Faculty Spotlight – Rachid Ait Maalem Lahcen

In Spring 2016, I had the opportunity to lead the redesign of college algebra (MAC 1105C), a General Education Program course, and soon after intermediate algebra (MAT 1033C). I implemented a version of Personalized Adaptive Learning (PAL) that depends on the use of an adaptive learning system, Learning Management System, and Personalized Student Instruction (PSI). The use of adaptive courseware, ALEKS, is linked with reducing the cost of education to the student, and the PSI has been proven to be effective in teaching college courses in a variety of disciplines.  

The students meet for their class in a computer lab where a team of graduate teaching assistants (GTAs), undergraduate peers or learning assistants (LAs) and the instructor is available to support their personal learning needs. The computer lab is divided into different rooms and a lecture is presented in one or two rooms while other rooms are used for on-demand instruction or help. Students chose to attend a lecture room or a non-lecture room during a class meeting. The lectures are short and targeted toward skills or concepts that are identified to be too difficult, based on analytics that show a good number of students couldn’t master them. Learning analytics are used to intervene or provide feedback to the students, and performance milestones are specified in the syllabus to promote different pacing. Students can even complete multiple levels in one semester (e.g., intermediate algebra, college algebra, trigonometry, and/or precalculus algebra). 

Describe the impact PAL has had on your teaching and/or students’ learning

In general, PAL significantly improved these courses’ delivery. It allowed me to shift from linear instruction to a prescriptive, individualized instruction that relies on data analytics from an adaptive learning system—an inverted model that helps students prepare outside the classroom and collaborate with colleagues and teaching assistants in-session. Both GTAs and LAs play an essential aspect of human relation and connection, and based on students’ feedback, they enjoy working on math in a personalized way while a team of GTAs, LAs, and instructor are nearby and available to help.

Related Resources 

• TOPR Entry: Adopting adaptive courseware in first year online math course to support STEM retention
• Cavanagh, T., Chen, B., Lahcen, R. A. M., & Paradiso, J. (2020). Constructing a Design Framework and Pedagogical Approach for Adaptive Learning in Higher Education: A Practitioner’s Perspective. The International Review of Research in Open and Distributed Learning, 21(1), 173-197. https://doi.org/10.19173/irrodl.v21i1.4557