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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
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 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
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

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