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Araneda, Sergio; Lee, Dukjae; Lewis, Jennifer; Sireci, Stephen G.; Moon, Jung Aa; Lehman, Blair; Arslan, Burcu; Keehner, Madeleine – Education Sciences, 2022
Students exhibit many behaviors when responding to items on a computer-based test, but only some of these behaviors are relevant to estimating their proficiencies. In this study, we analyzed data from computer-based math achievement tests administered to elementary school students in grades 3 (ages 8-9) and 4 (ages 9-10). We investigated students'…
Descriptors: Student Behavior, Academic Achievement, Computer Assisted Testing, Mathematics Achievement
Betts, Joe; Muntean, William; Kim, Doyoung; Kao, Shu-chuan – Educational and Psychological Measurement, 2022
The multiple response structure can underlie several different technology-enhanced item types. With the increased use of computer-based testing, multiple response items are becoming more common. This response type holds the potential for being scored polytomously for partial credit. However, there are several possible methods for computing raw…
Descriptors: Scoring, Test Items, Test Format, Raw Scores
Steedle, Jeffrey T.; Cho, Young Woo; Wang, Shichao; Arthur, Ann M.; Li, Dongmei – Educational Measurement: Issues and Practice, 2022
As testing programs transition from paper to online testing, they must study mode comparability to support the exchangeability of scores from different testing modes. To that end, a series of three mode comparability studies was conducted during the 2019-2020 academic year with examinees randomly assigned to take the ACT college admissions exam on…
Descriptors: College Entrance Examinations, Computer Assisted Testing, Scores, Test Format
Andrea Cedeno – ProQuest LLC, 2022
The relationship between computer-based and paper-based testing may vary. Students with special needs may or may not perform better on computer-based testing compared to paper-based testing. Over the past few decades, computers and technology have increased in society and in classrooms. The use of technology has increased during the era of the…
Descriptors: Computer Assisted Testing, Test Format, Special Needs Students, Reading Comprehension
Edwin Ambrosio – ProQuest LLC, 2022
Assessments are some of the most common tools used to evaluate student learning. While exams have always been a part of evaluating how well students learn and retain information, the most effective way to administer them has always been debated. However, remarkably few studies have compared online and paper testing, and even fewer have examined…
Descriptors: Computer Science Education, Computer Assisted Testing, Test Format, Performance
Shahid A. Choudhry; Timothy J. Muckle; Christopher J. Gill; Rajat Chadha; Magnus Urosev; Matt Ferris; John C. Preston – Practical Assessment, Research & Evaluation, 2024
The National Board of Certification and Recertification for Nurse Anesthetists (NBCRNA) conducted a one-year research study comparing performance on the traditional continued professional certification assessment, administered at a test center or online with remote proctoring, to a longitudinal assessment that required answering quarterly…
Descriptors: Nurses, Certification, Licensing Examinations (Professions), Computer Assisted Testing
Abdullah Albalawi – Vocabulary Learning and Instruction, 2024
Despite the substantial expansion in vocabulary research since the 1980s, we still know very little about how vocabulary develops over time and what factors influence this development. This methodological overview discusses key issues and considerations in vocabulary breadth growth assessment to help advance research in this area. The report…
Descriptors: Vocabulary Development, Teaching Methods, Language Tests, Test Use
Provasnik, Stephen – Large-scale Assessments in Education, 2021
This paper presents the concepts and observations in the author's keynote address at the May 2019 "Opportunity versus Challenge: Exploring Usage of Log-File and Process Data in International Large-Scale Assessments" conference in Dublin, Ireland. This paper recaps briefly some key points that emerged at the December 2018 ETS symposium on…
Descriptors: Data Collection, Cognitive Processes, Ethics, Student Evaluation
Lemmo, Alice – International Journal of Science and Mathematics Education, 2021
Comparative studies on paper and pencil--and computer-based tests principally focus on statistical analysis of students' performances. In educational assessment, comparing students' performance (in terms of right or wrong results) does not imply a comparison of problem-solving processes followed by students. In this paper, we present a theoretical…
Descriptors: Computer Assisted Testing, Comparative Analysis, Evaluation Methods, Student Evaluation
Greg Gaynor; Kevin T. Wynne; Ting Zhang; Daniel Gerlowski; Joel N. Morse – Journal of Economic Education, 2024
The authors of this article examine the effect of online proctoring on exam scores with samples of proctored and unproctored students in an upper-level economics class. They document a proctoring discount (i.e., the tendency for lower scores on proctored exams versus on unproctored exams) and a relationship with students' perceptions measured by…
Descriptors: Computer Assisted Testing, Stress Variables, Economics Education, Online Courses
Janse van Rensburg, Cecile; Coetzee, Stephen A.; Schmulian, Astrid – Assessment & Evaluation in Higher Education, 2022
This study reports on the incorporation of mobile instant messaging (MIM) in assessments, as a collaborative learning tool, to enable students to socially construct knowledge and develop their collaborative problem solving competence, while being assessed individually. In particular, this study explores: what is the extent and timing of students'…
Descriptors: Computer Mediated Communication, Student Evaluation, Peer Relationship, Cooperative Learning
Paiva, José Carlos; Leal, José Paulo; Figueira, Álvaro – ACM Transactions on Computing Education, 2022
Practical programming competencies are critical to the success in computer science (CS) education and go-to-market of fresh graduates. Acquiring the required level of skills is a long journey of discovery, trial and error, and optimization seeking through a broad range of programming activities that learners must perform themselves. It is not…
Descriptors: Automation, Computer Assisted Testing, Student Evaluation, Computer Science Education
Chen, Dandan – Online Submission, 2023
Technology-driven shifts have created opportunities to improve efficiency and quality of assessments. Meanwhile, they may have exacerbated underlying socioeconomic issues in relation to educational equity. The increased implementation of technology-based assessments during the COVID-19 pandemic compounds the concern about the digital divide, as…
Descriptors: Technology Uses in Education, Computer Assisted Testing, Alternative Assessment, Test Format
Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
Ashish Gurung; Kirk Vanacore; Andrew A. McReynolds; Korinn S. Ostrow; Eamon S. Worden; Adam C. Sales; Neil T. Heffernan – Grantee Submission, 2024
Learning experience designers consistently balance the trade-off between open and close-ended activities. The growth and scalability of Computer Based Learning Platforms (CBLPs) have only magnified the importance of these design trade-offs. CBLPs often utilize close-ended activities (i.e. Multiple-Choice Questions [MCQs]) due to feasibility…
Descriptors: Multiple Choice Tests, Testing, Test Format, Computer Assisted Testing