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1. Advances in step-based tutoring for linear circuit analysis and comprehensive evaluation

   Skromme, B. J. ; Gupta, R. ; Nasim, T. ; Redshaw, C. J. ; Miller, B. ; Andre, P. ; Erives, H. ; Bailey, D. ; Wilkins, G. ; Bansal, S. K. ; et al ( August 2022 , 2022 ASEE Annual Conference & Exposition, Minneapolis, MN)

   Step-based tutoring consists in breaking down complicated problem-solving procedures into individual steps whose inputs can be immediately evaluated to promote effective student learning. Here, recent progress on the extension of a step-based tutoring for linear circuit analysis to cover new topics requiring complex, multi-step solution procedures is described. These topics include first and second-order transient problems solved using classical differential equation approaches. Students use an interactive circuit editor to modify the circuit appropriately for each step of the analysis, followed by writing and solving equations using methods of their choice as appropriate. Initial work on Laplace transform-based circuit analysis is also discussed. Detailed feedback is supplied at each step along with fully worked examples, supporting introductory multiple-choice tutorials and YouTube videos, and a full record of the student's work is created in a PDF document for later study and review. Further, results of a comprehensive independent evaluation involving both quantitative and qualitative analysis and users across four participating institutions are discussed. Overall, students had very favorable experiences using the step-based system across Fall 2020 and Spring 2021. At least 48% of students in the Fall 2020 semester and 60% of students in the Spring 2021 semester agreed or strongly agreed with all survey questions about positive features of the system. Those who had used the step-based system and the commercial MasteringEngineering system preferred the former by 69% to 12% margins in surveys. Instructors were further surveyed and 86% would recommend the system to others. 

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2. Interactive Editing of Circuits in a Step-Based Tutoring System

   Skromme, B ; Redshaw, C. ; Gupta, A ; Gupta, S ; Andrei, P ; Erives, H ; Bailey, A ; Thompson, W ; Bansal, S. ( July 2020 , American Society for Engineering Education Annual Conference)

   Step-based tutoring systems are known to be more effective than traditional answer-based systems. They however require that each step in a student’s work be accepted and evaluated automatically to provide effective feedback. In the domain of linear circuit analysis, it is frequently necessary to allow students to draw or edit circuits on their screen to simplify or otherwise transform them. Here, the interface developed to accept such input and provide immediate feedback in the Circuit Tutor system is described, along with systematic assessment data. Advanced simplification methods such as removing circuit sections that are removably hinged, voltage-splittable, or current-splittable are taught to students in an interactive tutorial and then supported in the circuit editor itself. To address the learning curve associated with such an interface, ~70 video tutorials were created to demonstrate exactly how to work the randomly generated problems at each level of each of the tutorials in the system. A complete written record or “transcript” of student’s work in the system is being made available, showing both incorrect and correct steps. Introductory interactive (multiple choice) tutorials are now included on most topics. Assessment of exercises using the interactive editor was carried out by professional evaluators for several institutions, including three that heavily serve underrepresented minorities. Both quantitative and qualitative methods were used, including focus groups, surveys, and interviews. Controlled, randomized, blind evaluations were carried out in three different course sections in Spring and Fall 2019 to evaluate three tutorials using the interactive editor, comparing use of Circuit Tutor to both a commercial answer-based system and to conventional textbook-based paper homework. In Fall 2019, students rated the software a mean of 4.14/5 for being helpful to learn the material vs. 3.05/5 for paper homework (HW), p < 0.001 and effect size d = 1.11σ. On relevant exam questions that semester, students scored significantly (p = 0.014) higher with an effect size of d = 0.64σ when using Circuit Tutor compared to paper HW in one class section, with no significant difference in the other section. 

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3. Development, Implementation, Refining and Revising of Adaptive Platform Lessons for an Engineering Course

   Kaw, A. ; Yalcin, A. ; Gomes, R. ; Serrano, L. ; Scott, A. ; Lou, Y. ; Clark, R. ( July 2022 , Proceedings of ASEE Annual Conference and Exposition)

   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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4. Development, Implementation, Refining and Revising of Adaptive Platform Lessons for an Engineering Course

   Kaw, A. ( June 2023 , Proceedings of the 2022 ASEE Annual Conference and Exposition)

   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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5. Step-Based Tutoring Software for Complex Procedures in Circuit Analysis

   Skromme, B. J. ; Bansal, S. K. ; Barnard, W. M. ; O’Donnell, M. A. ( January 2019 , Proceedings - Frontiers in Education Conference)

   Step-based tutoring systems, in which each step of a student’s work is accepted by a computer using special interfaces and provided immediate feedback, are known to be more effective in promoting learning than traditional and more common answer-based tutoring systems, in which only the final (usually numerical) answer is evaluated. Prior work showed that this approach can be highly effective in the domain of linear circuit analysis in teaching topics involving relatively simple solution procedures. Here, we demonstrate a novel application of this approach to more cognitively complex, multi-step procedures used to analyze linear circuits using the superposition and source transformation methods. Both methods require that students interactively edit a circuit diagram repeatedly, interspersed with the writing of relevant equations. Scores on post-tests and student opinions are compared using a blind classroom-based experiment where students are randomly assigned to use either the new system or a commercially published answer-based tutoring system on these topics. Post-test scores are not statistically significantly different but students prefer the step-based system by a margin of 84 to 11% for superposition and 68 to 23% for source transformations. 

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