To test the suitability of an automatic system for emotional management in the classroom following the control-value theory of achievement emotions (CVT) framework, the performance of an emotional expression recognition software of our creation is evaluated in an online synchronous context. Sixty students from the Faculty of Education at the…

The process model of vocational identity was well applied in various Western countries to study the vocational identity process and statuses of college students. However, such research is limited in Hong Kong. Moreover, the relation between vocational identity development and academic performance was inconclusive in the literature, and it was also…

The study focused on understanding the different patterns of Facebook usage among university students and its impact on their academic performance. It was examined that to what extent Facebook consumption influenced the students' educational performance. "Uses and Gratifications" a theoretical framework was used to analyze consumption…

Using eye-tracking, we examined whether overspecification hinders or facilitates referent selection and the extent to which this depends on the properties of the attribute mentioned in the referring expressions and the underpinning processing mode. Following spoken instructions, participants selected the referent in a visual display while their…

In the field of communication studies, an understanding of the relationship between form and genre is essential for mastering both practical skills and theoretical concepts in core courses such as public speaking, communication theory, and rhetorical criticism. Building on scholarship on the visual politics of presidential portraiture, this…

Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…

Attrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students' retention services. Big Data mining and machine learning methods are applied to manipulate, analyze and predict students' failure,…

Attrition is one of the main concerns in distance learning due to the impact on the incomes and institutions reputation. Timely identification of students at risk has high practical value in effective students' retention services. Big Data mining and machine learning methods are applied to manipulate, analyze, and predict students' failure,…

The early detection of students' academic performance or final grades helps instructors prepare their online courses. In the Open University Learning Analytics Dataset, I found many online students clicked the course materials before the first day of class. This study aims to investigate how data mining models can use this student interaction data…

Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…

As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well…

This study aims to develop a computer program for the identification key to insect orders (Arthropoda: Hexapoda) and to investigate its effectiveness as teaching material. Secondly, this study is aiming at whether this program improves students' computational thinking skills or not longitudinal quasi-experimental design. Firstly, the study is…

This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…

The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic…

Humans possess a remarkable ability to recognise both simple patterns such as shapes and handwriting and very complex patterns such as faces and landscapes. To investigate one small aspect of human pattern recognition, in this study participants position lines of "best fit" to two-dimensional scatter plots of data. The study investigates…