Over the past decade, machine learning has become an integral part of educational technologies. With more and more applications such as students' performance prediction, course recommendation, dropout prediction and knowledge tracing relying upon machine learning models, there is increasing evidence and concerns about bias and unfairness of these…

Schools across the United States suffer from low on-time graduation rates. Targeted interventions help at-risk students meet graduation requirements in a timely manner, but identifying these students takes time and practice, as warning signs are often context-specific and reflected in a combination of attendance, social, and academic signals…

Student state testing, annual teacher evaluation, and A-to-F campus and school district rating are here. And all of these have real policy implications for every school system. With seven thousand students a day dropping out of the public schools in the United States at a rate of one student every 26 seconds, what might be done to help these…

Children who exhibit disruptive behavior often do so across multiple settings (e.g., home and school) and are vulnerable to many negative outcomes, including low achievement scores and academic grades, high school dropout, and increased school suspensions. Family-school partnership interventions, which are grounded in ecological theory, are highly…

The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50-60%. At the college level in the US only 30% of students graduate from…