Students are the future of a nation. Personalizing student interests in higher education courses is one of the biggest challenges in higher education. Various AI and ML approaches have been used to study student behaviour. Existing AI and ML algorithms are used to identify features for various fields, such as behavioural analysis, economic…

In this paper, we report the results of a 3-year, quasi-experimental study comparing students' engagement and deep learning of course materials between students who took an undergraduate engineering course that used a video game approach to a control group. The video game, EduTorcs, provided challenges in which students devised control algorithms…

Contribution: The proposed work carries out the training and testing of the available data through an artificial neural network and develops a model to allocate the subject for maximum outcome. The system also provides percentagewise correlation among all the possible subjects of best fit to allocate among the faculty members. Background: Data…

Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect…

Quantum information science and engineering (QISE) is a rapidly developing field that leverages the skills of experts from many disciplines to utilize the potential of quantum systems in a variety of applications. It requires talent from a wide variety of traditional fields, including physics, engineering, chemistry, and computer science, to name…

Engineering design plays an important role in education. However, due to its open nature and complexity, providing timely support to students has been challenging using the traditional assessment methods. This study takes an initial step to employ learning analytics to build performance prediction models to help struggling students. It allows…

Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…

Previous findings from the study within which this research is located had uncovered students' approaches to learning in the context of a second year chemical engineering course. Using an analysis of students' reflections on their experience, the study has shown the existence of three approaches to learning in this context: an 'information-based'…

This paper reports findings from a comprehensive evaluation of the first national electronic mentoring program that matches female engineering students with mentors working in industry. The program being evaluated--MentorNet--uses a combination of on-line tools, computer databases, mentoring specialists, and campus and industrial contacts to…

This study investigated students' conceptual and procedural understanding of calculus within the context of an engineering mechanics course. Four traditional calculus students were compared with three students from one of the calculus reform projects, Calculus & Mathematica. Task-based interviews were conducted with each participant throughout…

Described is a computer algorithm for obtaining the coordinates of vertices, chord factors, and dihedral angles for plotting orthographic and axonometric projections, and for tabulating chord lengths and dihedral angles. (Author)

Reports on a study in which two spatial tests were given to science and engineering majors and to students in nursing and agriculture at Purdue University (Indiana). Scores from the tests consistently contributed a small but significant amount of success on measures of performance in chemistry. (TW)