This study elaborates on the pivotal roles of mathematical and statistical models in data-driven predictions in an integrated STEM context using the case of Year 4 students: (?) "a descriptive means" to describe the features of trends and variability of data and (?) "an explanatory means" to explain causal relationships behind…

Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…

It is essential to save lives during emergencies not only in hospitals but also in colleges and universities. Failure to identify risks and take prompt action during catastrophes and emergency situations could result in the loss of life and property for the campus community. This research aims to explore the feasibility of using data analytics to…

This study investigated L2 learners' perception changes at each stage of online collaborative writing. Previous studies revealed the familiarity of L2 collaborative learning with Information and Communication Technology (ICT), whereas few described at which stage of the learning process L2 learners' perceptions change. Therefore, this study…

Over the years, researchers have studied novice programming behaviors when doing assignments and projects to identify struggling students. Much of these efforts focused on using student programming and interaction features to predict student success at a course level. While these methods are effective at early detection of struggling students in…

Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…

This longitudinal study aimed to determine changes in students' predictive reasoning across one year. Forty-four Australian students predicted future temperatures from a table of maximum monthly temperatures, explained their predictive strategies, and represented the data at two time points: Grade 3 and 4. Responses were analysed using a…

Data mining of course enrollment and course description records has soared as institutions of higher education begin tapping into the value of these data for academic and internal research purposes. This has led to a more than doubling of papers on course prediction tasks every year. The papers often center around a single prediction task and…

National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…

This paper describes a preliminary study of how computational methods allow us to know more about citizen science and its connection with education. Citizen science is a practice involving a general public in scientific tasks and generating knowledge and scientific results. Previous studies have shown that the education sector can take benefit of…

This study explores the effectiveness of Data-Driven Learning (DDL) approach to second-language (L2) English vocabulary learning in on-demand online distance learning at a private university in Tokyo, Japan. The participants were 49 Japanese undergraduates, intermediate L2 English learners at the B1 level in the Common European Framework of…

Effectively estimating student enrollment and recruiting students is critical to the success of any university. However, despite having an abundance of data and researchers at the forefront of data science, traditional universities are not fully leveraging machine learning and data mining approaches to improve their enrollment management…

Lawson (1983a) offered that an individuals' experiences as students in schools are significant in shaping their views of teaching. Pajares (1992) argued that a teacher's perceptions of the classroom are a product of their experiences as students. The purpose of this study was to examine the relationship between physical education (PE) pre-service…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

Recent work describes methods for systematic, data-driven improvement to instructional content and calls for diverse teams of learning engineers to implement and evaluate such improvements. Focusing on an approach called "design-loop adaptivity," we consider the problem of how developers might use data to target or prioritize particular…