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Student performance and retention in STEM majors is a major concern in higher education. Individual attention and coaching are effective at improving the retention of under-performing students, but these tools are too labor-intensive for faculty to apply in large introductory courses. Additionally, many struggling students are limited by non-cognitive factors such as fear of failure, social anxiety, and general overwhelm. There is a need for large-format, scalable instructional tools that both engage students in course material and address non-cognitive factors in an appropriate way. This Work In Progress will present the effects of a remedial intervention, the “reflective knowledge inventory”, at improving student outcomes in Calculus 1. This intervention was developed over several years in sophomore through senior-level engineering classes post-pandemic. In the intervention, students improve their exam score by submitting a “reflective knowledge inventory”. Expert learners know that new skills are best built on existing knowledge, and that big problems should be broken into smaller tasks. Novice learners are more likely to feel overwhelmed and panicked, especially when they know they are underperforming. We attempted to design a remedial assignment that scaffolds students through the process of identifying technical strengths to build on and breaking weaknesses into manageable chunks. Briefly, students create a glossary of terms and concepts from the class and rank them by their level of understanding. Importantly, the assignment also includes reflections on emotions, barriers, and support networks. This work will combine quantitative analysis of student grades with thematic analysis of student submissions to determine the effectiveness of the intervention. 

Electronic connections between active material particles and the conductive carbon binder domain govern high-energy commercial Li-ion batteries' rate capability and lifetime (LIB). This work develops an in situ electrochemical fluorescent microscopy (EFM) technique that maps fluorescence intensity to these local electronic connections. Specifically, rapid redox kinetics of an electrofluorophore translates to reaction distributions limited by the electronic accessibility of battery electrode regions and individual active material particles. This technique can visualize hot spots, dead zones, and isolated particles on the electrode surface. EFM characterization of a series of LiNi_0.33Mn_0.33Co_0.33O₂electrodes across processing parameters finds a significant negative correlation between the number of disconnected active particles and the rate capability. This low-cost technique provides quantitative mesoscale characterization of commercial LIB electrodes with fast throughput (<60 s) to facilitate rapid research and development and provide manufacturing quality control. 

The viscosity and microstructure of Li-ion battery slurries and the performance of the resulting electrodes have been shown to depend on the mixing protocol. This work applies rheology to understand the impact of shear during mixing and polymer molecular weight on slurry microstructure and electrode performance. Mixing protocols of different shear intensity are applied to slurries of LiNi0.33Mn0.33Co0.33O2 (NMC), carbon black (CB), and polyvinyldiene difluoride (PVDF) in N-methyl-2-pyrrolidinone (NMP), using both high-molecular-weight (HMW) and low-molecular-weight (LMW) PVDF. Slurries of both polymers are observed to form colloidal gels under high-shear mixing, even though unfavorable interactions between high molecular weight PVDF and CB should prevent this microstructure from forming. Theoretical analysis and experimental results show that increasing shear rate during the polymer and particle mixing steps causes polymer scission to decrease the polymer molecular weight and allow colloidal gelation. In general, electrodes made from high molecular weight PVDF generally show increased rate capability. However, high shear rates lead to increased cell variability, possibly due to the heterogeneities introduced by polymer scission. 

The 2021 return to face-to-face teaching and proctored exams revealed significant gaps in student learning during remote instruction. The challenge of supporting underperforming students is not expected to abate in the next 5-10 years as COVID-19-related learning losses compound structural inequalities in K-12 education. More recently, anecdotal evidence across courses shows declines in classroom attendance and student engagement. Lack of engagement indicates emotional barriers rather than intellectual deficiencies, and its growth coincides with the ongoing mental health epidemic. Regardless of the underlying reasons, professors are now faced with the unappealing choice of awarding failing grades to an uncomfortably large fraction of classes or awarding passing grades to students who do not seem prepared for the workforce or adult life in general. Faculty training, if it exists, addresses neither the scale of this situation nor the emotional/identity aspects of the problem. There is an urgent need for pedagogical remediation tools that can be applied without additional TA or staff resources, without training in psychiatry, and with only five or eight weeks remaining in the semester. This work presents two work-in-progress interventions for engineering faculty who face the challenges described above. In the first intervention, students can improve their exam score by submitting videos of reworked exams. The requirement of voiceover forces students to understand the thought process behind problems, even if they have copied the answers from a friend. Incorporating peer review into the assignment reduces the workload for instructor grading. This intervention has been successfully implemented in sophomore- and senior-level courses with positive feedback from both faculty and students. In the second intervention, students who fail the midterm are offered an automatic passing exam grade (typically 51%) in exchange for submitting a knowledge inventory and remediation plan. Students create a glossary of terms and concepts from the class and rank them by their level of understanding. Recent iterations of the remediation plan also include reflections on emotions and support networks. In February 2023, the project team will scale the interventions to freshman-level Introductory Programming, which has 400 students and the highest fail/withdrawal rate in the college. The large sample size will enable more robust statistics to correlate exam scores, intervention rubric items, and surveys on assignment effectiveness. Piloting interventions in a variety of environments and classes will establish best pedagogical practices that minimize instructors’ workload and decision fatigue. The ultimate goal of this project is to benefit students and faculty through well-defined and systematic interventions across the curriculum. 

A new electroanalytical design based on asymmetric interdigitated arrays (IDA) is presented and the effects of asymmetry on the device performance are characterized electrochemically. Varying the collector and generator band widths independently of each other tunes the collection efficiency and redox cycling-induced feedback. These arrays are able to provide low feedback (<10%) while maintaining moderate collection efficiency (25%–40%). Behavior is evaluated experimentally and using a numerical model. The application of the device to detect soluble electrolyte degradation products in nonaqueous lithium-ion and sodium-ion battery electrolytes is demonstrated.