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  1. Abstract

    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.

     
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  2. Perspective sketching is a skill that is required for a variety of jobs including, but not limited to, architectural design, graphic design, and engineering. Sketching however, is a difficult skill to grasp for people early and can take a while to learn. Recently, there have been many intelligent tutoring systems (ITSs) designed to help improve people’s drawing skills. The feedback system for the perspective drawing lessons in SketchTivity, one such ITS, is currently limited to smoothness, speed, and accuracy of the lines. Our team plans to improve upon this feedback system so that the feedback provided to a user is now more nuanced as well as more actionable to reaffirm future learning. To evaluate our system we will conduct a user study with 40 students that involves going through several sketching lessons and then sketching a street corner in 2-D perspective. We plan to run a between-subjects user study with our participants to determine if our adjustment has any effect on the improvement of sketching skills and the usability of the application. We hope to determine that providing the user with data for their smoothness, speed, and accuracy after four sketching prompts can cause an overall improvement in the students’ scores in comparison to at the end of their sketching session. The algorithm that we created to identify a student’s potential issue we hope will be able to provide accurate, actionable feedback in most situations. The visual alterations we made to SketchTivity we expect to have a positive impact on the perspective feedback system and alter the students sketching performance. In future iterations the algorithm should be further refined and the data collected from the students sketches should be further developed to provide more data to create more actionable recommendations for improved sketching performance and retention. 
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  3. Sketching skills are developed over time through practice, requiring students to stay motivated to continue improving. Gamification has been shown to be helpful in keeping users motivated, so this work seeks to investigate the impact of gamification on the user’s motivation to practice sketching skills in the intelligent tutoring system, SketchTivity. Specifically, this work will evaluate the impact of gamified elements including achievement banners, star ratings, and performance statistics to give users feedback about their level of success after a sketching lesson. This concept will be explored through within subjects focus group testing where participants will interact with each version of the interface, describe their experiences in a think-aloud fashion, and discuss their preferences in a post-interview. The motivational impact of the gamified elements will be synthesized through thematic analysis of the think-aloud comments and interview data as well as statistical analysis of performance differences in terms of SketchTivity’s sketch quality metrics. 
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  4. 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. 
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  5. 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. 
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  6. Freehand sketching is a powerful skill in engineering design [1, 2]. Freehand sketching empowers designers in the early stages of design to express ideas, communicate with stakeholders, and evaluate concepts at a rapid pace. However, teaching sketching in engineering education poses unique challenges for the classroom. Sketching in other domains is often taught in studio-style courses where instructors can provide personalized feedback on technique. This type of feedback is not possible in typical large entry-level engineering graphics courses. To address this problem, Sketchtivity was developed as an intelligent tutoring software to aid instructors in providing feedback on sketching. Using a tablet and smart pen, learners receive real-time personalized feedback on sketching practice. The main goals of this project are to improve sketching instruction methods, understand the educational efficacy of Sketchtivity, and work towards improving the feedback and content of Sketchtivity. 
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  7. Sketching is a valuable skill in engineering for representing information, developing design ideas, and communicating technical and abstract information. It is an important means of developing spatial abilities which are predictive of success in STEM fields. While existing spatial ability tests are predictive of engineering visualization skills, they do not allow students to develop drawing skills through spatial exercises. The Object Assembly Sketching test examines sketching skills with object assembly tasks using mental imagery and mental rotation. This study focuses on the development and pilot testing of a new sketching skills test using object assembly exercises. We piloted the test in two sections of an undergraduate mechanical engineering design course. Inter-rater reliability of two raters scoring students sketches on eight criteria was acceptable across exercises, but low across criteria. Students scored highest on Representation Accuracy, Scale, and Symmetry, and exhibited complex understanding of perspective sketching. We intend to revise the rubric to score for aesthetics and make instructions more precise. 
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  8. 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. 
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  9. Drawing, as a skill, is closely tied to many creative fields and it is a unique practice for every individual. Drawing has been shown to improve cognitive and communicative abilities, such as visual communication, problem-solving skills, students’ academic achievement, awareness of and attention to surrounding details, and sharpened analytical skills. Drawing also stimulates both sides of the brain and improves peripheral skills of writing, 3-D spatial recognition, critical thinking, and brainstorming. People are often exposed to drawing as children, drawing their families, their houses, animals, and, most notably, their imaginative ideas. These skills develop over time naturally to some extent, however, while the base concept of drawing is a basic skill, the mastery of this skill requires extensive practice and it can often be significantly impacted by the self-efficacy of an individual. Sketchtivity is an AI tool developed by Texas A&M University to facilitate the growth of drawing skills and track their performance. Sketching skill development depends in part on students’ self-efficacy associated with their drawing abilities. Gauging the drawing self-efficacy of individuals is critical in understanding the impact that this drawing practice has had with this new novel instrument, especially in contrast to traditional practicing methods. It may also be very useful for other researchers, educators, and technologists. This study reports the development and initial validation of a new 13-item measure that assesses perceived drawing self efficacy. The13 items to measure drawing self efficacy were developed based on Bandura’s guide for constructing Self-Efficacy Scales. The participants in the study consisted of 222 high school students from engineering, art, and pre-calculus classes. Internal consistency of the 13 observed items were found to be very high (Cronbach alpha: 0.943), indicating a high reliability of the scale. Exploratory Factor Analysis was performed to further investigate the variance among the 13 observed items, to find the underlying latent factors that influenced the observed items, and to see if the items needed revision. We found that a three model was the best fit for our data, given fit statistics and model interpretability. The factors are: Factor 1: Self-efficacy with respect to drawing specific objects; Factor 2: Self-efficacy with respect to drawing practically to solve problems, communicating with others, and brainstorming ideas; Factor 3: Self-efficacy with respect to drawing to create, express ideas, and use one’s imagination. An alternative four-factor model is also discussed. The purpose of our study is to inform interventions that increase self-efficacy. We believe that this assessment will be valuable especially for education researchers who implement AI-based tools to measure drawing skills.This initial validity study shows promising results for a new measure of drawing self-efficacy. Further validation with new populations and drawing classes is needed to support its use, and further psychometric testing of item-level performance. In the future, this self-efficacy assessment could be used by teachers and researchers to guide instructional interventions meant to increase drawing self-efficacy. 
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