One of the challenges of discussing validity arguments for machine scoring of essays centers on the absence of a commonly held definition and theory of good writing. At best, the algorithms attempt to measure select attributes of writing and calibrate them against human ratings with the goal of accurate prediction of scores for new essays.…

To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…

Despite decades of research, it has been difficult to achieve consensus on a definition of common learning disabilities such as dyslexia. This lack of consensus represents a fundamental problem for the field. Our approach to addressing this issue is to use model-based meta-analyses and Bayesian models with informative priors to combine the results…

In 2020, Year 12 students at John Curtin College of the Arts, were required to model COVID-19 data from five different countries in order to find correlations between daily infections and unemployment rates, in order to make future predictions. Work received from students demonstrated how the task successfully provided unique learning…

The so-called Diet Coke and Mentos experiment is initiated by dropping Mentos candies into a bottle of Diet Coke or other carbonated beverage. This causes the beverage to rapidly degas, causing foam to stream out of the bottle. Simple application of the gas laws leads to the straightforward prediction that ejection of greater foam volume is…

In this essay, findings from research in science and chemistry education are used to describe and discuss progression in students' structure-property reasoning through schooling. This work provides insights into the challenges that students face to master this important component of chemical thinking. The analysis reveals that student reasoning is…

Performance prediction has emerged as one of the most popular approaches to leverage large volume of online learning data. In the majority of current works, performance prediction is based on students' past activities in graded learning resources (such as problems and quizzes), while their activities in non-graded resources (such as reading…

Measures of student disadvantage--or risk--are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new…

This article describes activities in which students sample, investigate, classify, and compare characteristics (i.e., texture, color, density, porosity) of local soils, evaluating whether the soils are healthy or at risk. Students investigate correlations between geology and geography, predict which soil types may go extinct in their state, and…

A wide body of research has documented the relationship between social norms and individual behaviors. There is growing evidence that academic behaviors in early adolescence--when most children begin middle school--may be subject to normative influence as well. However, the structure and composition of peer relationships within middle schools have…

Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…

The goal of this article is to preserve and distribute the information presented at the LASI (2014) workshop on Coh-Metrix, a theoretically grounded, computational linguistics facility that analyzes texts on multiple levels of language and discourse. The workshop focused on the utility of Coh-Metrix in discourse theory and educational practice. We…

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

Research in the field of mental chronometry and individual differences has revealed several robust regularities (Jensen, 2006). These include right-skewed response time (RT) distributions, the worst performance rule, correlations with general intelligence ("g") that are more pronounced for RT standard deviations (RTSD) than they are for RT means…

The article first summarizes the assumptions of Luce (2004, 2008) for inherently binary (2-D) stimuli (e.g., the ears and eyes) that lead to a "p-additive," order-preserving psychophysical representation. Next, a somewhat parallel theory for unary (1-D) signals is developed for intensity attributes such as linear extent, vibration to finger, and…