This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…

Procrastination, the irrational delay of tasks, is a common occurrence in online learning. Potential negative consequences include a higher risk of drop-outs, increased stress, and reduced mood. Due to the rise of learning management systems (LMS) and learning analytics (LA), indicators of such behavior can be detected, enabling predictions of…

Aim/Purpose: The aim of this paper is to evaluate whether the use of social media by college students is linked with diminished academic productivity, and if so, why? Background: In prior research, social media use was inversely related to academic productivity. We replicated that effect and tested whether depletion sensitivity, delay discounting,…

Preparing for exams in introductory biology classrooms is a complex metacognitive task. Focusing on lower achieving students (those with entering ACT scores below the median at our institution), we compared the effect of two different assignments distributed ahead of exams by dividing classes in half to receive either terms to define or open-ended…

In today's connected world, forming teams of people to execute projects is seen as a challenge in government agencies and public and private organisations alike. For large enterprises, a small group of thoughtful and committed people performing different roles could essentially change the world. At the same time, however, it is hard to select an…

This paper describes a neural network model that can be used to detect at- risk students failing a particular course using only grade book data from a learning management system. By analyzing data extracted from the learning management system at the end of week 5, the model can predict with an accuracy of 88% whether the student will pass or fail…

Much of learning analytics research has focused on factors influencing model generalizability of predictive models for academic performance. The degree of model generalizability across courses may depend on aspects, such as the similarity of the course setup, course material, the student cohort, or the teacher. Which of these contextual factors…

The practice assignments in a mathematics textbook or course can be arranged so that most of the problems relating to any particular concept are massed together in a single assignment, or these related problems can be distributed across many assignments--a format known as spaced practice. Here we report the results of two classroom experiments…

The practice assignments in a mathematics textbook or course can be arranged so that most of the problems relating to any particular concept are massed together in a single assignment, or these related problems can be distributed across many assignments -- a format known as spaced practice. Here we report the results of two classroom experiments…

Reading is a core element in language education. Despite extensive research in second/foreign language (L2/FL) reading, relatively little is known about the differences between two common practices: Compulsory reading (i.e. reading assigned by teachers) and voluntary reading (i.e. self-initiated reading). This article reports two related…

Doing assignments is a very important part of learning. Students' assignment submission time provides valuable information on study attitudes and habits which strongly correlate with academic performance. However, the number of assignments and their submission deadlines vary among university courses, making it hard to use assignment submission…

This study analyzed students' online assignment submission behaviors from the perspectives of temporal learning analytics. This study aimed to model the time-dependent changes in the assignment submission behavior of university students by employing various machine learning methods. Precisely, clustering, Markov Chains, and association rule mining…

This study investigates task-specific emotions, examining how they arise and impact performance in a second language writing task through the lens of control-value theory and a positive psychology (PP) perspective. Participants were 206 secondary English-as-a-foreign-language learners from rural China. They completed an English argumentative…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

We use Markov chain Monte Carlo (MCMC) analysis to construct a three-question math quiz to assess key skills needed for introductory finance. We begin with data collected from a ten-question criterion-referenced math quiz given to 314 undergraduates on the first day of class. MCMC indicates the top three questions for predicting overall course…