The primary technique that many researchers use to analyze data from randomized control trials (RCTs)--detecting the average treatment effect (ATE)--imposes assumptions upon the data that often are not correct. Both theory and past research suggest that treatments may have significant impacts on subgroups even when showing no overall effect.…

The number of unique words in children's speech is one of most basic statistics indicating their language development. We may, however, face difficulties when trying to accurately evaluate the number of unique words in a child's growing corpus over time with a limited sample size. This study proposes a novel technique to estimate the latent number…

Higher education administrators lack strong understanding about using course evaluation data to make judgments and decisions. Using archival student course evaluation data from a pharmacy school, we examined (a) course evaluation instrument reliability and validity; (b) bivariate relationships between eight course rating items and the overall…

In this brief, the authors examine the level of access to school counselors, and how this access is mediated by district demographic and location characteristics. Using a large nationally representative data source compiled from the 2013-2104 Civil Rights Data Collection (CRDC), the 2014 Small Area Income and Poverty Estimates (SAIPE), and 2007…

"Which preschool programs best prepare students for kindergarten?" "Which students from which schools need remediation classes in higher education?" "How successful are college graduates in the workforce by major or credential?" These are just a few of the questions that can be answered by a robust longitudinal data…

In this dissertation, I create a navigable path between the learning sciences, accounting information systems (AIS), and analytics education. After considering the context of AIS and accounting analytics education, I present a learning sciences design framework, apply the design principles, and study their implementation and success in an…

We present an analysis of log data from a semester's use of the OpenDSA eTextbook system with the goal of determining the most difficult course topics in a data structures course. While experienced instructors can identify which topics students most struggle with, this often comes only after much time and effort, and does not provide real-time…

We propose a novel tensor factorization approach, Feedback-Driven Tensor Factorization (FDTF), for modeling student learning process and predicting student performance. This approach decomposes a tensor that is built upon students' attempt sequence, while considering the quizzes students select to work with as its feedback. FDTF does not require…

The COVID-19 pandemic disrupted education provision at an unprecedented scale, with education systems around the world being impacted by extended school closures and abrupt changes to normal school operations. The Responses to Educational Disruption Survey (REDS) investigated how teaching and learning were affected by the health crisis, and how…

With the continued adoption of learning analytics in higher education institutions, vast volumes of data are generated and "big data" related issues, including privacy, emerge. Privacy is an ill-defined concept and subject to various interpretations and perspectives, including those of philosophers, lawyers, and information systems…

The OECD's PISA exercise has by now been widely critiqued. Whilst we agree with most concerns, we begin with the assumption that PISA will remain an enduring and powerful feature of the global educational landscape. Even if the PISA test itself were discontinued, a similar large-scale quantitative assessment exercise would soon arise to take its…

This paper examines recent political debates surrounding data disaggregation in education policy in one US state, and analyses the discourses taken up by supporters and opponents of these policies. Analysis suggests how discourses move across time and space, and focuses on how these discourses are contextualized and entextualized in social media,…

The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…

The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary. Conventional methods used to anticipate…

Background: In the context of Texas of the USA, House Bill 5 signifies a major policy shift requiring entering high school students starting in fall 2014 to choose an endorsement, like science, technology, engineering, and mathematics (STEM) being one of them, to provide students with earlier exposure to a coherent course sequence. As we barely…