Creativity is an imperative skill for today's learners, one that has important contributions to issues of inclusion and equity in education. Therefore, assessing creativity is of major importance in educational contexts. However, scoring creativity based on traditional tools suffers from subjectivity and is heavily time- and labour-consuming. This…

Prompting students to generate constructed responses as they read provides a window into the processes and strategies that they use to make sense of complex text. In this study, Markov models examined the extent to which: (1) patterns of strategies; and (2) strategy combinations could be used to inform computational models of students' text…

In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…

In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and…

More research is needed on how to best use analytics to support educational decisions and design effective learning environments. This study was to explore and mine the data captured by a digital educational game designed for middle school science to understand learners' behavioral patterns in using the game, and to use evidence-based findings to…

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…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…

The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…

Violations of normality and homogeneity are common in educational data. When this occurs, the use of parametric statistics may be inappropriate. A generalized form of nonparametric analyses based on the Puri and Sen L statistic provides an alternative approach. Using a chi-square distribution, this technique is easy to apply and has significant…

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 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…

Science literacy, which is included in Programme for International Student Assessment (PISA) as an assessment area, is an important research and discussion area of science education literature with all its dimensions. In this study, the clustering results of the students from 34 Organization for Economic Cooperation and Development (OECD)…