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 lessonsmore »
This content will become publicly available on June 26, 2024
Development, Implementation, Refining and Revising of Adaptive Platform Lessons for an Engineering Course
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 more »
- Award ID(s):
- 2013271
- Publication Date:
- NSF-PAR ID:
- 10404648
- Journal Name:
- Proceedings of the 2022 ASEE Annual Conference and Exposition
- Sponsoring Org:
- National Science Foundation
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Abstract Preclass learning, an obstacle in the success of a flipped classroom, is addressed via placing lessons on an online adaptive platform. The lessons combine the power of video lectures, textbook content, simulations, and assessments while using personalized paths for each student. This article describes the development of the adaptive lessons for a course in Numerical Methods, and the interpretation of the analytic data collected via the adaptive lesson platform and student focus groups over a two‐semester period with 146 students. Analytical data includes student metrics, such as the lesson scores and the time spent and lesson metrics, such as the percentage of students who completed the lesson and the percentage of possible adaptive paths used by students. The focus groups were conducted for two different demographic groups—students who are “white males” (comprise the majority of students in public engineering schools in the USA) and “other than white males”—to compare their perspectives on adaptive learning. Students in the focus group of the “other than white male” pupils demonstrated more favorable and positive perspectives towards the adaptive learning compared with the “white males”, although both groups identified benefits with the adaptive platform. Final examination scores were found to be correlated withmore »
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Abstract As use of adaptive learning technology in STEM courses gains traction, studies evaluating its impacts are important to undertake. Adaptive e‐learning platforms provide personalized, flexible learning via monitoring of student progress and performance and subsequent provision of an individualized learning path containing various resources. In this study, adaptive technology was utilized in blended and flipped versions of a numerical methods course. A particular challenge with flipped instruction is preclass preparation, in which videos with the same instruction for all students are often assigned. Therefore, to diversify preclass learning, the instructor developed adaptive lessons via an NSF grant and rigorously assessed outcomes in this flipped class with adaptive learning. In addition, to fully evaluate the lessons and respond to calls from the literature, the lessons were implemented and evaluated in a blended version of the course, which was lecture‐based with available online resources. Data from previous semesters of flipped and blended instruction (without adaptive learning were available), enabling a comparison of four instructional methods. The comparisons consisted of direct assessment (i.e., exam questions) and affective assessment via a survey (i.e., perceptions of the classroom environment). An analysis was performed for students collectively and for underrepresented minority students in engineering. Focusmore »
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The emphasis on conceptual learning and the development of adaptive instructional design are both emerging areas in science and engineering education. Instructors are writing their own conceptual questions to promote active learning during class and utilizing pools of these questions in assessments. For adaptive assessment strategies, these questions need to be rated based on difficulty level (DL). Historically DL has been determined from the performance of a suitable number of students. The research study reported here investigates whether instructors can save time by predicting DL of newly made conceptual questions without the need for student data. In this paper, we report on the development of one component in an adaptive learning module for materials science – specifically on the topic of crystallography. The summative assessment element consists of five DL scales and 15 conceptual questions This adaptive assessment directs students based on their previous performances and the DL of the questions. Our five expert participants are faculty members who have taught the introductory Materials Science course multiple times. They provided predictions for how many students would answer each question correctly during a two-step process. First, predictions were made individually without an answer key. Second, experts had the opportunity to revisemore »
