In the traditional teaching mode, it is difficult for teachers to have a comprehensive understanding of each student's study, and it is also hard for them to provide targeted guidance and assistance. With the development of data collection and analysis technology, schools and educational institutions can make better use of big data technology to…

This paper first analyzed the shortcomings of the summative final exam methods which focuses only on final exams. Then, we showed the specific implementation of the quantitative formative assessment which includes objective results and subjective scores. Objective results include the traditional written chapter test score, online mid-term and…

This ethnographic case study, situated in Newfoundland and Labrador, Canada, examined the effects of full-scale provincial testing on families, its influences on homework, and familial accountability for teaching and learning. Data were drawn from family interviews, as well as letters and documents regarding homework. Teachers sensed a significant…

The undergraduate college years are a critical time when students are beginning to think seriously about their career interests, and it is critical that students have a positive outlook for their mathematical learning if they are going to pursue math-related STEM majors. The current research with 748 undergraduate math students found that the more…

In most mathematics textbooks, each lesson is followed by a set of homework problems in one of two ways -- blocked practice and mixed practice. Additionally, most mathematics textbooks rely on a common learning strategy called overlearning, that is, mastering a skill and continuing to practice this same skill. This study investigated the effects…

The primary purpose of this study was to compare academic variables from students participating in mixed teaching methods/course revitalization biology courses to those in traditional courses at two community colleges in Tennessee. A two-group comparison design using archived data was used, which evaluated differences in final grades, exam scores,…

Machine learning models were constructed to predict student performance in an introductory mechanics class at a large land-grant university in the United States using data from 2061 students. Students were classified as either being at risk of failing the course (earning a D or F) or not at risk (earning an A, B, or C). The models focused on…