In the contemporary society a massive amount of data is generated continuously by various means, and they are called Big-Data sets. Big Data has potential and limits which need to be understood by statisticians and statistics consumers, therefore it is a challenge to develop Big-Data Literacy to support the needs of constructive, concerned, and…

This is the decade of data analytics and big data, but not everyone agrees with the definition of big data. Some researchers see it as the future of data analysis, while others consider it as hype and foresee its demise in the near future. No matter how it is defined, big data for the time being is having its glory moment. The most important…

Big qualitative data (Big Qual), or research involving large qualitative data sets, has introduced many newly evolving conventions that have begun to change the fundamental nature of some qualitative research. In this methodological essay, we first distinguish big data from big qual. We define big qual as data sets containing either primary or…

In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…

Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…

Language education has a rich history of research and scholarship focusing on the effectiveness of learning activities and the impact these have on student behaviour and outcomes. One of the basic assumptions in foreign language pedagogy and CALL in particular is that learners want to be able to communicate effectively with native speakers of…

As the availability of high-throughput data-collection technologies, such as information-sensing mobile devices, remote sensing, internet log records, and wireless sensor networks has grown, science, engineering, and business have rapidly transitioned from striving to develop information from scant data to a situation in which the challenge is now…

Purpose: The purpose of this paper is to demonstrate the utility of combining event-centred and variable-centred approaches when analysing big data for higher education institutions. It uses a large, university-wide data set to demonstrate the methodology for this analysis by using the case study method. It presents empirical findings about…

We are now living in an era of big data. From the perspective of data analysis of classroom questioning, the paper chooses three districts in City B that have significant differences. These are educationally developed District D, less developed District F, and developing District M. The study uses the stratified sampling method to choose from…

Quantitative modelling plays an important role as biology increasingly deals with big data sets, relies on modelling to understand system dynamics, makes predictions about impacts of changes, and revises our understanding of system interactions. An assessment of quantitative modelling in biology was administered to students (n = 612) in…

The term data scientist has only been in common use since 2008, but in 2016 it is considered one of the top careers in the United States. The purpose of this paper is to explore the growth of data science content areas such as analytics, business intelligence, and big data in AACSB Information Systems (IS) programs between 2011 and 2016. A…

The need for analysts with expertise in big data software is becoming more apparent in today's society. Unfortunately, the demand for these analysts far exceeds the number available. A potential way to combat this shortage is to identify the software taught in colleges or universities. This article will examine four data analysis software--Excel…

Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…

In the information age, one of the most influential institutions is education. The recent emergence of MOOCS [Massively Open Online Courses] is a sample of the new expectations that are offered to university students. Basing decisions on data and evidence seems obvious, and indeed, research indicates that data-driven decision-making improves…

In the era of Big Data, because of diminishing cost of data collection and storage, a large number of statistical tests may even possibly be conducted all together by a high school student to seek for some "exciting" new scientific findings. In this article, we propose an interesting approach to introduce students to some important…