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Abstract Details

Activity Number: 344
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract #324012
Title: Research Findings on Innovative Teaching Methods in Statistics Classes Using ALEKS
Author(s): Cheng Li* and Xiaohui Wang
Companies: and University of Texas Rio Grande Valley
Keywords: Quantitative Research ; Assessment ; Student Learning Behaviors ; ALEKS ; Statistics Education
Abstract:

In a Hispanic Serving Institution, statistics education in introductory statistics courses were experimented on some innovative teaching methods and adoption of a web-based learning platform, ALEKS for several years. ALEKS is an artificially intelligent assessment and learning system that provides the advantages of one-on-one instruction and assessment, 24/7, from any web-based computer. With the rich records kept in ALEKS, we were able to assess students' knowledge and learning behaviors. We examined students' prior knowledge and their knowledge gain (post knowledge minus prior knowledge) in statistics courses when some innovative teaching methods were deployed. In addition, students' learning behaviors, including total study hours in ALEKS, study habits, and independent learning behaviors, were studied using quantitative research methods. Findings on how students' prior knowledge and learning behaviors in ALEKS jointly predict students' knowledge gain and academic performance, as well as how students' demographics and study statuses affect those relationships, will be reported.


Authors who are presenting talks have a * after their name.

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