In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

Data from student learning provide learning curves that, ideally, demonstrate improvement in student performance over time. Existing data mining methods can leverage these data to characterize and improve the domain models that support a learning environment, and these methods have been validated both with already-collected data, and in…

To improve the learning process, the evolution of learner's characteristics (cognitive, affective, prior knowledge, workflow, organization, ...) must be taken into account during the personalization or adaptation. This requires generating several scenarios (a description of activities, their order and links in the learning sequence as well as the…

Bayesian Knowledge Tracing (BKT) has been in wide use for modeling student skill acquisition in Intelligent Tutoring Systems (ITS). BKT tracks and updates student's latent mastery of a skill as a probability distribution of a binary variable. BKT does so by accounting for observed student successes in applying the skill correctly, where success is…

Purpose: The study's purpose was to determine the degree to which connoisseurship and educational criticism exists in student work evaluation; to identify master teachers' methods utilizing verbal feedback; and to determine the degree that project-based learning (PBL) principles serve as a "model of practice" for selected PBL technology…

This paper presents the development of the fusion model skills diagnosis system (fusion model system), which can help integrate standardized testing into the learning process with both skills-level examinee parameters for modeling examinee skill mastery and skills-level item parameters, giving information about the diagnostic power of the test.…

Describes the instructional materials and features that distinguish the Chicago model of mastery learning instruction from other models of mastery learning. Also describes innovative ways to examine the effects of mastery learning instruction, given that school data often are limited to norm referenced tests and are lacking in controls. (Author/GC)

Two approaches to measurement for instructional decision making (specific subskill mastery measurement and general outcome measurement) are described and illustrated with case studies. The paper concludes that measuring general outcome indicators can bridge traditional and contemporary assessment paradigms to form an innovative approach to…

Explains the use of instructional design with a mastery learning strategy (IDML) in teaching mathematics. The IDML model, a combination of other theories including Gagne's instructional events, has been used to improve mathematics instruction in Malaysian schools, and includes developing test items, the teachers' development of learning materials,…

A computing literacy course at Michigan State University for non-computer science students was designed with a fixed course structure and continuously changing course content. The structure provides feedback for assessing students and revising content to meet the changing demands of client departments, changing student experience, and changing…

Options are suggested for using and expanding upon the RMC models for evaluating the effectiveness of Title I mastery learning programs with planned high turnover of students. Examples are given of uses of the diagnostic and reporting systems for program planning and decision making. It is suggested that consideration be given to: (1) determining…