Since the 2014 high-profile meta-analysis of undergraduate STEM courses, active learning has become a standard in higher education pedagogy. One way to provide active learning is through the flipped classroom. However, finding suitable pre-class learning activities to improve student preparation and the subsequent classroom environment, including student engagement, can present a challenge in the flipped modality. To address this challenge, adaptive learning lessons were developed for pre-class learning for a course in Numerical Methods. The lessons would then be used as part of a study to determine their cognitive and affective impacts. Before the study could be started, it involved constructing well-thought-out adaptive lessons. This paper discusses developing, refining, and revising the adaptive learning platform (ALP) lessons for pre-class learning in a Numerical Methods flipped course.
In a prior pilot study at a large public southeastern university, the first author had developed ALP lessons for the pre-class learning for four (Nonlinear Equations, Matrix Algebra, Regression, Integration) of the eight topics covered in a Numerical Methods course. In the current follow-on study, the first author and two other instructors who teach Numerical Methods, one from a large southwestern urban university and another from an HBCU, collaborated on developing the adaptive lessons for the whole course.
The work began in Fall 2020 by enumerating the various chapters and breaking each one into individual lessons. Each lesson would include five sections (introduction, learning objectives, video lectures, textbook content, assessment). The three instructors met semi-monthly to discuss the content that would form each lesson. The main discussion of the meetings centered on what a student would be expected to learn before coming to class, choosing appropriate content, agreeing on prerequisites, and choosing and making new assessment questions. Lessons were then created by the first author and his student team using a commercially available platform called RealizeIT. The content was tested by learning assistants and instructors. It is important to note that significant, if not all, parts of the content, such as videos and textbook material, were available through previously done work. The new adaptive lessons and the revised existing ones were completed in December 2020.
The adaptive lessons were tested for implementation in Spring 2021 at the first author's university and made 15% of the students' grade calculation. Questions asked by students during office hours, on the LMS discussion board, and via emails while doing the lessons were used to update content, clarify questions, and revise hints offered by the platform. For example, all videos in the ALP lessons were updated to HD quality based on student feedback. In addition, comments from the end-of-semester surveys conducted by an independent assessment analyst were collated to revise the adaptive lessons further. Examples include changing the textbook content format from an embedded PDF file to HTML to improve quality and meet web accessibility standards.
The paper walks the reader through the content of a typical lesson. It also shows the type of data collected by the adaptive learning platform via three examples of student interactions with a single lesson.
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Virtual adaptation of introductory materials engineering: a partially asynchronous approach to engage a large class
With large enrollments (about 200-350) of primarily non-majors, engaging students in the
required introductory materials science and engineering course at our university has been a longstanding challenge. In moving to the virtual format in the fall of 2020, we significantly
adapted several aspects of the course, many of which have continued to the hybrid format in future semesters, with good results. The primary content was provided through asynchronous videos; this format allowed us to break content into digestible pieces. In particular, multiple mini-lectures and example videos were pre-recorded for each week, with a total viewing time per week somewhat less than the typical total class time. To provide real-time, structured interaction, one live virtual class session per week was held, centered on previously submitted student questions. Smaller teaching-assistant-led recitation sections also met live (virtually or in person), during which “clicker” questions were asked through TopHat. Assignments were also updated to take advantage of the virtual format. Multiple small assignments with lower stakes were due throughout the week: a reading/lecture quiz, a survey to submit questions, and a shortened homework assignment. Finally, we changed some content near the end of the course to allow
students to connect the course to their own career aspirations, which we expect can aid in longterm retention. Specifically, students chose among several possible topics to cover in the final weeks, covered via typical pre-recorded lectures and reading, and also guest lectures. They wrote an abstract-length reflection on how they could use what they learned in this course later in their careers. Overall, students remained engaged with the course throughout the semester and provided favorable comments and evaluations of the course, including higher numerical evaluations of the course than in prior semesters.
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- Award ID(s):
- 1943870
- NSF-PAR ID:
- 10403112
- Date Published:
- Journal Name:
- 2022 ASEE Annual Conference & Exposition
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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