NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 18 results Save | Export
Crisp, Victoria; Shaw, Stuart – Research Matters, 2020
For assessment contexts where both a paper-based test and an on-screen assessment are available as alternatives, it is still common for the paper-based test to be prepared first with questions later transferred into an on-screen testing platform. One challenge with this is that some questions cannot be transferred. One solution might be for…
Descriptors: Computer Assisted Testing, Test Items, Test Construction, Mathematics Tests
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Albacete, Patricia; Silliman, Scott; Jordan, Pamela – Grantee Submission, 2017
Intelligent tutoring systems (ITS), like human tutors, try to adapt to student's knowledge level so that the instruction is tailored to their needs. One aspect of this adaptation relies on the ability to have an understanding of the student's initial knowledge so as to build on it, avoiding teaching what the student already knows and focusing on…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Multiple Choice Tests, Computer Assisted Testing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Jancarík, Antonín; Kostelecká, Yvona – Electronic Journal of e-Learning, 2015
Electronic testing has become a regular part of online courses. Most learning management systems offer a wide range of tools that can be used in electronic tests. With respect to time demands, the most efficient tools are those that allow automatic assessment. The presented paper focuses on one of these tools: matching questions in which one…
Descriptors: Online Courses, Computer Assisted Testing, Test Items, Scoring Formulas
Peer reviewed Peer reviewed
Direct linkDirect link
Ihme, Jan Marten; Senkbeil, Martin; Goldhammer, Frank; Gerick, Julia – European Educational Research Journal, 2017
The combination of different item formats is found quite often in large scale assessments, and analyses on the dimensionality often indicate multi-dimensionality of tests regarding the task format. In ICILS 2013, three different item types (information-based response tasks, simulation tasks, and authoring tasks) were used to measure computer and…
Descriptors: Foreign Countries, Computer Literacy, Information Literacy, International Assessment
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Golovachyova, Viktoriya N.; Menlibekova, Gulbakhyt Zh.; Abayeva, Nella F.; Ten, Tatyana L.; Kogaya, Galina D. – International Journal of Environmental and Science Education, 2016
Using computer-based monitoring systems that rely on tests could be the most effective way of knowledge evaluation. The problem of objective knowledge assessment by means of testing takes on a new dimension in the context of new paradigms in education. The analysis of the existing test methods enabled us to conclude that tests with selected…
Descriptors: Expertise, Computer Assisted Testing, Student Evaluation, Knowledge Level
Peer reviewed Peer reviewed
Direct linkDirect link
Andjelic, Svetlana; Cekerevac, Zoran – Education and Information Technologies, 2014
This article presents the original model of the computer adaptive testing and grade formation, based on scientifically recognized theories. The base of the model is a personalized algorithm for selection of questions depending on the accuracy of the answer to the previous question. The test is divided into three basic levels of difficulty, and the…
Descriptors: Computer Assisted Testing, Educational Technology, Grades (Scholastic), Test Construction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
Peer reviewed Peer reviewed
Direct linkDirect link
Papasalouros, Andreas; Kotis, Konstantinos; Kanaris, Konstantinos – Interactive Learning Environments, 2011
The aim of this article is to present an approach for generating tests in an automatic way. Although other methods have been already reported in the literature, the proposed approach is based on ontologies, representing both domain and multimedia knowledge. The article also reports on a prototype implementation of this approach, which…
Descriptors: Semantics, Natural Language Processing, Test Construction, Educational Technology
National Assessment Governing Board, 2014
Due to the growing importance of technology and engineering in the educational landscape, and to support America's ability to contribute to and compete in a global economy, the National Assessment Governing Board (NAGB) initiated development of the first NAEP Technology and Engineering Literacy (TEL) Assessment. Relating to national efforts in…
Descriptors: Technological Literacy, Technical Education, Engineering Education, National Competency Tests
Qian, Hong – ProQuest LLC, 2013
This dissertation includes three essays: one essay focuses on the effect of teacher preparation programs on teacher knowledge while the other two focus on test-takers' response times on test items. Essay One addresses the problem of how opportunities to learn in teacher preparation programs influence future elementary mathematics teachers'…
Descriptors: Teacher Education Programs, Pedagogical Content Knowledge, Preservice Teacher Education, Preservice Teachers
Peer reviewed Peer reviewed
Direct linkDirect link
Wauters, K.; Desmet, P.; Van den Noortgate, W. – Journal of Computer Assisted Learning, 2010
The popularity of intelligent tutoring systems (ITSs) is increasing rapidly. In order to make learning environments more efficient, researchers have been exploring the possibility of an automatic adaptation of the learning environment to the learner or the context. One of the possible adaptation techniques is adaptive item sequencing by matching…
Descriptors: Knowledge Level, Adaptive Testing, Test Items, Item Response Theory
Peer reviewed Peer reviewed
McLeod, Lori; Lewis, Charles; Thissen, David – Applied Psychological Measurement, 2003
Explored procedures to detect test takers using item preknowledge in computerized adaptive testing and suggested a Bayesian posterior log odds ratio index for this purpose. Simulation results support the use of the odds ratio index. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Knowledge Level
Peer reviewed Peer reviewed
Direct linkDirect link
Levy, Roy; Mislevy, Robert J. – International Journal of Testing, 2004
The challenges of modeling students' performance in computer-based interactive assessments include accounting for multiple aspects of knowledge and skill that arise in different situations and the conditional dependencies among multiple aspects of performance. This article describes a Bayesian approach to modeling and estimating cognitive models…
Descriptors: Computer Assisted Testing, Markov Processes, Computer Networks, Bayesian Statistics
PDF pending restoration PDF pending restoration
Plake, Barbara S.; And Others – 1994
In self-adapted testing (SAT), examinees select the difficulty level of items administered. This study investigated three variations of prior information provided when taking an SAT: (1) no information (examinees selected item difficulty levels without prior information); (2) view (examinees inspected a typical item from each difficulty level…
Descriptors: Adaptive Testing, College Students, Computer Assisted Testing, Difficulty Level
Peer reviewed Peer reviewed
Plake, Barbara S.; And Others – Educational and Psychological Measurement, 1995
No significant differences in performance on a self-adapted test or anxiety were found for college students (n=218) taking a self-adapted test who selected item difficulty without any prior information, inspected an item before selecting, or answered a typical item and received performance feedback. (SLD)
Descriptors: Achievement, Adaptive Testing, College Students, Computer Assisted Testing
Previous Page | Next Page »
Pages: 1  |  2