Machine learning is a powerful method for predicting the outcomes of interactions with educational software, such as the grade a student is likely to receive. However, a predicted outcome alone provides little insight regarding how a student's experience should be personalized based on that outcome. In this paper, we explore a generalizable…

New student success interventions generate costs for colleges (for example, staff time and supplies). However, if they lead more students to remain enrolled, cause students to attempt more credits, and improve longer-term student outcomes, they can also generate tuition revenue and state funding (for public institutions in states that allocate…

Given the rapid growth of K-12 online learning, research is needed in the effective identification of at-risk students so that administrators and teachers can develop appropriate supports and interventions. The purpose of this research was to determine if student success in an online course could be predicted for English Learners (EL) using…

Upon the advent of the COVID-19 pandemic, hundreds of higher education institutions in the United States temporarily or permanently adopted test- optional admissions policies. Growth in the number of test- optional institutions and the longstanding criticism of standardized admissions tests as limited and unreliable predictors of college success…

Soliciting predictions about hypothetical memory performance (without having participants engage in a related memory task) is a simple way for researchers to examine people's metacognitive beliefs about how memory functions. Using this methodology, researchers can vary what information is provided as part of the scenario or how the memory…

The "surprisingly popular" method (SP) of aggregating individual judgments has shown promise in overcoming a weakness of other crowdsourcing methods--situations in which the majority is incorrect. This method relies on participants' estimates of other participants' judgments; when an option is chosen more often than the average…

Completion of a first-semester chemistry (Chem I) course lays the foundation for understanding second-semester chemistry (Chem II) topics. The purpose of this study is to evaluate the influence of basic arithmetic skills on students' Chem II success in understanding mathematics-grounded concepts (e.g., solutions and aqueous reactions, kinetics,…

Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…

One of the key findings of prospect theory is that people tend to treat potential gains differently to potential losses. Consistent with earlier findings across a range of areas, pilots were risk averse when faced with an uncertain situation involving monetary gains and risk seeking when faced with a monetary loss. Prospect theory has largely been…

The Hill equation, which models the cooperative ligand-receptor binding equilibrium, turns out to be useful in modeling the progression of infectious disease outbreaks such as CoViD-19. The equation fits well the data for total and daily case numbers, allows tentative predictions for the half-point and end point of the epidemic, and presents a…

Purpose: We sought to critically analyze and evaluate published evidence regarding feasibility and clinical potential for predicting neurodevelopmental outcomes of the frequency-following responses (FFRs) to speech recordings in neonates (birth to 28 days). Method: A systematic search of MeSH terms in the Cumulative Index to Nursing and Allied…

Over the last decade, iterated learning studies have provided compelling evidence for the claim that linguistic structure can emerge from non-structured input, through the process of transmission. However, it is unclear whether individuals differ in their tendency to add structure, an issue with implications for understanding who are the agents of…

College-level statistics courses emphasize the use of the coefficient of determination, R-squared, in evaluating a linear regression model: higher R-squared is better. This often gives students an impression that higher R-squared implies better predictability since textbooks tend to use sample data to support the theory and students rarely have an…

In E-Learning Systems, the automatic detection of the learners' learning styles provides a concrete way for instructors to personalize the learning to be made available to learners. The classification techniques are the most used techniques to automatically detect the learning styles by processing data coming from learner interactions with the…

Students have difficulty bridging the conceptual gap between Newtonian and relativistic physics, and, consequently, the teaching of special relativity has been discussed extensively in the literature. A comprehensive list of such references is too large to include, but a brief list is given. In this paper, the author presents several exercises,…