The purpose of this paper is to present an empirical investigation of the critical determinants for the adoption of learning analytics in higher education. A conceptual model was proposed to understand better the adoption of learning analytics in higher education by teaching staff. Structural equation modelling is used for testing and validating…

Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…

The recent focus on learning analytics (LA) to analyze temporal dimensions of learning holds the promise of providing insights into latent constructs, such as learning strategy, self-regulated learning (SRL), and metacognition. These methods seek to provide an enriched view of learner behaviors beyond the scope of commonly used correlational or…

A distinctive feature of game-based learning environments is their capacity to create learning experiences that are both effective and engaging. Recent advances in sensor-based technologies such as facial expression analysis and gaze tracking have introduced the opportunity to leverage multimodal data streams for learning analytics. Learning…

This large-scale study was conducted for the purposes of determining how representative library users are compared to the whole student population, to explore how library services contribute to student success, and to position the library to be included in the institution's learning analytics landscape. To that end, data were collected as students…

In higher education, predictive analytics can provide actionable insights to diverse stakeholders such as administrators, instructors, and students. Separate feature sets are typically used for different prediction tasks, e.g., student activity logs for predicting in-course performance and registrar data for predicting long-term college success.…

CAL (Computer Assisted Learning) programs are widespread today in schools and families due to the effectiveness of CAL programs in improving students' learning and task performance. The flourishing of CAL programs in education has brought large amounts of students' learning data including log data, performance data, mouse movement data, eye…

We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the…

Innovative information and communication technologies have reformed higher education from the traditional way to smart learning. Smart learning applies technological and social developments and facilitates effective personalized learning with innovative technologies, especially smart devices and online technologies. Smart learning has attracted…

Learning analytics dashboards (LADs) can provide learners with insights about their study progress through visualisations of the learner and learning data. Despite their potential usefulness to support learning, very few studies on LADs have considered learners' needs and have engaged learners in the process of design and evaluation. Aligning with…

One of the biggest challenges for EFL (English as Foreign Language) students to learn English is the lack of practicing environments. Although language researchers have attempted to conduct flipped classrooms to increase the practicing time in class, EFL students generally have difficulties interacting with peers and teachers in English in class.…

Keystroke logs provide a comprehensive record of observable writing processes. Previous studies examining the keystroke logs of young L1 English writers performing experimental writing tasks have identified writing processes features predictive of the quality of responses. Contrarily, large-scale studies on the dynamic and temporal nature of L2…

In the era of digitalization of learning and teaching processes, Educational Data Literacy (EDL) is highly valued and is becoming essential. EDL is conceptualized as the ability to collect, manage, analyse, comprehend, interpret, and act upon educational data in an ethical, meaningful, and critical manner. The professionals in the field of…

In this research, the effect of the use of learning analytics (LA) based feedback as a metacognitive tool on the learners' transactional distance and motivation was examined. The research was carried out according to experimental design and was carried out on 81 university students. The students were randomly assigned to the experimental and…

Cyberlearning technologies increasingly seek to offer personalized learning experiences via adaptive systems that customize pedagogy, content, feedback, pace, and tone according to the just-in-time needs of a learner. However, it is historically difficult to: (1) create these smart learning environments; (2) continuously improve them based on…