The paper aims to present application of Educational Data Mining and particularly Case-Based Reasoning (CBR) for students profiling and further to design a personalised intelligent learning system. The main aim here is to develop a recommender system which should help the learners to create learning units (scenarios) that are the most suitable for…

This article is a response to an article written by Wang and Ma "An Examination of Plausible Score Correlation from the Trend in Mathematics and Science Study", published in the Athens Journal of Education. The purpose of this paper is to address issues with Wang's and Ma's suggestion to use analysis method for correlating plausible…

This study investigates the impact of different modes and tailor-made response enhancing measures (TMREM)--such as bilingual interviewers with a shared ethnic background and translated questionnaires--on the measurement of substantive variables in surveys among minority ethnic groups in the Netherlands. It also provides insight into the ability to…

Educational data mining constitutes a recent research field which gained popularity over the last decade because of its ability to monitor students' academic performance and predict future progression. Numerous machine learning techniques and especially supervised learning algorithms have been applied to develop accurate models to predict…

Founded on the need to help university students develop a greater academic metacognitive capacity, student-facing learning analytics are considered useful tools for making students overtly aware of their own learning processes, helping students to develop control over their learning, and subsequently supporting more effective learning. However,…

Longitudinal administrative data generated by public education systems in the United States have become increasingly available and have tremendous potential to inform policy research. While it is tempting to take the accuracy of administrative data for granted, there are reasons why researchers should approach these data with a degree of caution.…

Aimed at a massive outreach and open access education, Massive Open Online Courses (MOOC) has evolved incredibly engaging millions of learners' over the years. These courses provide an opportunity for learning analytics with respect to the diversity in learning activity. Inspite of its growth, high dropout rate of the learners', it is examined to…

When data for multiple outcomes are collected in a multilevel design, researchers can select a univariate or multivariate analysis to examine group-mean differences. When correlated outcomes are incomplete, a multivariate multilevel model (MVMM) may provide greater power than univariate multilevel models (MLMs). For a two-group multilevel design…

This article shows fundamental notions of one of the qualitative research methods, we refer to the hermeneutical phenomenology based on the theories of Van Manen, Raquel Ayala and Miguel Martínez. This approach leads to the description and interpretation of the essence of lived experiences, recognizes the meaning and importance in pedagogy,…

This article presents theoretical and empirical support for a data-driven instructional coaching approach and emerging evidence for the contributions of an online platform in operationalizing, assessing, and facilitating the implementation of key coaching actions for both research and practice. The contributions of an online platform in guiding…

School climate profoundly influences students' social, emotional, and academic functioning, representing an important indicator of student and school success. The federal Every Student Succeeds Act recognizes the importance of prioritizing positive learning conditions for all students and requires states to both include an indicator of…

California needs better data on the state's education systems to uncover and remedy systemic, long-standing racial and socioeconomic inequities. To create more just institutions, students, families, policymakers, educators, and advocates need access to quality, disaggregated data that allows them to answer questions about how well the state's…

Without the development and implementation of appropriate reforms directed by school district leaders, struggling schools may continue to achieve low scores on state-wide evaluations. Addressing this issue requires cooperation between administrators to identify areas of need, develop a plan of action for change, and implement and monitor a shared…

Most districts help teachers use data to improve student learning, often supporting this effort with federal funds. But many teachers feel unprepared to use student data to inform their instruction -- referred to as data-driven instruction (DDI) -- and there is little evidence of whether it improves student achievement. One hundred and two…

This paper discusses some of the recurrent issues which the authors have noticed in educational research. These might be concerned with the nature of social science research, such as its representation of the reality of student learning, the role for replication studies, and the tolerance for disagreements. There are also issues related to the…