Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…

Leading by doing takes an unwavering and visible commitment to an intentional, continuous improvement process. Teams at every system level distribute leadership to support effective practice so outcomes improve. Using a practice-based approach to improving mathematics outcomes, the Kentucky Department of Education (KDE) facilitated a continuous…

Interactive digital tools increasingly used for language learning can provide detailed system logs (e.g., number of attempts, responses submitted), and thereby a window into the user's learning processes. To date, SLA researchers have made little use of such data to understand the relationships between learning conditions, processes, and outcomes.…

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.…

To understand how learner metacognition and goal orientation affect learner problem-solving in a Serious Game (SG) environment, this study examined 12 undergraduate students' metacognition, goal orientations, and problem-solving performances and processes while playing a SG that adopts problem-based learning pedagogy to teach space science.…

This study explored science-related variables that have an impact on the prediction of science achievement groups by applying the educational data mining (EDM) method of the random forest analysis to extract factors associated with students categorized in three different achievement groups (high, moderate, and low) in the Korean data from the 2015…

This research was a mixed-methods study investigating how teachers in northeastern West Virginia use student data to drive their instructional decisions. This study also investigated teachers' perceptions of the data use on their instruction, their students, and themselves. Data collection for this research included both a cross-sectional survey…

Word frequency has a long history of being considered the most important predictor of word difficulty and has served as a guideline for several aspects of second language vocabulary teaching, learning, and assessment. However, recent empirical research has challenged the supremacy of frequency as a predictor of word difficulty. Accordingly,…

Purpose: With a growing need to assess multiple aspects of healthcare education, the goal of this study was to develop an innovative web-based application to streamline assessment processes and meet the increasingly complex role of the educational manager. Design/methodology/approach: AARDVARC (Automated Approach to Reviewing and Developing…

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…

Learning analytics (LA) has been increasingly using in teaching and learning. However, in the field of applied linguistics, the use of LA has only begun to touch the surface. There is a need for understanding how LA and learning design (LD) influence each other and provide useful information to language teachers in the context of specific courses…

We investigated the effects of proximal grouping of numbers, problem-solving goals to make 100, and prior knowledge on students' solution strategies in an online mathematics game. Logistic regression on 857 problem-level data points from 227 middle-school students showed that students were more likely to use productive solution strategies on…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

These proceedings contain the papers and poster of the 17th International Conference on Mobile Learning (ML 2021) and 8th International Conference on Educational Technologies (ICEduTech 2021), which were organised by the International Association for Development of the Information Society (IADIS). Due to an unprecedented situation caused by the…

New educational technologies present an opportunity to help teachers monitor and support their students remotely in Science, Technology, Engineering, and Mathematics (STEM). However, most technologies do not have the capacity to comprehensively assess and report on students' critical 21st century practice competencies (such as those described in…