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This paper will provide the first-year results of the impact of implementing the flipped approach in lower level math and aerospace engineering courses. A quasi-experimental between-groups research design was used for assessing the effectiveness of this methodology. The control group consisted of students who were in the same course but in sections with traditional teaching delivery while the intervention group consisted of students who were registered in the sections with the flipped approach. All students were from underrepresented groups. A positive impact on the students’ attitudes and learning strategies was observed as a result of the flipped classroom with active learning. Data pertaining to the effectiveness of the flipped classroom pedagogy is shared in this paper. Analysis of students’ cognitive engagement and their attitudes towards flipped classroom is discussed. The paper also includes best practices, their impact on student performance, and challenges in implementing a flipped classroom pedagogy.
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Innovative Learning Strategies to Engage Students Cognitively
The role of cognitive engagement in promoting deep learning is well established. This deep learning fosters attributes of success such as self-efficacy, motivation and persistence. However, the traditional chalk-and-talk teaching and learning environment is not conducive to engage students cognitively. The biggest impediment to implementing an environment for deep learning such as active-learning is the limited duration of a typical class period most of which is consumed by lecturing. In this paper, best practices and strategies for cognitive engagement of students in the classroom are discussed. Several lower level math and aerospace engineering courses were redesigned and offered during the academic year at a historically black university. The learning strategies in these redesigned courses included the “flipped” pedagogical model which allowed the integration of the active-learning strategy in the classroom. The research study is to determine the impact of these redesigned courses on student academic performance and persistence in STEM courses. The efficacy of the design of the flipped approach was also investigated. A between-group quasi-experimental research design was used for comparing student academic performance in traditional classroom (control group) and redesigned classroom (intervention group). A within-subject, repeated measures design was also used to assess the impact on the students’ self-regulated learning. A validated instrument was used to measure the effect of the redesigned learning environment on the motivational beliefs and self-regulated learning. Data on the academic performance of the students were collected. Analyses of these data indicated a significant impact on student academic performance. A positive change in student motivation and self-regulated learning was observed. Data analysis also validated the design of the intervention. This research is supported by NSF Grant# 1712156.
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- Award ID(s):
- 1712156
- PAR ID:
- 10168216
- Date Published:
- Journal Name:
- 2020 ASEE National Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Deep learning is the result of cognitive engagement with the learning materials. Various strategies have been proposed for promoting cognitive engagement during the learning process. One such strategy is active learning which is an essential element for student engagement to foster deeper learning leading to academic success. However, time limitation of the classroom is a major obstacle in implementing active learning. One solution is the use of the flipped teaching and learning methodology. This paper provides details of strategies to promote engagement and deeper learning in lower level math and aerospace engineering courses at a Historically Black College and University (HBCU). Data on students’ motivation and self-regulation was collected using the validated instrument, Motivated Strategies for Learning Questionnaire (MSLQ). Results of the analysis and best practices impacting students’ academic performance are shared in this paper. The work is supported by NSF Grant# 1712156.more » « less
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