Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…

The purpose of this study is to predict the mathematical literacy levels of the students participating in the research through the data obtained from PISA 2015 exam organized by OECD using data mining and to determine the variables that affect mathematics literacy. For this purpose, students' mathematics literacy levels and the variables that…

The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically,…

Integrating learning analytics in digital game-based learning has gained popularity in recent decades. The interactive nature of educational games creates an ideal environment for learning analytics data collection. However, past research has limited success in producing accessible and effective assessments using game learning analytics. In this…

The purpose of this paper is to integrate mathematical modeling and ecology by presenting an activity involving an authentic environmental problem, which is called "Pine Processionary Caterpillars Invasion." Adopting Mathematical Modeling and Education for Climate Action (EfCA) approaches, it was aimed to encourage pre-service teachers…

The higher education sector is under increasing pressure to deliver more and to evidence the fruits of its contribution to society. There is a particular focus on the enhanced engagement of students in order to maximise success, and for this engagement to be achieved equitably across the student body, regardless of demographic backgrounds. This…

The need for a knowledge-based society has perpetuated an increasing demand for higher education around the globe. Recently, there has been an increase in the demand for Computer Science professionals due to the rise in the use of ICT in the business, health and education sector. The enrollment numbers in Computer Science undergraduate programmes…

Rough set theory (RST) was proposed by Zdzistaw Pawlak (Pawlak,1982) as a methodology for data analysis using the notion of discernibility of objects based on their attribute values. The main advantage of using RST approach is that it does not need additional assumptions--like data distribution in statistical analysis. Besides, it provides…

The intensification of data collection practices in schooling -- often due to state accountability requirements -- has resulted in the widespread adoption of commercial student management systems (SMS) in schools. Drawing on a qualitative case study of a New Zealand primary school, this paper investigates its adoption of a commercial SMS, and the…

We studied the impact of introducing first-year computer science (CS) students to ethical thinking about the social justice impacts of data collection, tracking, bias, internet privacy, and competitive "real world" system design and critique activities. While basic content was consistent for all, one group was involved throughout the…

In this article, the authors experiment with data-ing as a methodology, and wonder how three researchers?--?two in Oslo (Norway) and one in Melbourne (Australia)?--?can come closer to-with the research material by following and buggy-walking a young wayfarer in urban spaces and places. The ideas of not knowing and experimenting, making-with urban…

Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…

Much psychological research depends on participants' diligence in filling out materials such as surveys. However, not all participants are motivated to respond attentively, which leads to unintended issues with data quality, known as careless responding. Our question is: how do different modes of data collection--paper/pencil, computer/web-based,…

The "on-time" degree completion crisis within the community college system is alarming. Only 5% of students graduate in two years (Complete College America [CCA], n.d.-a). Many community college students are low-income and racially and ethnically minoritized, and their graduation rates are low (CCA, n.d.-a). Community colleges around the…

Tutorials for EXperimentalisT Interactive LEarning (TEXTILE) is an interactive semi-linear module-based curriculum for training students at various educational levels on data science methodologies currently utilized by research laboratories. We show how we developed our eleven module TEXTILE program to train 15 students from high school,…