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Metsämuuronen, Jari – International Journal of Educational Methodology, 2020
Kelley's Discrimination Index (DI) is a simple and robust, classical non-parametric short-cut to estimate the item discrimination power (IDP) in the practical educational settings. Unlike item-total correlation, DI can reach the ultimate values of +1 and -1, and it is stable against the outliers. Because of the computational easiness, DI is…
Descriptors: Test Items, Computation, Item Analysis, Nonparametric Statistics
Mang, Julia; Küchenhoff, Helmut; Meinck, Sabine; Prenzel, Manfred – Large-scale Assessments in Education, 2021
Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…
Descriptors: Sampling, Hierarchical Linear Modeling, Simulation, Scaling
Lu, Chang; Macdonald, Rob; Odell, Bryce; Kokhan, Vasyl; Demmans Epp, Carrie; Cutumisu, Maria – Journal of Computing in Higher Education, 2022
The field of computational thinking (CT) is developing rapidly, reflecting its importance in the global economy. However, most empirical studies have targeted CT in K-12, thus, little attention has been paid to CT in higher education. The present scoping review identifies and summarizes existing empirical studies on CT assessments in…
Descriptors: Computation, Thinking Skills, Higher Education, Educational Trends
Cho, April E.; Wang, Chun; Zhang, Xue; Xu, Gongjun – Grantee Submission, 2020
Multidimensional Item Response Theory (MIRT) is widely used in assessment and evaluation of educational and psychological tests. It models the individual response patterns by specifying functional relationship between individuals' multiple latent traits and their responses to test items. One major challenge in parameter estimation in MIRT is that…
Descriptors: Item Response Theory, Mathematics, Statistical Inference, Maximum Likelihood Statistics
Evripidou, Salomi; Amanatiadis, Angelos; Christodoulou, Klitos; Chatzichristofis, Savvas A. – IEEE Transactions on Learning Technologies, 2021
Today, in the era of robotics, different types of educational robots have been used extensively in school classrooms to facilitate teaching activities related to a variety of computer science concepts. Numerous studies have been performed that attempt to examine the effects of using tangible interfaces to enhance collaborative learning…
Descriptors: Thinking Skills, Mathematics, Computation, Sequential Approach
Sari, Ugur; Pektas, Hüseyin Miraç; Sen, Ömer Faruk; Çelik, Harun – Education and Information Technologies, 2022
The need to benefit from information technologies in the twenty-first century digital age is increasing in all economies to overcome problems and difficulties and to have desired solutions. So, developing algorithmic thinking has been important as a skill that requires the application of knowledge from different disciplines, especially science,…
Descriptors: Mathematics, Thinking Skills, Information Technology, Computer Uses in Education
Fu, Jianbin – ETS Research Report Series, 2019
A maximum marginal likelihood estimation with an expectation-maximization algorithm has been developed for estimating multigroup or mixture multidimensional item response theory models using the generalized partial credit function, graded response function, and 3-parameter logistic function. The procedure includes the estimation of item…
Descriptors: Maximum Likelihood Statistics, Mathematics, Item Response Theory, Expectation
Mackworth-Young, Charles – Journal of Research Administration, 2021
Background: The peer review of clinical research projects is an essential step in project preparation. While some projects undergo rigorous review by grant-giving organizations, this does not apply to all clinical research. In many cases, peer review, if undertaken at all, is not rigorous, fully independent, or timely. Depending on their…
Descriptors: Peer Evaluation, Medical Research, Research Projects, Ethics
Young, Nicholas T.; Caballero, Marcos D. – Journal of Educational Data Mining, 2021
We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the…
Descriptors: Prediction, Models, Learning Analytics, Mathematics
Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
Ezz, Mohamed; Elshenawy, Ayman – Education and Information Technologies, 2020
Some of the educational organizations have multi-education paths such as engineering and medicine collages. In such colleges, the behavior of the student in the preparatory year determines which education path the student will join in the future. In this paper, an adaptive recommendation system is proposed for predicting a suitable education…
Descriptors: Educational Technology, Artificial Intelligence, Computation, Mathematics
Avci, Canan; Deniz, Mine Nur – Education and Information Technologies, 2022
Computational thinking (CT) is considered a group of problem-solving skills that the next generations are expected to possess. The most efficient way to make them acquire these skills is to incorporate CT into K-12 education. To this end, various education programs have been designed to improve teachers' and prospective teachers' competence in CT.…
Descriptors: Early Childhood Teachers, Preservice Teachers, Computation, Thinking Skills
Thrall, Elizabeth S.; Lee, Seung Eun; Schrier, Joshua; Zhao, Yijun – Journal of Chemical Education, 2021
Techniques from the branch of artificial intelligence known as machine learning (ML) have been applied to a wide range of problems in chemistry. Nonetheless, there are very few examples of pedagogical activities to introduce ML to chemistry students in the chemistry education literature. Here we report a computational activity that introduces…
Descriptors: Undergraduate Students, Artificial Intelligence, Man Machine Systems, Science Education
Dewi, Jasinta D. M.; Bagnoud, Jeanne; Thevenot, Catherine – Cognitive Science, 2021
As a theory of skill acquisition, the instance theory of automatization posits that, after a period of training, algorithm-based performance is replaced by retrieval-based performance. This theory has been tested using alphabet-arithmetic verification tasks (e.g., is A + 4 = E?), in which the equations are necessarily solved by counting at the…
Descriptors: Skill Development, Training, Task Analysis, Learning Theories
Fazlul, Ishtiaque; Koedel, Cory; Parsons, Eric; Qian, Cheng – Thomas B. Fordham Institute, 2021
When the COVID-19 pandemic hit the U.S. last spring, schools nationwide shut their doors and states cancelled annual standardized tests. Now federal and state policymakers are debating whether to cancel testing again in 2021. One factor they should consider is whether a two-year gap in testing will make it impossible to measure student-level…
Descriptors: COVID-19, Pandemics, Academic Achievement, Achievement Gains

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