Intelligent technology plays a pivotal role in revolutionizing learning assessments, overcoming the constraints of traditional assessment methods and driving educational innovation. Knowledge tracing (KT) emerges as a critical component for assessing students' learning states and forecasting their future performance. However, existing graph-based…

Given the extensive use of online learning in educational settings, Knowledge Tracing (KT) is becoming increasingly essential. KT primarily aims to predict a student's future knowledge acquisition based on their past learning activities, thus enhancing the efficiency of student learning. However, the effective acquisition of dynamic and evolving…

Network meta-analysis (NMA) is an established method for assessing the comparative efficacy and safety of competing interventions. It is often the case that we deal with interventions that consist of multiple, possibly interacting, components. Examples of interventions' components include characteristics of the intervention, mode (face-to-face,…

In recent years, the rapid growth of Massive Open Online Courses (MOOCs) has attracted much attention for related research. Besides, one of the main challenges in MOOCs is the high dropout or low completion rate. Early dropout prediction algorithms aim the educational institutes to retain the students for the related course. There are several…

Automatic short answer grading (ASAG) is a challenging task that aims to predict a score for a given student response. Previous works on ASAG mainly use nonneural or neural methods. However, the former depends on handcrafted features and is limited by its inflexibility and high cost, and the latter ignores global word cooccurrence in a corpus and…

Technological advances have significantly affected education, leading to the creation of online learning platforms such as virtual learning environments and massive open online courses. While these platforms offer a variety of features, none of them incorporates a module that accurately predicts students' academic performance and commitment.…

Component network meta-analysis (CNMA) compares treatments comprising multiple components and estimates the effects of individual components. For network meta-analysis, a standard network plot with nodes for treatments and edges for direct comparisons between treatments is drawn to visualize the evidence structure and the connections between…

The full implementation of MOOCs in online education offers new opportunities for integrating multidisciplinary and comprehensive STEM education. It facilitates the alignment between online learning content and learning behaviors. However, it also presents new challenges, such as a high rate of STEM dropouts. Many learners struggle to establish…

This article describes an activity and resource from The New York Times that can be used to help learners cultivate critical statistical literacy. Critical statistical literacy involves understanding, interpreting, and questioning statistical information to make informed decisions (Casey et al., 2023; Franklin et al., 2015; Weiland, 2017). It is a…

Network meta-analysis compares multiple treatments from studies that form a connected network of evidence. However, for complex networks, it is not easy to see if the network is connected. We use simple techniques from graph theory to test the connectedness of evidence networks in network meta-analysis. The method is to build the adjacency matrix…

Network meta-analysis (NMA) can be used to compare multiple competing treatments for the same disease. In practice, usually a range of outcomes is of interest. As the number of outcomes increases, summarizing results from multiple NMAs becomes a nontrivial task, especially for larger networks. Moreover, NMAs provide results in terms of relative…

Traditional visualization in meta-analysis uses forest plots to illustrate the combined treatment effect, along with the respective results from primary trials. While the purpose of visualization is clear in the pairwise setting, additional treatments broaden the focus and extend the results to be illustrated in network meta-analysis. The…

While the use of video recording as a method of data collection has helped researchers to resolve the challenge of capturing classroom interactions between teachers and students, it can be challenging for the researchers and teachers to make sense of the rich data collected. This paper describes an approach of analysing and visualising a language…

Background: Meta-regression results must be interpreted taking into account the range of covariate values of the contributing studies. Results based on interpolation or extrapolation may be unreliable. In network meta-regression (NMR) models, which include covariates in network meta-analyses, results are estimated using direct and indirect…

Curriculum prerequisite networks have a central role in shaping the course of university programs. The analysis of prerequisite networks has attracted a lot of research interest recently since designing an appropriate network is of great importance both academically and economically. It determines the learning goals of the program and also has a…