Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 7 |
| Since 2017 (last 10 years) | 7 |
| Since 2007 (last 20 years) | 7 |
Descriptor
| Algorithms | 16 |
| Reaction Time | 16 |
| Models | 7 |
| Problem Solving | 6 |
| Test Items | 5 |
| Cognitive Processes | 4 |
| Computer Assisted Testing | 4 |
| Accuracy | 3 |
| Artificial Intelligence | 3 |
| Foreign Countries | 3 |
| Prediction | 3 |
| More ▼ | |
Source
Author
| Atkinson, Richard C. | 1 |
| Bulut, Okan | 1 |
| Carter, Philip | 1 |
| Chun Wang | 1 |
| Dashiell, William | 1 |
| Daxun Wang | 1 |
| Deary, Ian J. | 1 |
| Dongbo Tu | 1 |
| Egan, Vincent | 1 |
| Feng, Mingyu, Ed. | 1 |
| Glaser, Robert | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 9 |
| Journal Articles | 8 |
| Collected Works - Proceedings | 1 |
| Collected Works - Serials | 1 |
| Dissertations/Theses -… | 1 |
| Reports - Descriptive | 1 |
| Reports - Evaluative | 1 |
Education Level
| Secondary Education | 3 |
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
| United Kingdom (Scotland) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Program for International… | 2 |
What Works Clearinghouse Rating
Schneider, Stefan; Jin, Haomiao; Orriens, Bart; Junghaenel, Doerte U.; Kapteyn, Arie; Meijer, Erik; Stone, Arthur A. – Field Methods, 2023
Researchers have become increasingly interested in response times to survey items as a measure of cognitive effort. We used machine learning to develop a prediction model of response times based on 41 attributes of survey items (e.g., question length, response format, linguistic features) collected in a large, general population sample. The…
Descriptors: Surveys, Response Rates (Questionnaires), Test Items, Artificial Intelligence
Zhichen Guo; Daxun Wang; Yan Cai; Dongbo Tu – Educational and Psychological Measurement, 2024
Forced-choice (FC) measures have been widely used in many personality or attitude tests as an alternative to rating scales, which employ comparative rather than absolute judgments. Several response biases, such as social desirability, response styles, and acquiescence bias, can be reduced effectively. Another type of data linked with comparative…
Descriptors: Item Response Theory, Models, Reaction Time, Measurement Techniques
Gorgun, Guher; Bulut, Okan – Large-scale Assessments in Education, 2023
In low-stakes assessment settings, students' performance is not only influenced by students' ability level but also their test-taking engagement. In computerized adaptive tests (CATs), disengaged responses (e.g., rapid guesses) that fail to reflect students' true ability levels may lead to the selection of less informative items and thereby…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
Seyma N. Yildirim-Erbasli; Guher Gorgun – Technology, Knowledge and Learning, 2025
Exploring the relationship between student ability and test-taking effort is an important area of study, offering insights into their approach to educational assessments. Previous research shows this relationship, yet there is a scarcity of research comparing the test-taking effort of students. In addition, researchers have frequently employed…
Descriptors: Ability, Test Wiseness, Predictor Variables, Student Reaction
Mingying Zheng – ProQuest LLC, 2024
The digital transformation in educational assessment has led to the proliferation of large-scale data, offering unprecedented opportunities to enhance language learning, and testing through machine learning (ML) techniques. Drawing on the extensive data generated by online English language assessments, this dissertation investigates the efficacy…
Descriptors: Artificial Intelligence, Computational Linguistics, Language Tests, English (Second Language)
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
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 reviewedDashiell, William; Killian, Paul W., Jr. – Perceptual and Motor Skills, 1981
Eighteen college students solved addition problems using the Hutchings Low Fatigue Addition Algorithm, which requires a written record of running sums, and the standard algorithm, which does not. Students using the Hutchings algorithm had significantly higher reaction times to a tone, indicating that the Hutchings method requires less cognitive…
Descriptors: Addition, Adolescents, Algorithms, Cognitive Processes
Peer reviewedCarter, Philip; And Others – Journal of Experimental Child Psychology, 1983
Two experiments studied nine-year-olds, l3-year-olds, and adults in their encoding of two kinds of stimuli taken from a psychometric measure of spatial aptitude. The first experiment used letter-like stimuli; the second employed multi-element flags. (CI)
Descriptors: Adults, Age Differences, Algorithms, Children
Peer reviewedWoods, Shirley S.; And Others – Journal of Educational Psychology, 1975
Descriptors: Algorithms, Elementary Education, Elementary School Students, Intellectual Development
Matthews, Paul G.; Atkinson, Richard C. – 1975
This paper reports an experiment designed to test theoretical relations among fast problem solving, more complex and slower problem solving, and research concerning fundamental memory processes. Using a cathode ray tube, subjects were presented with propositions of the form "Y is in list X" which they memorized. In later testing they were asked to…
Descriptors: Algorithms, Graphs, Information Processing, Logical Thinking
Peer reviewedGroen, Guy; Resnick., Lauren B. – Journal of Educational Psychology, 1977
Ten nursery school children who knew how to count but were unacquainted with arithmetic were taught a simple algorithm for solving single-digit addition problems and were then given extended practice. The reaction time on the final block of extended practice suggested that subjects had invented a more efficient procedure to replace the original…
Descriptors: Addition, Algorithms, Cognitive Development, Cognitive Processes
Peer reviewedMeghabghab, George – Information Processing & Management, 2001
Discusses the evaluation of search engines and uses neural networks in stochastic simulation of the number of rejected Web pages per search query. Topics include the iterative radial basis functions (RBF) neural network; precision; response time; coverage; Boolean logic; regression models; crawling algorithms; and implications for search engine…
Descriptors: Algorithms, Computer Simulation, Evaluation Methods, Mathematical Formulas
Peer reviewedEgan, Vincent; Deary, Ian J. – Intelligence, 1992
To assess whether movement artifacts reported in visual inspection time (IT) tasks were under metacognitive control, 29 young adults in Edinburgh (Scotland) were tested on a dual-task paradigm in which IT was conducted along with a concurrent task. Reports of movement artifacts are not usually examples of metacognitive processing. (SLD)
Descriptors: Algorithms, Foreign Countries, Intelligence Quotient, Metacognition
Sternberg, Robert J. – 1979
About 25 children in each of grades 3, 5, 7, 9, and 11 were tested in their ability to solve linear syllogisms, such as: John is taller than Mary. Mary is taller than Pete. Who is tallest--John, Mary, or Pete? Response latencies and error rates decreased across grade levels and sessions. Component latencies also generally decreased with increasing…
Descriptors: Abstract Reasoning, Age Differences, Algorithms, Cognitive Development
Previous Page | Next Page »
Pages: 1 | 2
Direct link
