Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…

This study employs advanced data mining techniques to investigate the DASS-42 questionnaire, a widely used psychological assessment tool. Administered to 680 students at Necmettin Erbakan University's Ahmet Kelesoglu Faculty of Education, the DASS-42 comprises three distinct subscales--depression, anxiety and stress--each consisting of 14 items.…

This paper explores using data mining in English teaching assessment in higher education within the 'Internet + Education' era. Traditional assessment methods struggle to meet modern teaching needs. By collecting diverse data like student performance and learning behavior, and employing data mining, a comprehensive assessment model is built. This…

In educational data mining (EDM), preprocessing is an arduous and complex task and must promote an appropriate treatment of data to solve each specific educational problem. In the same way, the parameters used in the evaluation of postprocessing results are decisive in the interpretation of the results and decision-making in the future. These two…

In crowdsourcing ideation websites, companies can easily collect large amount of ideas. Screening through such volume of ideas is very costly and challenging, necessitating automatic approaches. It would be particularly useful to automatically evaluate idea novelty since companies commonly seek novel ideas. Four computational approaches were…

We examined how Learning Analytics literature represents participants from diverse societies by comparing the studies published with samples from WEIRD (Western, Industrialized, Rich, Democratic) nations versus non-WEIRD nations. By analyzing the Learning Analytics studies published during 2015-2019 (N = 360), we found that most of the studies…

Influence diagrams, derived from the mystery method as its learning output, represent an externalization of systems thinking and are, therefore, valid to research; so far they have not been conceptualized in the research literature for teaching systems thinking in education for sustainable development. In this study, 31 of those diagrams are…

The article shows the role of data mining methods at the stages of the e-learning risk management for the various participants. The article proves the e-learning system fundamentally contains heterogeneous information, for its processing it is not enough to use the methods of mathematical analysis but it is necessary to apply the new educational…

The purpose of this research is to examine the research that has been done on MOOCs by applying data mining and analytic approaches and to depict the current state of MOOC research. The text mining revealed four broad themes: (I) MOOCs as a mainstreaming learning model in HE, (II) motivation and engagement issues in MOOCs, (III) assessment issues…

Question classification is a key point in many applications, such as Question Answering (QA, e.g., Yahoo! Answers), Information Retrieval (IR, e.g., Google search engine), and E-learning systems (e.g., Bloom's tax. classifiers). This paper aims to carry out a systematic review of the literature on automatic question classifiers and the technology…

Purpose: In this study, Logistic Regression (LR), CHAID (Chi-squared Automatic Interaction Detection) analysis and data mining methods are used to investigate the variables that predict the mathematics success of the students. Research Methods: In this study, a quantitative research design was employed during the data collection and the analysis…

Collecting (or "sampling") information that one expects to be useful is a powerful way to facilitate learning. However, relatively little is known about how people decide which information is worth sampling over the course of learning. We describe several alternative models of how people might decide to collect a piece of information…

Net Promoter System (NPS) is well known as an evaluation measure of the growth engine of big companies in the business area. The ultimate goal of my research is to build an action rules and meta-actions based recommender system for improving NPS scores of 34 companies (clients) dealing with similar businesses in the US and Canada. With the given…

In the modern world, higher education is transitioning from enrollment mode to recruitment mode. This shift paved the way for institutional research and policy making from historical data perspective. More and more universities in the U.S. are implementing and using enterprise resource planning (ERP) systems, which collect vast amounts of data.…

How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…