Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial…

Structural equation modeling (SEM) is being applied to ever more complex data types and questions, often requiring extensions such as regularization or novel fitting functions. To extend SEM, researchers currently need to completely reformulate SEM and its optimization algorithm -- a challenging and time-consuming task. In this paper, we introduce…

In this article, the authors explore how the 3C Model can be used to integrate other curriculum areas with mathematics, namely digital technologies. To illustrate the model, they provide a practical example of a teaching sequence. T he 3C Model is designed to create opportunities for applying reasoning and problem-solving skills and learning…

Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…

Many important human activities involve accomplishing goals without a script. There is no formula for true problem-solving. Heuristic, cognitive "rules of thumb" are the problem-solver's best guide. Learners should understand heuristic tools such as means-end analysis, working backwards, successive approximation, and external representation. Since…

Computer task automation is part of the natural progression of encoding information. This thesis considers the automation process to be a question of whether it is possible to automatically learn the encoding based on the behavior of the system to be described. A variety of representation languages are considered, as are means for the learner to…

Compares traditional mathematical models with computer simulations. Shows the strengths and flexibility of algorithmic computational simulations through a program designed to investigate and extend understanding in one of the most enduring questions in social choice research. Discusses solutions to this problem from each approach--analytic and…

Polynomial algorithms are presented that are used to solve selected problems in test theory, and computational results from sample problems with several hundred decision variables are provided that demonstrate the benefits of these algorithms. The algorithms are based on optimization theory in networks (graphs). (SLD)

A model for solving very large item selection problems is presented. The model builds on binary programming applied to test construction. A heuristic for selecting items that satisfy the constraints in the model is also presented, and various problems are solved using the model and heuristic. (SLD)

The reasons people most often give for the failures of U.S. schools involve poverty, racial inequality, and a host of social problems. This paper argues that even if all these conditions were remedied, the schools would not produce many more people with the ability to think than they do today. Teachers, who are usually able to think, do not know…

Research on the cognitive processes used by physicians during patient care (template matching, deductive logic starting with multiple hypotheses, and algorithmic logic) is examined for its applicability to optometrists and the problem-solving strategies used by optometric students in the classroom or clinic. (Author/MSE)

A model is presented for item responses when different subjects use different strategies, but only responses--not choice of strategy--can be observed. Substantive theory is used to differentiate the likelihoods of response vectors under a fixed set of strategies, and response probabilities are modeled via item parameters for each strategy. (TJH)

It is proposed that algorithms and heuristics are useful in improving professional problem-solving abilities when contextualized within the academic discipline. A basic algorithm applied to problem solving in undergraduate engineering education and a similar algorithm applicable to legal problems are used as examples. Problem complexity and…

Discusses the structure of a problem-based curriculum based on the complexity of the problems that the students must solve, taking into account the level they must attain and their previous experience with problem-based teaching. This approach is compared with the conventional teaching methods. Twenty-two references are listed. (CHC)