Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…

It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…

Background: Despite the usefulness of systematic reviews and meta-analyses, they are time-consuming and labor-intensive (Michelson & Reuter, 2019). The technological advancements in recent years have led to the development of tools aimed at streamlining the processes of systematic reviews and meta-analyses. Innovations such as Paperfetcher…

A vast amount of published scholarly literature is generated every day. Today, it is one of the biggest challenges for organisations to extract knowledge embedded in published scholarly literature for business and research applications. Application of text mining is gaining popularity among researchers and applications are growing exponentially in…

This paper presents a mobile application aimed at enhancing the financial literacy of college students by monitoring their spending patterns and promoting better decision-making. The application is developed using the agile methodology with Android Studio and Flutter as development tools and Firebase as a database. The app is divided into…

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…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

In the higher education context, an increasing concern on the technical or instrumental approach permeates attention to academics' data literacies and faculty development. The need for data literacy to deal specifically with the rise of learning analytics in higher education has been raised by some authors, though in spite of some focus on the…

Social media can contribute to an inclusive society, but they are also asymmetrical and polarised communication spaces. This requires competent teachers to build critical digital citizenship. The aim of this article is twofold: to present web scraping and text analytics as tools that define teachers' digital competences, and to investigate which…

The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…

This paper describes and evaluates a computerized system, MATCH, which is being used in South Carolina to match or link student records from year to year. The functioning of MATCH and its specific features are described, and its use in matching student test scores is detailed. The problem of mismatched records and the use of visual editing to…

This guidebook is designed for data analysts who are working with computer data files that contain records with incomplete data. It indicates choices the analyst must make and the criteria for making those choices in regard to the following questions: (1) What resources are available for performing the imputation? (2) How big is the data file? (3)…