In a study on systematic reflection in a flipped fluid mechanics course to drive metacognition, engineering undergraduates were asked to reflect on the impact of the classroom surroundings on their learning. The reflection question described surroundings as the "conditions and objects"that surround you. Based on an emergent content analysis, peers were mentioned as positive classroom "surroundings"in 46% of the reflections in the fall 2021 and fall 2022 semesters upon return to campus after the COVID-19 pandemic. We had expected reflections related to physical classroom surroundings, such as layout, size, furniture, temperature, or infrastructure. Although students identified the classroom's physical features as "surroundings"with both positive and negative influences, they more frequently identified peers, the instructor, and/or in-person instruction as their positive "surroundings."To situate and understand this unexpected result, we applied the Community of Inquiry (CoI) theoretical framework. This framework has been applied in multiple contexts with its three interdependent presences that drive learning-cognitive, social, and teaching. Interestingly, when students identified their CoI as part of their positive "surroundings,"they less-frequently mentioned non-supportive physical classroom features. Our results suggest that an interactive classroom with notable social presence can have a positive impact on perceptions of the classroom "surroundings"that influence learning. Students' identification of the CoI with their classroom surroundings suggests the importance of community in higher education, particularly during times of disturbance to educational practices.

This article explores the use of adaptive learning platform (ALP) data to conduct early identification and provide support to students who have a low-performance outcome (C or lower) in a numerical methods engineering course. The data from assigned ALP lessons for two semesters was used to create decision-tree models to identify students who would benefit from advising and tutoring support. In the following two semesters, low-performing students were identified early in the semester and provided with support, and their performance was compared to their peers. The best-performing prediction model achieved an accuracy of 85% in predicting low-performing students in the third week of the course. The support included weekly one-on-one tutoring and advising sessions. Although only 23% of the identified students accepted support, they scored one-third a letter grade better than those who did not. Additionally, students who received support were invited to participate in a focus group at the end of the semester. Positive outcomes reported included improved understanding of course material, higher academic performance, advice on learning strategies, and guidance on non-course-related topics like internships and employment. Although most students valued receiving personalized invitations, a few felt singled out as low-performing. Students acknowledged the significance of individualized support, gave advice on how to word the invitation emails, and made helpful suggestions for improving help sessions, particularly in terms of personalization and recognizing their heavy academic workload.

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.

Adaptive learning supports online instruction by offering feedback to students using machine learning. In a funded study, adaptive learning was used in a flipped STEM course at three universities for pre-class preparation. We conducted a comparative analysis with and without adaptive learning. The assessments were a final exam and concept inventory (stratified demographically) and affective questions from the College and University Classroom Environment Inventory, focus groups, and evaluation survey. This study found classroom environment enhancement with adaptive learning, with Task Orientation and Satisfaction exhibiting significant changes at two universities. We found enhanced perspectives with adaptive learning, including increased preference for flipped instruction and reduced perceptions of responsibility imposed. The direct assessment results differed by institution and exam type but showed adaptive learning may be helpful for URM, Pell Grant, and community college transfers and for open-ended problem solving. This research supports adaptive learning for flipped STEM classroom preparation and learning.

Multiple-chance testing was used to conduct standards -based testing in a blended-format numerical methods course for engineering undergraduates. The process involved giving multiple chances on tests and post-class learning management system quizzes. The effectiveness of standards -based testing was evaluated through various forms of assessment, including an analysis of cognitive and affective outcomes, and compared to a blended classroom that did not use standards-based testing. Based on a two-part final exam, a concept inventory, final course grades, a classroom environment inventory, and focus groups, the results showed that standards -based testing had overall positive effects. Standards-based testing was associated with a more significant percentage of students (15% vs. 3%) earning a high final exam score, a higher proportion of A grades (36% vs. 27%), and a better classroom environment on dimensions of involvement, cohesiveness, and satisfaction. Focus group discussions revealed that students appreciated the benefits of enhanced learning, second chances, and reduced stress with standards-based testing. The study also included an analysis of the impact of standards-based testing on underrepresented minorities, Pell Grant recipients (low socioeconomic groups), and low-GPA students, as well as an examination of test-retaking behaviors. The methodology and comprehensive results of the study are presented in this paper.

Starting in March 2020, the COVID19 pandemic instantly affected the education of 14 million higher education students in the USA. The switch to remote instruction caught instructors and students off guard – teachers had to change their techniques, approaches, and course content rapidly (called "panicgogy"), and students had to adjust to remote instruction in a hurry. Hoping that the pandemic would not last too long, most had expected to return to the regular class format at most by the Fall semester. That expectation was quickly squashed as the summer semester progressed. If one were teaching a face-to-face classroom in a flipped modality, it would be even more challenging to teach a flipped class in an online environment. In this paper, we present how the instructor overhauled a face-to-face flipped class in Numerical Methods to an online environment. This involved 1) rethinking the learning design of the course content via the learning management system, 2) using Microsoft forms as personal response systems, and YouTube for video lectures, 3) not only using break-out rooms for peer-to-peer learning but the "main room" for individual learning as well, 4) exploit the availability of two computers and multiple monitors to deliver and observe the synchronous part of the class, 5) use of discussion boards to streamline the flow of communication that would have otherwise been unwieldy for the instructor, TAs, and students alike, 6) changes made to assessment as it had to be carried online and within a proctoring software environment, 7) changes in the conducting of office hours. The above items will be discussed in the paper, and comparisons of face-to-face and online implementations will be made. The ultimate goal is to present a logic model for a typical lecture-based online flipped STEM classroom for efficient and effective implementation by other instructors.

During two semesters, a numerical methods course for mechanical engineering students at a large US southeastern university used discussion board questions to promote reflection and metacognition. The course covered eight chapters, each with a related discussion question. The students could choose to answer these questions and receive 2% extra credit for the course. This was intended to help the students who missed some of the 30 online homework assignments that comprised 15% of the final course grade. The questions were also meant to encourage the students to think deeply and creatively. The students could see other students’ responses after they posted their own. The questions ranged from making a meme, writing a nursery rhyme, and explaining a complex or easy concept. Only 64% of the total possible responses were submitted by students, and there was a small-to-medium practical but no statistical significance between the levels of participation among the high- or low-performing students. The submissions were analyzed and determined to be at the low level of Bloom’s taxonomy. They identified complex topics to inform future instruction.

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.

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.

Research shows that active learning improves student performance and narrows the achievement gaps for marginalized groups. One of the active learning strategies is the use of flipped learning. However, flipped classrooms pose challenges due to reluctant student preparation in the pre-class learning requirements and general resistance from students to the modality. To address these challenges for a flipped engineering course in Numerical Methods, adaptive learning lessons that present content, assessment, and feedback based on student engagement and performance were created for pre-class learning using a commercial platform. The paper details how the lessons were developed, implemented in pre-class learning, and revised, creating a framework for other engineering educators who may want to duplicate them. An initial study of student behavior during the lessons showed that a low-performing student made many more attempts at the assessments while spending less time on the accompanying learning materials.

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.

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.

Evidence-based testing strategies in the form of multiple cumulative midterm tests preceded by practice tests were recently introduced to a numerical methods course for engineers after the course had been taught for many years in a blended fashion. The instructor introduced these practices in fall 2019, thereby creating his so-called modified blended approach, with the objective of enhancing direct and affective assessment results in his blended classroom implementation. A statistical comparison of results from this modified approach with results from a prior semester of blended instruction was made using final exam and concept inventory scores as well as classroom environment scores based on the CUCEI. This comparison was made for students collectively and for several demographic segments of interest. Based on triangulated results from direct assessments of conceptual understanding and Bloom's taxonomy (lower levels), the modified blended approach with the testing strategies may be the preferred method for this blended classroom for students collectively as well as potentially for Pell grant recipients as a group. The classroom environment and direct assessment results from the higher levels of Bloom's taxonomy did not suggest a preferred instructional method. Support for blended instruction and practice and cumulative testing from the literature is also presented.

Flipped instruction in an undergraduate numerical methods course in the online, remote environment during the COVID-19 pandemic was conducted with and without the use of adaptive-learning lessons for pre-class preparation. This comparison was made to explore potential differences with and without adaptive software relative to exam and concept inventory performance and student perceptions of the classroom environment, learning and motivation, and benefits and drawbacks. Student perceptions were gathered via the College and University Classroom Environment Inventory (CUCEI) and a survey designed to capture feedback specific to flipped instruction. The analysis was made possible by a current NSF grant to study adaptive learning in the flipped classroom at three universities and extensive prior research with the flipped classroom and adaptive learning by the authors. Results gathered in the online flipped classroom with adaptive learning suggested positive changes in the following: classroom environmental perceptions, preference for flipped instruction, perceived responsibility imposed, motivation for independent learning, and perceived learning. Furthermore, based on an open-ended question, there was a significant decrease in the proportion of students who experienced load, burden, or stressors in the online flipped classroom when adaptive learning was available versus not. Multiple-choice exam and concept-inventory results were slightly higher with adaptive lessons (although not significantly so), with the most promising results occurring for Pell grant recipients. The emerging medical education literature has suggested that adaptive learning and flipped instruction will be key to post-pandemic education. The present article begins advocacy for adaptive learning with flipped instruction in engineering education.

A challenge with flipped instruction is the pre-class preparation, where students independently learn fundamental content outside the classroom. For this pre-class learning, instructors typically assign videos with quizzes. However, this approach is the same for all and does not address differential needs. In a prior National Science Foundation (NSF) study with three schools, differences in the outcomes for blended versus flipped instruction in a numerical method course were not statistically significant, and the effect sizes were small. To diversify pre-class preparation and potentially improve outcomes in the flipped classroom, the instructor developed lessons using an adaptive platform via a new NSF grant. The adaptive platform provides personalized, flexible learning with multiple resources, including videos, text, quizzes, and simulations, with different paths depending on a student's progress. Adaptive lessons were implemented during two semesters in a flipped classroom, and the results were compared to (1) flipped instruction without adaptive lessons and (2) blended instruction. The comparisons consisted of direct assessments (i.e. exams) and student evaluations via survey. Analysis was done collectively for students and for several demographic groups. Based on direct and indirect measures, the flipped classroom with adaptive learning may be the preferred method for this and other STEM courses.

Effectiveness of four instructional delivery modalities – 1) Traditional lecture, 2) Webenhanced lecture, 3) Web-based self-study, and 4) Combined web-based self-study & classroom discussion, was investigated for a single instructional unit (Nonlinear Equations) over separate administrations of an undergraduate course in Numerical Methods. Two assessment instruments – 1) student performance on a multiple-choice examination, and 2) a student satisfaction survey were used to gather relevant data to compare the delivery modalities. Statistical analysis of the assessment data indicates that the second modality where web-based modules for instruction were used in conjunction with a face-to-face lecture delivery mode resulted in higher levels of student performance and satisfaction. Background and Rationale Web-based modules have been developed for a junior-level Numerical Methods course delivered in the College of Engineering at University of South Florida, Tampa. The features of the web-based modules are addressed indirectly since the complete details are readily available in Ref 1, 2 . Stating in brief, the unique features of the web-based modules are that they are both holistic and customized. Holistically, the web-based modules review essential course background information; present numerical methods through several options textbook notes, lecture videos, PowerPoint presentations, simulations and assessments; show how course content covered is applied in real life; tell stories to illustrate special topics and pitfalls; and give historical perspectives to the material 1,2 . Faculty and students are able to choose a customized view based on their preferred computational system Maple 3 , Mathcad 4 , Mathematica 5 , Matlab 6 , and choice of engineering major Chemical, Civil, Computer, Electrical, General, Industrial, and Mechanical. Figure 1: Home page of the Holistic Numerical Methods Institute Committed to Bringing Customized Numerical Methods Holistically to Undergraduates. The focus of this research is to compare four different modes of instructional delivery, namely P ge 11242.2 1) Traditional lecture, 2) Web-enhanced lecture, 3) Web-based self-study, and 4) Web-based self-study/discussion The present study is a follow-up of findings reported in a previous paper 7 where we addressed only the first two modalities. Since the previous study was completed, the course has been delivered twice more, once with a web-based self-study and another with combined webbased self-study followed by a classroom discussion. In recent years, there has been a substantial amount of research exploring how to enhance student learning across disciplines, including science, mathematics, engineering, and technology (SMET) courses. Research in this area spans academic disciplines and professional preparation, from medicine 8 to education 9 and computing to business 10 . Furthermore, the research base is exploring how e-learning, as internet-based education is often referred to, has different benefits based on characteristics of the individual student. The British Journal of International Technology devoted an entire edition to this issue alone 11 addressing, among other things, the need to be cognizant that distance learning has a unique ability to provide students with different learning modalities with varied resources and strategies. Techniques and tools to be used to enhance learning using the web include effective and adaptive navigation as well as addressing multiple and diverse needs and interests of the student 12 . The text, How People Learn 13 provides a foundation for many of the issues facing current educators who are encountering an increasingly diverse and multi-faceted student population. This literature was foundational to the exploration of various modalities of course delivery considered in this study. According to How People Learn, experts (in this case, faculty) “often forget what is easy and what is difficult for students 13, p. 32 .” Relative to this issue, the modules and instructional materials developed through this study offer both students and faculty a comprehensive instructional package for simplifying and enhancing the teaching of numerical methods across the engineering curriculum. Further, research has demonstrated that it is beneficial to provide “instruction that enables students to see models of how experts organize and solve problems” and that “the level of complexity of the models must be tailored to the learners’ current levels of knowledge and skills 13, p. 37 .” The design and format of the web-based modules helps students see how experts apply fundamental numerical methods to solve real world engineering problems both within and across different engineering disciplines. And finally, citing again from this same synthesis of research findings, we know that “A major goal of schooling is to prepare students for flexible adaptation to new problems and settings 13, p. 65 ” and that “knowledge that is taught in only a single context is less likely to support flexible knowledge transfer than is knowledge that is taught in multiple contexts 13, p. 66 .” Our effort was to provide instruction opportunity to suit different learning styles 14 . By enabling students to select both a preferred computational system as well as to select one or more illustrative examples drawn from seven popular engineering majors within each topic area, these Page 11242.3 interactive instructional modules maximize the likelihood of lasting and flexible learning transfer of essential numerical methods course content. Implementation & Assessment Instruments The previous study 7 compared the first two modalities 1) Traditional lecture, and 2) Webenhanced lecture for the two topics of Nonlinear Equations and Interpolation. In this paper, the focus is narrowed to the topic of Nonlinear Equation, but the scope of data is broadened by looking at four modes of delivering the content. The four modalities were implemented in four separate semesters Summer 2002, Summer 2003, Summer 2004 and Spring 2005 1 semesters, respectively. In Summer 2002 semester, students in the Numerical Methods course were instructed on Nonlinear Equations using the traditional, face-to-face lecture method without the use of the web-based modules, hereafter referred to as the Traditional Lecture mode of delivery. We used a popular engineering numerical methods textbook 15 for reading assignments and problem sets. In Summer 2003 semester, students were instructed on the same topic of Nonlinear Equations using both lecture and the web-based resources that were developed for the course, hereafter referred to as the Web Enhanced Lecture. Before discussing numerical methods for a mathematical procedure, we conducted an in-class and informal diagnostic test on the background information via several multiple-choice questions. This allowed us to review specific material that most students struggle with. We used PowerPoint presentations to present the topics. These presentations were continually supplemented with discussions based on spontaneous instructor and student questions. Several times during the presentation, students were also paired in class to work out an iteration or two for a numerical problem. We also met during the weekly computer laboratory session where each student had access to a computer. Simulations for various numerical methods were conducted. Reading assignments were based on textbook notes written by the first author, and problem sets included questions based on Bloom’s taxonomy 16 . In Summer 2004 semester, students received instruction through a distance format without a classroom lecture component, hereafter called the Web-Based Self Study mode. Same resources were available to students as they were in Summer 2003. In addition, lecture videos that were video recorded in a studio were available online. Since the students were learning the material themselves, regular class periods and the weekly lab session that were devoted to the topic of Nonlinear Equations as in Summer 2003 were cancelled. At the end of the week, as part of their graded homework assignment, students were asked to submit answers to 18 short questions (6 on each of the 3 subtopics of Background, Bisection Method, and Newton-Raphson Method) that were based on six levels of Bloom’s taxonomy. The reading assignments and problem sets were the same as in Summer 2003. 1 We were planning to implement the fourth modality in Summer 2005. However, due to certain circumstances, it was co-taught by two instructors and hence assessments were not conducted like in previous semesters. The fourth modality will be implemented again in Summer 2006. P ge 11242.4 In Spring 2005 semester, students used the same self-study methods as those in Summer 2004 but were required to meet in the weekly lab session to discuss the lesson. This mode hereafter is called Web-based Self Study/Class Discussion. Although attending the weekly lab session was mandatory, they were not required to ask questions. Before the weekly lab session, as part of their graded homework assignment, students were asked to submit answers to 9 short questions (3 on each of the 3 subtopics) based on first three levels of Bloom’s taxonomy. After the weekly lab session, they were asked to submit answers to 9 more short questions (3 on each of the 3 subtopics) based on last three levels of Bloom’s taxonomy. The reading assignments and problem sets were the same as in Summer 2003. To measure the student performance, four 2 questions were asked in the Nonlinear Equations portion of the final examination. Two of the four questions were selected at the lower levels of Bloom’s taxonomy, while the other two were chosen from the upper levels of Bloom’s taxonomy. Student performance on these four questions was examined as a function of the four course delivery modes. To measure student satisfaction, a survey that gathered information on students’

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.

She conducts research on education projects that focus on active learning

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 groupsstudents who are white males (comprise the majority of students in public engineering schools in the USA) and other than white malesto 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 with the raw score of the adaptive lessons.