This study investigated how one's problem-solving style impacts his/her problem-solving performance in technology-rich environments. Drawing upon experiential learning theory, we extracted two behavioral indicators (i.e., planning duration for problem solving and human-computer interaction frequency) to model problem-solving styles in…

Educational Data Mining (EDM) is an emerging field that aims to better understand students' behavior patterns and learning environments by employing statistical and machine learning methods to analyze large repositories of educational data. Analysis of variable data in the early stages of a course might be used to develop a comprehensive…

The objective of this study is to present and discuss how data visualization can be incorporated into teaching approaches by business faculty in introductory business statistics to strengthen business students' practical skills. Data visualization lessens difficulties in learning statistics by providing opportunities to illustrate analytical…

Over the last years there has been a growing interest in the use of educational games as learning tools. Educational games have proven to contribute in enhancing student motivation, increasing their engagement and providing them with personalized and adaptive learning. Learner modeling is a prerequisite when it comes to adaptive learning; it is…

Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at…

The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…

Purpose: The primary goal of this commentary was to consider the future directions that researchers dealing with levels and regulation of strategies and with approaches to learning may wish to pursue in the years to come. Procedure: In order to accomplish this goal, the first step was to look for any common ground shared by authors contributing to…

The paper aims to present application of Educational Data Mining and particularly Case-Based Reasoning (CBR) for students profiling and further to design a personalised intelligent learning system. The main aim here is to develop a recommender system which should help the learners to create learning units (scenarios) that are the most suitable for…

Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes and behaviors through surveys and questionnaires. This approach presents several weaknesses including the lack of self-awareness of…

Sophisticated technology advances are delivering new and powerful ways for marketers to collect and use consumer data. These data-driven marketing capabilities present a unique challenge for students, as they will soon be expected to manage consumer data and make business decisions based on ethical, legal, and fiscal considerations. This article…

This study examined the effectiveness of guided data-driven learning (DDL) activities on helping technological university students with a lower-intermediate proficiency level to learn grammar and vocabulary topics for the TOEIC test. The question of whether inductive learners make more progress than deductive learners was also addressed. A total…

Nowadays, Massive Open Online Courses (MOOCs) have obtained a rapid development and drawn much attention from the areas of learning analytics and artificial intelligence. There are lots of unstructured data being generated in online reviews area. The learning behavioral data become more and more diverse, and they prompt the emergence of big data…

Purpose: The purpose of this study is to empirically explore how managers differ from non-managers with regard to learning skills as competencies and learning style in a public-sector work setting. The paper also examined how learning style affects competency development. Design/methodology/approach: This study applied Kolb's experiential learning…

In the identification process, there may be gifted students who may be unnoticed or students who are misdiagnosed and are disappointed. In this context, this study is a step that may solve these two problems about the identification of mathematically gifted students with the help of data mining, which is data analysis methodology that has been…

College graduates need better preparation for and experience in data analytics for higher-quality problem solving. Using the curriculum innovation framework of Borin, Metcalf, and Tietje (2007) and case study research methods, we offer rich insights about one higher education institution's work to address the marketing analytics skills gap.…