The unstructured multiple-attempt (MA) item response data in virtual learning environments (VLEs) are often from student-selected assessment data sets, which include missing data, single-attempt responses, multiple-attempt responses, and unknown growth ability across attempts, leading to a complex and complicated scenario for using this kind of…

Testwiseness may introduce construct-irrelevant variance to multiple-choice test scores. Presenting response options sequentially has been proposed as a potential solution to this problem. In an experimental validation, we determined the psychometric properties of a test based on the sequential presentation of response options. We created a strong…

Learning path and learning progression have received extensive attention from broad disciplines. The existing research In the field of learning path is rarely applied in curriculum learning and teaching. Learning progression is usually constructed through observations, interviews but not quantitative analyses. With 726 Grade 8 students'…

This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…

The development of novel educational assessment models founded on item response theory (IRT), as well as software tools designed to implement these models, has contributed to the surge in computerized adaptive tests (CATs). The distinguishing characteristic of CATs is that the sequence of items on a test progressively adapts to the performance…

Purpose: The study sought to determine the hierarchical nature of reading skills. Whether reading is a "unitary" or "multi-divisible" skill is still a contentious issue. So is the hierarchical order of reading skills. Determining the hierarchy of reading skills is challenging as item difficulty is greatly influenced by factors…

Learning progressions (LPs) are hypothetical models of how learning in a domain develops over time with appropriate instruction. In the domain of genetics, there are two independently developed alternative LPs. The main difference between the two progressions hinges on their assumptions regarding the accessibility of classical (Mendelian) versus…

Sequential mastery testing (SMT) has been researched as an efficient alternative to paper-and-pencil testing for pass/fail examinations. One popular method for determining when to cease examination in SMT is the truncated sequential probability ratio test (TSPRT). This article introduces the application of stochastic curtailment in SMT to shorten…

A simulation study of a sequential computerized mastery test is carried out with items modeled with the 3 parameter logistic item response theory model. The examinees' responses are either identically distributed, not identically distributed, or not identically distributed together with estimation errors in the item characteristics. The…

Computer Adaptive Sequential Testing (CAST) is a test delivery model that combines features of the traditional conventional paper-and-pencil testing and item-based computerized adaptive testing (CAT). The basic structure of CAST is a panel composed of multiple testlets adaptively administered to examinees at different stages. Current applications…

The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…