Using Adaptive Learning Technology in General Chemistry

Written by
Dr. Anna Ivanova, Adjunct Assistant Professor, Natural Sciences Department, Physical Sciences Unit
& Dr. Anna Manukyan, Assistant Professor, Natural Sciences Department, Physical Sciences Unit

 

Technology has revolutionized education; it impacts student learning by making it more interactive and immersive. Colleges and universities across the nation continuously explore evolving technologies alongside effective methodologies to address a common challenge: incoming students often lack critical prerequisite knowledge and are unprepared for the rigors of entry-level calculus and chemistry courses. With the help of data analytics, adaptive learning technology combines cognitive and learning styles to individualize the learning process of a student.

Recently, several colleges conducted pilot studies on using adaptive learning technology to improve student success in entry level mathematics and chemistry (1-3). Each of the pilots showed positive results. Through their implementation of summer bridge programs using the ALEKS (Assessment and LEarning Knowledge Spaces) adaptive learning system, the campuses saw higher placement and improved student performance in these courses. They also showed that the students who participated generally did as well as other students who initially placed into the course without the foundational summer help.

Motivated by these studies, we introduced ALEKS, a stand-alone digital learning platform in our General Chemistry courses for science and allied health majors (CHE210, CHE220 and CHE110). This tool identifies critical prerequisite knowledge including foundational scientific concepts and chemistry-related mathematical skills before presenting homework material. This is typically done through a series of questions that assesses the skills and/or knowledge the student has (Initial Knowledge Check). The results of the initial knowledge check are accumulated and represented in an ALEKS Pie that is broken down into sections of knowledge within a specific domain or subject. As students are progressing through the objectives set towards the learning outcomes for the course, the ALEKS system periodically re-assesses students’ mastery of topics. If a student can no longer demonstrate mastery of a topic, the system will ask them to remediate in that area to regain mastery.  The piece of pie associated with this topic will disappear from the use their long-term memory to further reinforce the material presented in the course.

Overall, our preliminary analysis of survey data shows that students using ALEKS express higher satisfaction and higher engagement with the material, and in some cases they demonstrate a visible progress in performance in the course. We intend to continue using ALEKS in General Chemistry courses and in the process of adopting it in more sections. We plan to better study and analyze the effect of ALEKS implementation in General Chemistry courses in a context of a faculty collaborative project.

 

References

  1. Richards-Babb, M; Curtis, R; Ratcliff, B; Roy, A and Mikalik, T (2018). General Chemistry Student Attitudes and Success with Use of Online Homework: Traditional-Responsive versus Adaptive-Responsive. Journal of Chemical Education 295 (5), 691-699
  2. Mojarad, S; Essa, A and Baker, R. S. (2018). Studying Adaptive Learning Efficacy using Propensity Score Matching. Companion Proceedings 8th International Conference on Learning Analytics & Knowledge (LAK18)
  3. Fang, Y; Ren, Z; Hu, X and Graesser, A. (2019). A Meta-Analysis of the Effectiveness of ALEKS on Learning. Educational Psychology. 39 (10), 1278-1292
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