The data revolution has given citizens access to enormous large-scale open databases. In order to take into account the full complexity of data, we have to change the way we think in terms of the nature of data and its availability, the ways in which it is displayed and used, and the skills that are required for its interpretation. Substantial…

This paper investigates the intersection of big data and philosophy of education by considering big data's potential for addressing learning via a holistic process of coming-to-know. Learning, in this sense, cannot be reduced to the difference between a pre- and post-test, for example, as it is constituted at least as much by qualities of…

This study sought to explore the concept of mental toughness (comprising the attributes challenge, commitment, control, and confidence) from the perceptions of adolescents, to better understand their views on these attributes and the extent to which each were regarded as important within an educational setting. In total, 54 adolescents (31 female)…

As young children's perspectives are increasingly "taken seriously" across disciplines, the pursuit of authentic and ethical research with young children has become the subject of recent discussion. Much of this relates to listening "authentically" to (or understanding) young children, focusing on research design, ethics,…

This chapter explores lessons learned from two different learning analytics efforts at a large, public, multicampus university--one internally developed and one vended platform. It raises questions about how to best use analytics to support students while keeping students responsible for their own learning and success.

The many complex challenges posed by learning analytics can best be understood within a framework of structural justice, which focuses on the ways in which the informational, operational, and organizational structures of learning analytics influence students' capacities for self-development and self-determination. This places primary…

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

The undergraduate biochemistry laboratory curriculum is designed to provide students with experience in protein isolation and purification protocols as well as various data analysis techniques, which enhance the biochemistry lecture course and give students a broad range of tools upon which to build in graduate level laboratories or once they…

Purpose: The purpose of this paper is to describe an approach to analyzing qualitative data that uses Bakhtin's concepts of dialogue as a framework. Design/methodology/approach: Polyphonic Analysis (PA) is proposed as a critical approach to qualitative data analysis that emphasizes creating virtual dialogues of participants' voices, bringing…

When reviewing single-case design research, the What Works Clearinghouse (WWC) first reviews each single-case design experiment within a study (or research article) to determine whether it meets standards. For each experiment that meets standards, the WWC then uses visual analysis to characterize the evidence of a causal relationship. The WWC…

This case draws on the author's doctoral studies about practitioners' narratives of poverty in the early years. The case discusses how focus groups provide a useful way of exploring early years practitioners' (EY practitioners) understandings of child poverty. The research was based in two Sure Start Children Centres with onsite Nursery Schools…

This guide is designed for use by school, district, and state education agency staff to improve the effectiveness of efforts to collect and use discipline data, including reporting accurate and timely data to the federal government. It explains the importance of collecting discipline data, identifies key considerations for agencies implementing…

Educators are tasked with continually updating course objectives, content, assignments, and assessment to meet model curriculum guidelines. IS2020 proposes program level outcomes for required and elective areas. Two elective areas in IS2020 are Data and Business Analytics and Data and Information Visualization. IS2020 details 14 program level…

In today's age of information, the use of data is very powerful in making informed decisions. Data analytics is a field that is interested in identifying and interpreting trends and patterns within big data to make data-driven decisions. We focus on informal statistical inference and data modeling as a means of developing students' data analytics…

Learning analytics have proved promising capabilities and opportunities to many aspects of academic research and higher education studies. Data-driven insights can significantly contribute to provide solutions for curbing costs and improving education quality. This paper adopts a two-phase machine learning approach, which utilizes both…