Enhancing the Success of College Algebra Students by Incorporating Adaptive Technologies

Alina Stefanov, Barry J. Griffiths
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Abstract

College students in the United States often enrol in introductory mathematics courses to acquire skills and knowledge that will enable them to solve related problems in their careers and daily activities. However, previous studies have shown limited levels of improvement that perpetuate a lack of proficiency. As a result, the gap in performance between top students and those at the bottom continues to increase. Using modern technology has been suggested as part of the solution to help students resolve their difficulties in mathematics and achieve better learning outcomes. This study assesses the longitudinal effect of redesigning College Algebra classes at a large public university, switching from a modified emporium model to a lab-based adaptive model. The results show that after redesigning the course, the pass rate increased from 68% to consistently being over 80%, while the withdrawal rate fell from 8% to 3%.
结合自适应技术提高大学代数学生的成功
美国的大学生经常参加数学入门课程,以获得技能和知识,使他们能够解决职业生涯和日常活动中的相关问题。然而,先前的研究表明,有限的提高水平,使其长期缺乏熟练程度。结果,优等生和低等生之间的成绩差距继续扩大。有人建议使用现代技术作为解决方案的一部分,帮助学生解决数学困难,取得更好的学习成果。本研究评估了在一所大型公立大学重新设计大学代数课程的纵向效应,从改进的商场模型转换为基于实验室的自适应模型。结果表明,重新设计课程后,通过率从68%上升到80%以上,退课率从8%下降到3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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