Related papers: Correlation Between Student Collaboration Network …
This paper presents data analysis from a course on Software Engineering in an effort to identify metrics and techniques that would allow instructor to act proactively and identify patterns of low engagement and inefficient peer…
We investigate the impact of content sequencing on student learning outcomes in a first-year university electromagnetism course. Using a custom-built online system, the McGill Learning Platform (McLEAP), we test student problem-solving…
The lack of an engaging pedagogy and the highly competitive atmosphere in introductory science courses tend to discourage students from pursuing science, technology, engineering, and mathematics (STEM) majors. Once in a STEM field, academic…
While it is well known which curricular practices can improve student performance on measures of conceptual understanding, the sustaining of these practices and the role of faculty members in implementing these practices are less well…
Group work is becoming increasingly common in introductory physics classrooms. Understanding how students engage in these group learning environments is important for designing and facilitating productive learning opportunities for…
Performance in introductory courses, particularly physics, is often crucial for student success in STEM majors and can impact an individual's tendency to persist in their chosen field. To enhance students' individual learning experiences,…
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging…
Student performance of virtual introductory physics class (calculus-based mechanics) is analyzed. A fully web-enhanced class was done synchronously. The analysis is done in two categories, averaging all mid-exams (or chapter exams) and…
Identifying vital nodes in networks exhibiting a community structure is a fundamental issue. Indeed, community structure is one of the main properties of real-world networks. Recent works have shown that community-aware centrality measures…
Computer science's increased recognition as a prominent field of study has attracted students with diverse academic backgrounds. This has significantly increased the already high failure rates in introductory courses. To address this…
As generative AI becomes embedded in higher education, it increasingly shapes how students complete academic tasks. While these systems offer efficiency and support, concerns persist regarding over-automation, diminished student agency, and…
Centrality of a node measures its relative importance within a network. There are a number of applications of centrality, including inferring the influence or success of an individual in a social network, and the resulting social network…
Measure the similarity of the nodes in the complex networks have interested many researchers to explore it. In this paper, a new method which is based on the degree centrality and the Relative-entropy is proposed to measure the similarity…
Network analysis is an important tool in understanding the behavior of complex systems of interacting entities. However, due to the limitations of data gathering technologies, some interactions might be missing from the network model. This…
Many studies in educational data mining address specific learner groups, such as first-in-family to attend Higher Education, or focus on differences in characteristics such as gender or ethnicity, with the aim of predicting performance and…
Learning using Computer-Assisted Instruction (CAI) demands a high level of attention given the tendency to be distracted and mind-wander. How does the online STEM instructor know when learners are having attentional problems and the extent…
When the college student satisfaction survey is considered in the promotion and recognition of instructors, a usual complaint is related to the impact that biased ratings have on the arithmetic mean (used as a measure of teaching…
Many of the structural characteristics of a network depend on the connectivity with and within the hubs. These dependencies can be related to the degree of a node and the number of links that a node shares with nodes of higher degree. In…
The introductory programming course (CS1) at the university level is often perceived as particularly challenging, contributing to high dropout rates among Computer Science students. Identifying when and how students encounter difficulties…
The correlation between NLG automatic evaluation metrics and human evaluation is often regarded as a critical criterion for assessing the capability of an evaluation metric. However, different grouping methods and correlation coefficients…