Improving Mathematics Placement Procedure To Better Evaluate The Readiness Of Incoming College Students For Precalculus Courses

Improving Mathematics Placement Procedure to Better Evaluate the Readiness of Incoming College Students for Precalculus Courses

An extensive literature review of college freshman math placement procedures indicated that non-academic factors may have an important role in college student academic success. Therefore, this thesis investigated 1) the effectiveness of using SAT/prerequisite scores as placement qualifications into college mathematics courses, 2) the effect of adding a placement component that addresses a variety of non-academic factors, giving placement recommendations (ETS SuccessNavigator) and 3) the effect of an intervention designed to improve the non-academic factors. 1) Ho: SAT/prerequisite and final grade in the course have no correlation. Ha: SAT/prerequisite and final grade have some correlation. 2) Ho: mean final grade for recommended students is less than or equal to non-recommended students. Ha: mean scores for recommended students is greater than non-recommended students. 3) H o: the proposed intervention has no effect on the non-academic factors. Ha: the proposed intervention improves the non-academic factors. A letter was sent out to all pre-calculus students in participating classes asking for their participation. Participants took the SuccessNavigator as a pre/post assessment. Participants were randomly assigned to two groups, where they received either social support only, or an additional mindset/social support intervention. Of 200 students, 29 volunteered to participate. SAT/prerequisite effects on final grades were analyzed by correlation. SuccessNavigator effects on final grades were analyzed by T-test. The effect of the intervention on students' non-academic factors was analyzed by Chi-Square. The results of the data analysis suggest SAT and prerequisite scores lack the predictive accuracy to be used as placement qualifications into college mathematics courses, non-academic factors can predict college student academic success, and a mindset/social support intervention has the potential to affect student non-academic factors for larger sample sizes if effect size holds.

Personalized Learning

This self-contained monograph reports the recent approaches, methods and practices of technology-enabled personalized learning. It serves to provide some useful references for researchers and practitioners in the field in conceptualizing and deploying personalized learning. Personalized learning emphasizes student-centred learning that addresses individual learning strengths, needs, skills, and interests, and allows flexibility in the learning mode, process, time and space, where students can take ownership of their learning. It has been practiced in educational institutions at both K-12 and higher education level and, as evident from several successful cases, is an enabler of personalized learning. Educational technology incorporated with other forms of innovative pedagogical practices, such as blended learning, makes personalized learning a reality to achieve its aims effectively and efficiently. This book begins with a critical review on the features and trends of personalized learning. This is followed by a number of case studies on personalized learning practices with promising results. The latest research findings on the approaches, methods and strategies on design and implementation of personalized learning are then reported. Lastly, the prospects of personalized learning are discussed. All these provide some useful references for researchers and practitioners in the field in conceptualizing and deploying personalized learning. Personalized Learning will be a key resource for academics, researchers, and advanced students of education, instructional design and technology, educational research, educational technology, research methods, STEM Education, information and communications technology, and curriculum and instruction. The chapters included in this book were originally published as a special issue of Interactive Learning Environments.

Proceedings of the Section on Statistical Education