Using Analytics to Evaluate Influences on Student Learning Outcomes in a GenEd Science Course (G131, Oceans & Our Global Environment)

This proposal seeks to utilize analytics on student demographics and grade records in combination with data on their performance in the GenEd NMS class G131 “Oceans and Our Global Environment” to assess how performance in the class and its range of assignments may be related to specific student characteristics. The project is structured to examine such connections by testing six specific hypotheses: (i) Are all students equally successful in G131 irrespective of their gender, race, or citizenship?, (ii) Does success in G131 reflect a student’s scientific background?, (iii) Is student performance in subsequent science classes enhanced by success in G131?, (iv) Is there a relationship between the success of students in G131 and their class standing?, (v) Does the online version of G131 yield equivalent outcomes to the traditional format?, (vi) Does success in G131 online reflect prior experiences with online courses, and does it bolster students’ success when taking other online classes? The results obtained from evaluation of the analytics data, including relationships examined using statistical methods, will be used to identify modifications to G131 that should be implemented (e.g., changes to help students disadvantaged by their prior science background, decrease withdrawal rates, enhance performance in subsequent classes) to improve the learning outcomes of students when the course is revised during 2017/18. The overall aim of the project is to use analytics to identify what characteristics serve as predictors for student performance in G131 and determine how revisions to the course may help enhance student success in this class.