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Incidence of sexually transmitted infections (STIs) is rising sharply in the United States. Between 2014 and 2019, incidence among men and women has increased by 62.8% and 21.4%, respectively, with an estimated 68 million Americans contracting an STI in 2018.a Some human behaviors impacting the expanding STI epidemic are unprotected sex and multiple sexual partners.b Increasing dating app usage has been postulated as a driver for increases in the numbers of people engaging in these behaviors. Using the proposed model, it is estimated that both STI incidence and prevalence for females and males have increased annually by 9%–15% between 2015 and 2019 due to dating apps usage, and that STI incidence and prevalence will continue to increase in the future. The model is also used to assess the possible benefit of in-app prevention campaigns. 

A model combines demographic data provided by the United States Census Bureau for 2021 with survey data on sexual activity from the Centers for Disease Control and Prevention to estimate the structure by age and sex of the sexually active population in the United States. It also provides the proportions of newly sexually active people by age and sex. The model is based on percentages of sexually active people by age and sex, and on an ordinary differential equation formalizing a “learning process” for the years 2009 to 2019. The data produced fit well with the empirical data for each age and sex. 

An algebraic model uses a set of algebraic equations to describe a situation. Constructing such models is a fundamental skill, but many students still lack the skill, even after taking several algebra courses in high school and college. For such students, we developed instruction that taught students to decompose the to-be-modelled situation into schema applications, where a schema represents a simple relationship such as distance-rate-time or part-whole. However, when a model consists of multiple schema applications, it needs some connection among them, usually representedby letting the same variable appear in the slots of two or more schemas. Students in our studies seemed to have more trouble identifying connections among schema applications than identifying the schema applications themselves. We developed several tutoring systems and evaluated them in university classes. One of them, a step-based tutoring system called OMRaaT (One Mathematical Relationship at a Time), was both reliably superior (p = 0.02, d = 0.67) to baseline and markedly superior (p < 0.001, d = 0.84) to an answer-based tutoring system using only commercially available software (MATLAB Grader). 

An algebraic model uses a set of algebraic equations to describe a situation. Constructing such models is a fundamental skill, but many students still lack the skill, even after taking several algebra courses in high school and college. For underachieving college students, we developed a tutoring system that taught students to decompose the to-be-modelled situation into schema applications, where a schema represents a simple relationship such as distance-rate-time or part-whole. However, when a model consists of multiple schema applications, it needs some connection among them, usually represented by letting the same variable appear in the slots of two or more schemas. Students in our studies seemed to have more trouble identifying connections among schemas than identifying the schema applications themselves. This paper describes a newly designed tutoring system that emphasizes such connections. An evaluation was conducted using a regression discontinuity design. It produced a marginally reliable positive effect of moderate size (d = 0.4).