The quality of the data and the amount of correct information available is key to informed decision-making. Higher education institutions (HEIs) often employ various decision support systems (DSSs) to make better choices. However, there is a lack of systems to assist with decision-making to promote innovation in teaching and learning. In this…

Universities are increasingly turning toward data-driven technologies like data dashboards to support advisors' work in student success, yet little empirical work has explored whether these tools help or hinder best practices in advising, which is in many ways a relationship-based enterprise. This mixed-methods study analyzed whether and why the…

This study examines second language (L2) learners' perspectives regarding the affordances and challenges of using the Data-Driven Learning (DDL) to identify the properties of near-synonymous words. Employing a convergent mixed-method design, this study deciphers the perceptions of 40 undergraduate L2 learners majoring in English language teaching.…

The ability of automatically modeling learners' personalities is an important step in building adaptive learning environments. Several studies showed that knowing the personality of each learner can make the learning interaction with the provided learning contents and activities within learning systems more effective. However, the traditional…

Current technologies for qualitative data analysis treat all types of data analysis as a homogeneous category, and for this reason, the value of other technologies for a discourse analysis of transcripts is not well examined. Therefore, the current study addresses how qualitative data can be analyzed by a learning analytic tool, such as Knowledge…

Purpose: This study explores ongoing research into self-mapped learning pathways that students utilize to move through a course when given two modalities to choose from: one that is instructor-led and one that is student-directed. Design/methodology/approach: Process mining analysis was utilized to examine and cluster clickstream data from an…

One of the major factors affecting student learning is feedback. Although the importance of feedback has been recognized in educational institutions, dramatic changes--such as bigger class sizes and a more diverse student population--challenged the provision of effective feedback. In light of these changes, educators have increasingly been using…

Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…

If universities want to survive into the century while maintaining relevancy to the business world and the global market, they must utilize innovative methods that engage students from the time of admission through graduation. Successful engagement equates to economic growth and positive branding. Students who are 'invested' and feel that the…

Aside from learning the basic and common grammatical structures, English as foreign language learners ("hereafter EFL") have to be familiar with a wide range of lexical chunks called collocations. Being sensitive to collocations is the key of attaining a native-like fluency in English. The aim of this study is twofold: to explore the…

Data-Driven Learning (DDL) is a method for learning languages that involves analyzing language usage trends and finding patterns in language data, utilizing technology and statistics. One of the key benefits of DDL is that it allows students to focus on the most relevant and useful language data for their needs. Data-driven learning is an…