Multimodality in learning analytics and learning science is under the spotlight. The landscape of sensors and wearable trackers that can be used for learning support is evolving rapidly, as well as data collection and analysis methods. Multimodal data can now be collected and processed in real time at an unprecedented scale. With sensors, it is…

In this paper, we compare the estimates of earnings determinants based on the non-probabilistic WageIndicator web survey with those based on the widely used, representative EU Study of Income and Living Conditions survey. Using 10 years of Dutch data, we show that there exists an established segment of predominantly junior workers from which the…

Depending on their motivational dispositions, students choose different learning strategies and vary in their persistence in reaching learning outcomes. As learning is more and more facilitated through technology, analytics approaches allow learning processes and environments to be analyzed and optimized. However, research on motivation and…

This article explores 6th-grade students' modelling with data in generating models for selecting an Australian swimming team for the (then) forthcoming 2016 Olympics, using data on swimmers' times at various previous events. We propose a modelling framework comprising four components: working in shared problem spaces between mathematics and…

Collecting data on behavior, academic skills, and Individualized Education Plan (IEP) goals is an essential step in showing student progress--but it can also be a complicated, time-consuming process. Take the worry and stress out of data collection with this ultra-practical resource, packed with the tools you need to organize, manage, and monitor…

This country note presents the results of an analysis of undertake Portugal undertaken within the Labour Market Relevance and Outcomes of Higher Education Partnership Initiative project. The project was implemented by the OECD with the support of the European Commission with the aim of helping policy makers and higher education institutions…

We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. ARPs…

Background/Context: Amidst the complex and fast-paced demands in schools and classrooms, identifying what most deserves educators' attention can pose a challenge. Indicators help focus attention by highlighting key features that signal important outcomes or opportunities to take action or learn. Purpose: Informed by multiple literatures, we offer…

Background/Context: Over the past decade early warning systems which use predictive indicators to identify students in need of additional supports to stay on track to high school graduation have spread from a few schools to most states. There is now a growing interest in extending the utility of early warning systems from high school graduation to…

The use of data to govern education is increasingly supported by the use of knowledge-based technologies, including algorithms, artificial intelligence (AI), and tracking technologies [Fenwick, T., E. Mangez, and J. Ozga. 2014. "Governing Knowledge: Comparison, Knowledge-Based Technologies and Expertise in the Regulation of Education."…

Student success is becoming a shared vision for quality in higher education. Majority data in higher education have not been transformed into actionable insights for quality enhancement. Data are dispersed among stakeholders, and stakeholders' data literacy influences the effectiveness of using data for student success. However, existing studies…

Law Enforcement Agencies gather intelligence in order to prevent criminal activity and "pursue" criminals. In the context of human intelligence collection, intelligence elicitation relies heavily upon the deployment of "appropriate" evidence-based interviewing techniques (a topic rarely covered in the extant research…

Unit nonresponse in panel data sets is often a source of bias. Why certain individuals attrite from longitudinal studies and how to minimize this phenomenon have been examined by researchers. However, this research has typically focused on data sets collected via telephone, postal mail, or face-to-face interviews. Moreover, this research usually…

The goal of this special issue is to examine the use of self-report measures in the study of motivation and strategy use. This commentary reviews the articles contained in this special issue to address the primary objective of determining if and when self-report measures contribute to understanding these major constructs involved in self-regulated…

The field of learning analytics has been limited by its frequent dependence on learning logs created by students while learning. Most of the research has dealt with the relationships between learning during a course and the achieved results. Although students' in-class behavior affects learning achievement, this remains a challenging aspect to…