs), English language learners (ELLs), and their general education (GE) peers. Results indicate that all…
Descriptors: Assistive Technology, Students with Disabilities, English Language Learners, Regular and Special Education Relationship
Barkaoui, Khaled – Language Testing, 2019
This study aimed to examine the sources of variability in the second-language (L2) writing scores of test-takers who repeated an English language proficiency test, the Pearson Test of English (PTE) Academic, multiple times. Examining repeaters' test scores can provide important information concerning factors contributing to "changes" in…
Descriptors: Second Language Learning, Writing Tests, Scores, English (Second Language)
Yetter, Ibrahim H.; Livengood, Kimberly K.; Smith, Walter S. – Electronic Journal of Science Education, 2017
This study of science standards of all 50 states and 1958 American early adolescents asked whether there is agreement among states about a science topic, lunar phases, that appears in all recent national standards documents, is of cultural significance, and has been widely studied for misconceptions held by children and adults. Secondly, we asked…
Descriptors: State Standards, Science Instruction, Astronomy, Misconceptions
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
Pike, Gary R.; Hansen, Michele J.; Childress, Janice E. – Journal of College Student Retention: Research, Theory & Practice, 2014
The present research examined the extent to which pre-college characteristics, high school experiences, college expectations, and initial enrollment characteristics were related to graduation from college. Data from admission applications, the "ACT Compass" survey, and initial enrollment measures for Fall 2004 and Fall 2005 first-time…
Descriptors: Student Characteristics, Educational Experience, Correlation, Expectation
Huff, Kyle; Cline, Melinda; Guynes, Carl S. – American Journal of Business Education, 2012
Web-based testing has recently become common in both academic and professional settings. A web-based test is administered through a web browser. Individuals may complete a web-based test at nearly any time and at any place. In addition, almost any computer lab can become a testing center. It is important to understand the environmental issues that…
Descriptors: Computer Assisted Testing, Educational Technology, Computer Uses in Education, Internet
Wilson, Damian Vergara – Heritage Language Journal, 2012
This paper illustrates a method of item analysis used to identify discriminating multiple-choice items in placement data. The data come from two rounds of pilots given to both SHL students and Spanish as a Second Language (SSL) students. In the first round, 104 items were administered to 507 students. After discarding poor items, the second round…
Descriptors: Heritage Education, Graphs, Item Analysis, Correlation
Wise, Steven L.; Pastor, Dena A.; Kong, Xiaojing J. – Applied Measurement in Education, 2009
Previous research has shown that rapid-guessing behavior can degrade the validity of test scores from low-stakes proficiency tests. This study examined, using hierarchical generalized linear modeling, examinee and item characteristics for predicting rapid-guessing behavior. Several item characteristics were found significant; items with more text…
Descriptors: Guessing (Tests), Achievement Tests, Correlation, Test Items
Xu, Yuejin; Iran-Nejad, Asghar; Thoma, Stephen J. – Journal of Interactive Online Learning, 2007
The purpose of the study was to determine comparability of an online version to the original paper-pencil version of Defining Issues Test 2 (DIT2). This study employed methods from both Classical Test Theory (CTT) and Item Response Theory (IRT). Findings from CTT analyses supported the reliability and discriminant validity of both versions.…
Descriptors: Computer Assisted Testing, Test Format, Comparative Analysis, Test Theory
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection
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