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This Research Work-In-Progress reports the implementation of an Object Assembly Test for sketching skills in an undergraduate mechanical engineering graphics course. Sketching is essential for generating and refining ideas, and for communication among team members. Design thinking is supported through sketching as a means of translating between internal and external representations, and creating shared representations of collaborative thinking. While many spatial tests exist in engineering education, these tests have not directly used sketching or tested sketching skill. The Object Assembly Test is used to evaluate sketching skills on 3-dimensional mental imagery and mental rotation tasks in 1- and 2-point perspective. We describe revisions to the Object Assembly Test skills and grading rubric since its pilot test, and implement the test in an undergraduate mechanical engineering course for further validation. We summarize inter-rater reliability for each sketching exercise and for each grading metric for a sample of sketches, with discussion of score use and interpretation. 

With the advancements of ultra-high-precision micro-optics fabrication technologies, it is now possible to fabricate integral field units (IFUs) with slicer mirror width of 30 m or less. This paper describes a 36-um machined image slicer IFU (MISI-36) for the Diffraction-Limited near-IR Spectropolarimeter (DL-NIRSP) of the Daniel K. Inouye Solar Telescope (DKIST). MISI-36 has a unique 2-section image slicer design, and is consists of a monolithic image slicer block with 112 micro slicer mirrors, a parabolic collimator, a monolithic flat mirror array consists of 112 fold mirrors, and a monolithic spherical mirror array consists of 112 spherical mirrors. We have successfully fabricated a prototype device using Canon Inc.’s diamond-cutting CNC, and conducted a preliminary performance evaluation using an experimental bench-top spectrograph similar to the spectrograph of DL-NIRSP. We will present the optical design and optical performances of the MISI-36 prototype. 

Engineering design involves intensive visual-spatial reasoning, and engineers depend upon external representation to develop concepts during idea generation. Previous research has not explored how our visual representation skills influence our idea generation effectiveness. A designer’s deficit in sketching skills could create a need for increased focus on the task of visual representation reducing cognitive resources available for the task at hand — generating concept. Further, this effect could be compounded if designers believed that their sketching skill would be evaluated or judged by their peers. This evaluation apprehension could cause additional mental workload distracting from the production of idea generation.

The goal of this study is to investigate and better understand the relationship between designers’ sketching skills and idea generation abilities. In this paper, we present preliminary results of the relationship between independent measures of sketching skill and idea generation ability from an entry-level engineering design and graphics course. During data collection, task instructions were given in two ways to independent groups: one group was instructed upfront that sketching would be evaluated, while the second group was kept blind to the sketch evaluation. In this paper, we also examine the potential priming effects of sketch quality evaluation apprehension on idea generation productivity. The results show that sketching quality and idea quantity are largely independent, and that the priming effects of sketch evaluation instructions are small to negligible on idea generation productivity.

 

Dynamic loading is a shared feature of tendon tissue homeostasis and pathology. Tendon cells have the inherent ability to sense mechanical loads that initiate molecular-level mechanotransduction pathways. While mature tendons require physiological mechanical loading in order to maintain and fine tune their extracellular matrix architecture, pathological loading initiates an inflammatory-mediated tissue repair pathway that may ultimately result in extracellular matrix dysregulation and tendon degeneration. The exact loading and inflammatory mechanisms involved in tendon healing and pathology is unclear although a precise understanding is imperative to improving therapeutic outcomes of tendon pathologies. Thus, various model systems have been designed to help elucidate the underlying mechanisms of tendon mechanobiology via mimicry of the in vivo tendon architecture and biomechanics. Recent development of model systems has focused on identifying mechanoresponses to various mechanical loading platforms. Less effort has been placed on identifying inflammatory pathways involved in tendon pathology etiology, though inflammation has been implicated in the onset of such chronic injuries. The focus of this work is to highlight the latest discoveries in tendon mechanobiology platforms and specifically identify the gaps for future work. An interdisciplinary approach is necessary to reveal the complex molecular interplay that leads to tendon pathologies and will ultimately identify potential regenerative therapeutic targets. 

This Research Work In Progress Paper examines empirical evidence on the impacts of feedback from an intelligent tutoring software on sketching skill development. Sketching is a vital skill for engineering design, but sketching is only taught limitedly in engineering education. Teaching sketching usually involves one-on-one feedback which limits its application in large classrooms. To meet the demands of feedback for sketching instruction, SketchTivity was developed as an intelligent tutoring software. SketchTivity provides immediate personalized feedback on sketching freehand practice. The current study examines the effectiveness of the feedback of SketchTivity by comparing students practicing with the feedback and without. Students were evaluated on their motivation for practicing sketching, the development of their skills, and their perceptions of the software. This work in progress paper examines preliminary analysis in all three of these areas. 

Sketching exists in many disciplines and varies in how it is assessed, making it challenging to define fundamental sketching skills and the characteristics of a high‐quality sketch. For instructors to apply effective strategies for teaching and assessing engineering sketching, a clear summary of the constructs, metrics, and objectives for sketching assessment across engineering education and related disciplines is needed.

This systematic literature review explores sketching assessment definitions and approaches across engineering education research.

We collected 671 papers from five major engineering and education databases at all skill levels for reported sketching constructs and metrics, cognition, and learning contexts. Based on the selection criteria, we eliminated all but 41 papers, on which we performed content analysis.

Engineering, design, and art emerged as three major disciplines in the papers reviewed. We found that sketching assessment most often employs metrics on accuracy, perspective, line quality, annotations, and aesthetics. Most collected studies examined beginners in undergraduate engineering design sketching or drawing ability tests. Cognitive skills included perceiving the sketch subject, creatively sketching ideas, using metacognition to monitor the sketching process, and using sketching for communication.

Sketching assessment varies by engineering discipline and relies on many types of feedback and scoring metrics. Cognitive theory can inform instructional activities as a foundation for sketching skills. There is a need for robust evidence of high‐quality assessment practices in sketching instruction. Assessment experts can apply their knowledge toward improving sketching assessment development, implementation, and validation.

 

Freehand sketching equips engineers to rapidly represent ideas in the design process, but most engineering curriculums fall short of equipping students with adequate sketching skills. This paper is focused on methods to improve engineers’ sketching skill through type of instruction, length of instruction, and delivery of and feedback for assignments using Sketchtivity, an intelligent sketch-tutoring software. We answer several key questions for providing better sketching education for engineers. Does perspective training improve freehand drawing ability? Can an intelligent tutoring software improve education outcomes? And how much sketching instruction is necessary for engineers? Analyzing the changes in sketching skill from pre- to post-sketching instruction between different instruction types (n = 116), we found that perspective sketching instruction significantly improved freehand sketching ability compared to traditional engineering sketching methods. When comparing pre to post sketching skill of students using Sketchtivity (n = 135), there was no significant difference in improvement between students using the intelligent tutoring software and those that exclusively practiced on paper – both groups improved equally. However, completing sketching tasks on tablets did not hinder students’ skill development even when measured on paper. Future work will more directly explore the influence of Sketchtivity on sketching skill development. Additionally, we found that five weeks of sketching instruction greatly improves sketching skill compared to only three weeks of instruction (n = 108), but both approaches significantly improve sketching self-efficacy. These outcomes support more extensive sketching instruction in engineering classrooms, and changes in instruction type to promote more freehand sketching skills. 

Flow–ecology relationships are critical for developing and adaptively managing environmental flows. However, uncertainty often arises from data limitations and an incomplete understanding of the spatial and temporal attributes inherent to each relationship. Accounting for sources of uncertainty is critical given the mounting interest in implementing environmental flows at large scales, often with limited information. We used the South Fork Eel River watershed in northern California as a case study to demonstrate how data gaps and uncertainty in flow–ecology relationships may be better quantified. A rigorous literature review revealed that few flow–ecology relationships related directly to the flow regime, and none spanned the full range of hydrologic or geomorphic variability exhibited across the watershed. Identified data gaps informed several sensitivity analyses within a Bayesian network model which showed that the modeled ecological outcome differed by as much as 50% depending on the type and magnitude of uncertainty. This study presents a general regional framework for quantifying spatial and temporal data gaps that can be applied to other watersheds and information types to improve representation of uncertainty in flow–ecology relationships and to inform environmental flow design. 

Over the last three years, we have worked in a research practice partnership (RPP) between a research non-profit and three school districts to establish system-wide K-12 pathways that support equitable participation in computational thinking (CT) that is consistent across classrooms, cumulative from year to year, and competency-based. Reflecting on the work done over the last three years, we have identified tensions related to ambition and specificity within our RPP and the development, implementation, and spread of inclusive computing pathways. Ambitions can waver between grandiose upheaval in curriculum and classes and the identification of CT solely in what is already happening. While it is relatively easy to adopt and spread programs that propose modest change, these programs are not necessarily worth an investment nor do they produce CT skills in alignment with the district's overall vision. Similarly, the specificity in which computational thinking is operationalized can teeter between prescriptive lesson plans and broadly-stated curricular standards. Vague initiatives are difficult to implement, but teachers are also resistant to overly prescriptive programs. In this paper, we explore these tensions balancing ambition and specificity using examples from our partner districts. Drawing on our experiences co-designing the inclusive computing pathways as well as interviews with and open-ended questionnaire responses from our district partners, we discuss implications related to these issues and the ongoing tensions around ambition and specificity that need to be considered and overcome in terms of meeting the national call to develop more inclusive computing pathways for schools and districts. 

Shifts in rainfall frequency and intensity can lead to heavy crop loss in rainfed agricultural systems. Small‐scale farmers who plant with limited resources need to carefully select management strategies that are well suited for their environment. Farmers must choose between planting higher‐yielding varieties that take longer to mature and lower‐yielding varieties that can be harvested sooner. To better understand the interactions between rainfall variability, cultivar choice, and cropping success, we implement an ecohydrological model that accounts for variation in daily soil moisture and converts water stress to crop yield. We apply the model to growing conditions of dryland farmers in central Kenya, which is a drought‐prone and semiarid region with spatially heterogeneous rainfall. To simulate stochastic daily rainfall, we derive parameters in 10‐day increments from a 30+ year daily rainfall data set. We use these properties to model the stochastic seasonal water availability for cultivars with different maturation lengths. In agreement with past studies, our analysis shows that storms are becoming more intense and less frequent. We show that maize crops are prone to water deficit in the part of the growing season when crop water requirements are highest. Despite the potential for higher‐yielding, late maturing varieties to improve total harvest, we find that early maturing varieties that are drought‐avoidant have the lowest likelihood of failure. In light of reduced rainfall totals, we show that the historical probability of crop failure was lowest in the past and is now increasing.