In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…

The authors investigate coronavirus disease 2019 (COVID-19) risk factors, suitability of online instruction, politics, and institutions' finances as rationales guiding instructional delivery decisions for fall 2020, after COVID-19's emergence. Contributions include estimating multinomial logit regressions with mode of delivery as a categorical…

Background and Aims: The fastest growing group of students with disabilities are those with Autism Spectrum Disorder (ASD). States annually report on post-high school outcomes (PSO) of exited students. This study sought to fill two gaps in the literature related to PSO for exited high-school students with ASD and the use of state data and…

Through a mixed-methods approach that utilized teacher surveys and a focus group with computer science (CS) instructional coaches, this study examined elementary teachers' confidence in meeting the needs of students with disabilities, the extent to which the teachers could use the Universal Design for Learning (UDL) framework in CS education, and…

There is a lack of teacher education materials that develop equity literacy in content courses for preservice secondary mathematics teachers. In response, we created teacher education curriculum materials for introductory statistics that include an integrated focus on developing equity literacy and critical statistical literacy. In this article,…

This article describes experiences with teaching process data analytics and machine learning, including in: (1) a joint undergraduate/graduate course for students in chemical and mechanical engineering and engineering management; and (2) an undergraduate chemical engineering concentration in process data analytics. The article also describes…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

During the COVID-19 pandemic, people across the globe have been exposed to large amounts of statistical data. Previous studies have shown that individuals' mathematical understanding of health-related information affects their attitudes and behaviours. Here, we investigate the relation between: (1) basic numeracy; (2) COVID-19 health numeracy; and…

This study evaluated a scheduling methodology referred to as intervention-based scheduling to address the problem of practice regarding the fidelity of implementing Response to Intervention (RtI) in an existing school schedule design. Employing panel data, this study used fixed-effects regressions and first differences ordinary least squares (OLS)…

A much larger proportion of English 14-year-olds expect to apply to university than ultimately make an application by age 21, but the proportion expecting to apply falls from age 14 onwards. In order to assess the role of socioeconomic status in explaining changes in expectations, this paper applies duration modelling techniques to the…

The aim of this study is to investigate interrelationships between overexcitability and learning patterns from the perspective of personality development according to Dabrowski's theory of positive disintegration. To this end, Bayesian structural equation modeling (BSEM) is applied which allows for the simultaneous inclusion in the measurement…

Recently, studies have adopted fixed effects modeling to identify the returns to college. This method has the advantage over ordinary least squares estimates in that unobservable, individual-level characteristics that may bias the estimated returns are differenced out. But the method requires extensive longitudinal data and involves complex…

High dimensional multivariate data, where the number of variables approaches or exceeds the sample size, is an increasingly common occurrence for social scientists. Several tools exist for dealing with such data in the context of univariate regression, including regularization methods such as Lasso, Elastic net, Ridge Regression, as well as the…

We have been looking at two different numbers that have been used to describe the availability of physics in U.S. high schools: 60% and 95%. Last month we noted that the U.S. Department of Education Office of Civil Rights (OCR) includes over 7,000 more public schools in the denominator than American Institute of Physics (AIP) Statistics does.…

This brief examines student psychological well-being, an important issue of growing interest in U.S. higher education. Extensive research focused on student involvement in college suggested that quality involvement leads to higher levels of student learning and development. This study for psychological well-being was measured using the Ryff Scales…