Investment in technological subsystems to support the activity of teaching and learning and the various areas of the life of Higher Education Institutions (HEI) is of increasing importance in the implementation of the policy and strategy of these organizations. Each of these subsystems collects a huge amount of data that, if properly organized,…

Innovation and knowledge creation call for high-level epistemic agency and design-mode thinking, two competencies beyond the traditional scopes of schooling. In this paper, we discuss the need for learning analytics to support these two competencies, and more broadly, the demand for education for innovation. We ground these arguments on a…

The purpose of this article is to introduce readers to phenomenological inquiry, an inductive qualitative research approach that is rooted in the philosophical proposition that researchers can gain valuable insight into the structure of how people understand their experiences. It is assumed that there is a structure or essence to the meaning…

Purpose: The purpose of this study was to present normative data of tympanometric measurements of wideband acoustic immittance and to characterize wideband tympanograms. Method: Data were collected in 84 young adults with strictly defined normal hearing and middle ear status. Energy absorbance (EA) was measured using clicks for 1/12-octave…

Universities need to keep up with the demand of the business world when it comes to Big Data. The exponential increase in data has put additional demands on academia to meet the big gap in education. Business demand for Big Data has surpassed 1.9 million positions in 2015. Big Data, Business Intelligence, Data Analytics, and Data Mining are the…

This study aimed to investigate pre-service pre-school education teachers' data representation activities in terms of their relation to real life, the appropriateness of the data that the children can collect, the conformability of the graphs required for the data representation to the children's level, and the clarity of open-ended questions…

This qualitative study focuses on capturing students' understanding two visualizations often utilized by learning analytics-based educational technologies: bar graphs, and line graphs. It is framed by Achievement Goal Theory--a prominent theory of students' academic motivation--and utilizes interviews (n = 60) to investigate how students at risk…

Big data analysis involves the examination of large sets of data in order to uncover patterns and trends. Within the social studies or history classroom, such analyses can be effective for gaining insights into historical trends over time or across geographical regions. For instance, using simple technology tools, students can perform word…

Students who are at risk for or show low-intensity behavioral problems may need targeted, Tier 2 interventions. Often, Tier 2 problem-solving teams are charged with monitoring student responsiveness to intervention. This process may be difficult for those who are not trained in data collection and analysis procedures. To aid practitioners in these…

Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…

Over the last decade, there has been a steady increase in the number of Indigenous graduate research students in Australia, yet research and pedagogy has not kept pace with changes underway in the sector. From an extensive search of literature published between 2000 and 2017, 15 papers (representing 10 research projects conducted by seven teams or…

In the Australian higher education sector, the challenges to successful engagement and retention experienced by Aboriginal and/or Torres Strait Islander students and communities are considerable. They persist despite many well-intentioned attempts to address this issue and to strengthen equity in participation in the sector. Implicated in this is…

This book provides a comprehensive introduction by an extraordinary range of experts to the recent and rapidly developing field of learning analytics. Some of the finest current thinkers about ways to interpret and benefit from the increasing amount of evidence from learners' experiences have taken time to explain their methods, describe examples,…

Interdisciplinarity requires the collaboration of two or more disciplines to combine their expertise to jointly develop and deliver learning and teaching outcomes appropriate for a subject area. Curricula and assessment mapping are critical components to foster and enhance interdisciplinary learning environments. Emerging careers in data science…

Building on a study conducted by the authors, this article provides strategies for teaching data literacy and outlines the case-based teaching method as an effective way of developing data-literate teachers.