One of the popular creativity methods to solve technical problems is the Theory of Inventive Problem Solving, (TRIZ), however, requires a considerable investment of time. A teaching methodology for a simplified version of TRIZ (TRIZ10) has been developed for reducing learning time and improving the creative process in solving technical problems.…

Predictive modeling is a core technique used in tackling various tasks in learning analytics research, e.g., classifying educational forum posts, predicting learning performance, and identifying at-risk students. When applying a predictive model, it is often treated as the first priority to improve its prediction accuracy as much as possible.…

The main objective of this study is to develop a mathematical modeling framework for a deeper understanding of dynamics of math anxiety as a contagious process. Borrowing from theories of the spread of infectious disease, we develop two classes of mathematical models representing the spread of math anxiety in math gateway classes. The first…

The use of unidimensional scales that contain both positively and negatively worded items is common in both the educational and psychological fields. However, dimensionality investigations of these instruments often lead to a rejection of the theorized unidimensional model in favor of multidimensional structures, leaving researchers at odds for…

A research question that is of interest across many disciplines is whether and how relationships in a network are related to the attributes of the nodes of the network. In this dissertation, we propose two joint frameworks for modeling the relationship between the network and attributes. In the joint latent space model in Chapter 2, shared latent…

Many applications of structural equation modeling involve ordinal (e.g., Likert) variables. A popular way of dealing with ordinal variables is to estimate the model with polychoric correlations rather than Pearson correlations. Such an estimation also requires the asymptotic covariance matrix of polychoric correlations. It is computationally…

Dynamic Item Response Models extend the standard Item Response Theory (IRT) to capture temporal dynamics in learner ability. While these models have the potential to allow instructional systems to actively monitor the evolution of learner proficiency in real time, existing dynamic item response models rely on expensive inference algorithms that…

In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…

The literature on cognitive processing and strategic processing is murky with regard to how these types of processing influence learning. One reason for this is that the frameworks used to investigate these relations have separately focused on different aspects related to cognitive processing with little integration between them. To address these…

Group model building is a participatory workshop technique used in system dynamics for developing community consensus to address complex problems by consensus building on individual assumptions. This study examines changes in individual mental models of the complex problem of childhood obesity following participation in group model building (GMB),…

This study examined high school chemistry students' understandings of big ideas--matter and energy, how these understandings are related to macro and submicro representations and fine-grained distinguishing characteristics of students' explanations. The study was conducted in the context of computer-based models and model-based assessments.…

Each day people make decisions about complex topics such as health and personal finances. Causal models of these domains have been created to aid decisions, but the resulting models are often complex and it is not known whether people can use them successfully. We investigate the trade-off between simplicity and complexity in decision making,…

In this article we address the historical and epistemological study of infinity as a mathematical concept, focusing on identifying difficulties, counter-intuitive ideas and paradoxes that constituted implicit, unconscious models faced by mathematicians at different times in history, representing obstacles in the rigorous formalization process of…

Agility is a contemporary approach to IT project management, which we can also use in education. Students learn through the gradual implementation of iterative projects with information exchange between team members. Agility is above all a mindset. Being agile is quite simply being able to adapt to an environment that changes. Furthermore, various…

Machine learning (ML) has become commonplace in educational research and science education research, especially to support assessment efforts. Such applications of machine learning have shown their promise in replicating and scaling human-driven codes of students' work. Despite this promise, we and other scholars argue that machine learning has…