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Free, publicly-accessible full text available August 1, 2025
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In a core mechanical engineering course on numerical methods at the University of South Florida in the fall of 2022, students were presented with discussion questions to serve as metacognitive activities. The course consisted of eight topics, and after each topic, the students were asked a single discussion question. While answering these questions was optional for the students, it served as 2% extra credit for the eight questions of the course. This initiative was initially taken to offset any occasional missed 30 online homework assignments, which accounted for 15% of the grade for the semester. These questions were designed to elicit thoughtful and unique responses from the students. To promote learning from others, students were allowed to see posted responses from other students only after they had submitted theirs. The questions ranged from making a meme to describing a difficult or intuitive concept. Despite the opportunity for extra credit and the unique prompts, the participation rate was only 59% of the possible submissions, and no clear trend was observed between the participation of high- or low-performing students.more » « less
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The metacognitive strategies of planning, monitoring, and evaluating can be promoted through systematic reflection to drive self-directed, lifelong learning. This article reports on a three-year study on systematic written reflection within an undergraduate Fluid Mechanics course to promote planning, monitoring, and evaluation. Students were prompted weekly to reflect on their in-class problem-solving, classroom and exam preparation, performance, behaviors, and learning in a flipped classroom at a large southeastern U.S. university. In addition, they received intentional instruction on how to plan, monitor, and evaluate their problem-solving during class. To enable a comparative assessment, a flipped classroom without these interventions was also implemented as a non-experimental cohort. The cohorts were compared using a final exam, concept inventory, and the Metacognitive Activities Inventory (MCAI). The MCAI indicated a significantly higher positive change (pre- to post-course) in self-regulatory behavior for the experimental cohort ( p = 0.037). The weekly reflections were studied using an inductive content analysis to assess students’ self-regulatory behaviors. They were also used to investigate statistical associations between reflection content and course outcomes. This revealed that academic self-discipline via planning, monitoring one's work, or being careful and diligent may be as aligned with course performance in STEM as is practice with the problem-solving itself. The effects for the final exam in the experimental cohort were positive overall as well as statistically or practically significant for various demographic strata. These results provided evidence for the potential enhancement of course performance with metacognition support. A positive shift in students’ perspectives regarding the value of the reflection questions was observed throughout the study. Therefore, as an implementation guide for other educators, the reflection questions and any changes made in posing them to students are discussed chronologically. Overall, the study points to the desirability of providing metacognition support in a STEM course.
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When students repeatedly reflect, it can enhance their metacognitive abilities, including self-regulatory skills of planning, monitoring, and evaluating. In a fluid mechanics course for undergraduates at a large southeastern U.S. university, in-class problem solving in a flipped classroom was coupled with intentional metacognitive skills instruction and repeated reflection to enhance metacognition. The weekly reflective responses were coded by two analysts to identify the recurring themes and uncover evidence of the development and/or reinforcement of self-regulating behaviors for academic management. To enable a comparison, a flipped classroom without the metacognitive instruction and repeated reflection was also implemented (i.e., non-intervention group). The two cohorts completed identical final exams. Based on our preliminary analysis with year one data, a statistically and practically-significant difference between the two cohorts was found with the free-response scores on the final exam in favor of the intervention cohort that had received the metacognitive support ( p < 0.0005; Cohen's d = 0.72). Also, the Metacognitive Activities Inventory (MCAI) indicated a significantly-higher positive change in self-regulatory behavior for the intervention cohort ( p = 0.001; d = 0.50). Focus groups were conducted to gather students’ perspectives on the reflective activity, with differences found by demographic group. In addition, a significantly higher proportion of females (versus males) viewed the reflections in a positive manner ( p = 0.05). Significant associations between themes in the weekly reflections and direct knowledge measures were also uncovered. This included a positive relationship between academic self-management (i.e., diligence and carefulness) and exam performance. Overall, our preliminary results point to a desirable impact of metacognitive instruction and repeated reflection on knowledge outcomes, metacognitive skills, and self-regulatory behaviors.
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In this study, flipped instruction in an undergraduate engineering course in the ‘COVID’ online, remote environment was conducted and compared to onsite flipped instruction (i.e. pre-COVID) to explore potential changes in student perceptions. Student perceptions were gathered via survey instruments and investigated further through instructor interviews. This analysis was done at three universities and made possible by extensive research with the flipped classroom at these three schools as part of a previous NSF-funded study between 2014 and 2016. Results gathered in the online remote setting suggest positive changes in student perceptions of flipped instruction compared to the onsite environment, including the decreased perception of the ‘load’ imposed by the flipped classroom and the ‘effort‘’ required. Some desirable outcomes remained unchanged in the remote setting. The recent and emerging literature has suggested the remote, online environment dictated by the pandemic may be beneficial for flipped teaching and learning. These and other findings from conducting flipped classrooms at three engineering schools in the online environment are presented, including perceptions of the classroom environment (via the College and University Environment Inventory), benefits and drawbacks identified, student motivation levels, and perceived learning.more » « less
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Abstract Adaptive learning platforms are increasingly being used as part of varying instructional modalities. Particularly relevant to this paper, adaptive learning is a critical component of personalized, preclass learning in a flipped classroom. Previously inaccessible, data generated by adaptive learning platforms regarding student engagement with the course content provides an invaluable opportunity to gain a deeper understanding of the learning process and improve upon it. We aim to investigate the relationships between adaptive learning platform interactions and overall student success in the course and identify the variables most influential to student success. We present a comprehensive analysis of our adaptive learning platform data collected in a Numerical Methods course, including aggregate statistics, frequency analysis, and Principal Component Analysis, to determine which variables exhibited the most variability and, therefore, the most information in the data. Subsequently, we used the Partitioning Around Medoids clustering approach to investigate naturally occurring clusters of students and how these clusters relate to overall performance in the course. Our results show that overall performance in the course, as measured by the final course grade, is strongly associated with (1) the behavioral interactions of students with the adaptive platform and (2) their performance on the adaptive learning assessments. We also found distinct student clusters (as defined by success in the course) that exhibited distinctly different behaviors. These findings provide qualitative and quantitative information to identify students needing support and to craft an evidence‐based support strategy for these students.
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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. Focus groups enabled a comparison of student perspectives of using adaptive technology in blended versus flipped classrooms as well as by demographic. Upon combining these outcomes, including a notable Cohen's
d = 0.34 for open‐ended‐response performance, the flipped classroom with adaptive learning may be the best method for this STEM course.