The variables of class attendance and the institution-wide Early Alert Grading System were employed to predict academic success at the end of the semester. Classroom attendance was found to be statistically and significantly related to final average and accounted for 14-16% of the variance in academic performance. Class attendance was found to…

This research brief provides highlights from the full report (published separately). In the report on AISD students, with a focus on the graduating class of 2009, the most powerful predictors of overall student dropout risk were having an 8th-grade attendance rate of less than 90% and failing both the 8th-grade reading and math TAKS tests. [For…

The most powerful predictors of overall dropout risk among Austin Independent School District (AISD) 9th graders were failing either the state of Texas reading or math TAKS tests, having school attendance below 90%, and being 16 years or older at the start of the school year.

Ninth-grade predictors of dropout risk among Austin Independent School District's English language learner students included the following: having an attendance rate below 90%, being 16 years or older, earning less than 5 course credits, attending a Title I campus and scoring beginning or intermediate on the state's English proficiency assessment…

In this report on AISD students, with a focus on the graduating class of 2009, the most powerful predictors of overall student dropout risk were having an 8th-grade attendance rate of less than 90% and failing both the 8th-grade reading and math TAKS tests. A separate research brief also was published. [For the research brief, see ED628171.]

This qualitative case study considers factors such as difficulty of understanding mathematics and poor mathematics practicing strategy under academic factors and lack of family support under social factors as those that contribute to the failure. Many students entering community college have deficiencies in mathematics background and are required…

The main aim of this study was to gain a better understanding of why students abandon their studies, or perform less well than expected given their high school grades, and to develop predictive models that can help identify those students most at-risk at the time they enter college. This will allow teachers and those responsible for student…