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Stenger, Rachel; Olson, Kristen; Smyth, Jolene D. – Field Methods, 2023
Questionnaire designers use readability measures to ensure that questions can be understood by the target population. The most common measure is the Flesch-Kincaid Grade level, but other formulas exist. This article compares six different readability measures across 150 questions in a self-administered questionnaire, finding notable variation in…
Descriptors: Readability, Readability Formulas, Computer Assisted Testing, Evaluation Methods
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Liu, Changyun; Zhang, Dake; Pandolpho, Max; Yi, Julia – Assessment for Effective Intervention, 2023
This study investigated the effectiveness of four Digitalized Interactive Components (DICs) designed based on cognitive principles to accommodate individual differences among students with learning difficulties in geometry during computer-based assessments. The four DICs were annotations (allowing students to make notes on the screen), pop-up…
Descriptors: High School Students, Computer Assisted Testing, Geometry, Secondary School Mathematics
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Douglas Yeboah – Cogent Education, 2023
Computer-based test has been administered in e-learning environments as part of ICT integration in education. Recently, online test is gaining attention in both regular and distance education institutions, and students' preference or perception of an online test versus paper-based test is crucial in successful adoption or implementation of either…
Descriptors: Foreign Countries, Undergraduate Students, Test Format, Computer Assisted Testing
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Yan Jin; Jason Fan – Language Assessment Quarterly, 2023
In language assessment, AI technology has been incorporated in task design, assessment delivery, automated scoring of performance-based tasks, score reporting, and provision of feedback. AI technology is also used for collecting and analyzing performance data in language assessment validation. Research has been conducted to investigate the…
Descriptors: Language Tests, Artificial Intelligence, Computer Assisted Testing, Test Format
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
Moschella, Jennifer A. – ProQuest LLC, 2023
In higher education, the entry-level, not-for-credit courses in Developmental Education play a pivotal role for incoming degree-seeking students. Focusing specifically on Developmental Writing, at two- and four-year public and private institutions across the country, a common requirement to pass the course is a summative argumentative essay that…
Descriptors: Formative Evaluation, Writing Skills, Computer Assisted Testing, Basic Writing
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Yigiter, Mahmut Sami; Dogan, Nuri – Measurement: Interdisciplinary Research and Perspectives, 2023
In recent years, Computerized Multistage Testing (MST), with their versatile benefits, have found themselves a wide application in large scale assessments and have increased their popularity. The fact that forms can be made ready before the exam application, such as a linear test, and that they can be adapted according to the test taker's ability…
Descriptors: Programming Languages, Monte Carlo Methods, Computer Assisted Testing, Test Format
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Lim, Hwanggyu; Choe, Edison M. – Journal of Educational Measurement, 2023
The residual differential item functioning (RDIF) detection framework was developed recently under a linear testing context. To explore the potential application of this framework to computerized adaptive testing (CAT), the present study investigated the utility of the RDIF[subscript R] statistic both as an index for detecting uniform DIF of…
Descriptors: Test Items, Computer Assisted Testing, Item Response Theory, Adaptive Testing
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Falcão, Filipe; Pereira, Daniela Marques; Gonçalves, Nuno; De Champlain, Andre; Costa, Patrício; Pêgo, José Miguel – Advances in Health Sciences Education, 2023
Automatic Item Generation (AIG) refers to the process of using cognitive models to generate test items using computer modules. It is a new but rapidly evolving research area where cognitive and psychometric theory are combined into digital framework. However, assessment of the item quality, usability and validity of AIG relative to traditional…
Descriptors: Computer Assisted Testing, Test Construction, Test Items, Automation
Samira Syal; Marcia Davis; Xiaodong Zhang; Jason Schoeneberger; Samantha Spinney; Douglas J. Mac Iver; Martha Mac Iver – Grantee Submission, 2023
Motivation to read is crucial to improving reading skill. While there is extensive research examining reading motivation among elementary students, with respect to adolescents, research is limited. Employing a person-centered approach can aid in developing a better understanding of adolescent reading motivation and would help address possible…
Descriptors: Reading Motivation, Adolescents, Reading Achievement, High School Students
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Brittland K. DeKorver; Mitchell Krahulik; Deborah G. Herrington – Journal of Chemical Education, 2023
The COVID-19 pandemic confronted chemistry instructors worldwide with many new challenges as they were quickly required to make the shift to remote instruction. One of these challenges was administering assessments in an online format. This was the topic of many discussions in the online support group Strategies for Teaching Chemistry (SFTC). This…
Descriptors: Chemistry, Science Teachers, Teacher Attitudes, COVID-19
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Jiang, Zhuhan; Huang, Jiansheng – IEEE Transactions on Learning Technologies, 2022
Advanced digital technologies and social media have greatly improved both the learning experience and the assessment convenience, while inadvertently facilitated potential plagiarism and collaborative cheating at the same time. In this article, we will focus on the strategies and their technological implementations to run exams, or in-class tests…
Descriptors: Plagiarism, Educational Technology, Computer Assisted Testing, Cheating
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Ince Araci, F. Gul; Tan, Seref – International Journal of Assessment Tools in Education, 2022
Computerized Adaptive Testing (CAT) is a beneficial test technique that decreases the number of items that need to be administered by taking items in accordance with individuals' own ability levels. After the CAT applications were constructed based on the unidimensional Item Response Theory (IRT), Multidimensional CAT (MCAT) applications have…
Descriptors: Adaptive Testing, Computer Assisted Testing, Simulation, Item Response Theory
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El Asame, Maryam; Wakrim, Mohamed; Battou, Amal – Education and Information Technologies, 2022
E-Assessment, which is a key element in the instructional design process, plays a major role in supporting and enhancing learning. However, the current e-assessment design does not achieve the desired pedagogical objectives in the e-learning environments. In this paper, we propose a hybrid pedagogical framework for e-learning environments, that…
Descriptors: Computer Assisted Testing, Student Evaluation, Teaching Methods, Instructional Design
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Singh, Sneha; Kumar, Amit; Arya, Aditya – Biochemistry and Molecular Biology Education, 2022
The emergence of the global pandemic, SARS-CoV-2 has posed several challenges to education across the globe and led to the emergence and progression of newer methods of teaching and assessment. While online teaching has been quickly adopted and implemented across the globe, exams and assessment remain poorly managed both at an elementary and…
Descriptors: Cheating, Supervision, COVID-19, Pandemics
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