High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…

Development of purpose is an important goal of post-secondary education. This study advances the measurement of purpose by (a) enriching the construct through incorporating the facet of horizon; (b) providing a framework for Rasch/Guttman Scenario score interpretation; and (c) providing evidence of convergent, divergent, and known groups validity.

As online learning platforms and computerized testing become more common, an increasing amount of data are collected about users. These data include, but are not limited to, response time, keystroke logs, and raw text. The desire to observe these features of the response process reflect an underlying interest in the cognitive processes and…

Nowadays, the assessment of student performance has become increasingly technology-based, a trend that can also be observed in the evaluation of scientific reasoning, with more and more of the formerly paper-based assessment tools moving into the digital space. The study aimed to examine the reliability and validity of the paper-based and…

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 study sought to assess the level of secondary students' scientific literacy in suburban schools in Malaysia and England, a research area which to date has not been fully explored in the literature. The study analyzed the data using the OECD's three domain-specific competencies of scientific literacy, namely: (i) explain phenomena…

The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…

The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…

Given growing interest in K-12 data and data science education, new approaches are needed to help students develop robust understandings of and familiarity with data. The model of the "quantified self"--in which data about one's own activities are collected and made into objects of study--provides inspiration for one such approach. By…