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Makerspaces are common in engineering programs around the country and around the world. As universities invest more into these spaces, researchers investigate more the impacts of making in the educational setting. As more students across more educational contexts get involved in making and makerspaces, there is a greater need for educators to gain a more wholistic understanding of the impacts of making on the academic environment, both positive and negative. In this paper, we look at the critical relationship between makerspaces and academic performance at a unique university with a design-centric approach to engineering education. This study presents three key findings: First, more involvement in making early in the curriculum is related to increased retention. Second, increased anxiety towards engineering design is connected to both lower retention and lower involvement in academic makerspaces. Third, GPA and makerspace activity are largely independent at this university where the engineering curriculum prescribes engineering students’ engagement in making. As impacts of academic makerspaces are unfolding before us, these findings shed a positive light on their contribution to engineering education. 

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. 

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. 

Abstract—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 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. 

In online or large in-person course sections, instructors often adopt an online homework tool to alleviate the burden of grading. While these systems can quickly tell students whether they got a problem correct for a multiple-choice or numeric answer, they are unable to provide feedback on students’ free body diagrams. As the process of sketching a free body diagram correctly is a foundational skill to solving engineering problems, the loss of feedback to the students in this area is a detriment to students. To address the need for rapid feedback on students’ free body diagram sketching, the research team developed an online, sketch-recognition system called Mechanix. This system allows students to sketch free body diagrams, including for trusses, and receive instant feedback on their sketches. The sketching feedback is ungraded. After the students have a correct sketch, they are then able to enter in the numeric answers for the problem and submit those for a grade. Thereby, the platform offers the grading convenience of other online homework systems but also helps the students develop their free body diagram sketching skills. To assess the efficacy of this experimental system, standard concept inventories were administered pre- and post-semester for both experimental and control groups. The unfamiliarity or difficulty of some advanced problems in the Statics Concept Inventory, however, appeared to discourage students, and many would stop putting in any effort after a few problems that were especially challenging to solve. This effect was especially pronounced with the Construction majors versus the Mechanical Engineering majors in the test group. To address this tendency and therefore collect more complete pre- and post-semester concept inventory data, the research group worked on reordering the Statics Concept Inventory questions from more familiar to more challenging, based upon the past performance of the initial students taking the survey. This paper describes the process and results of the effort to reorder this instrument in order to increase Construction student participation and, therefore, the researchers’ ability to measure the impact of the Mechanix system. 

Freehand sketching equips engineers to represent ideas rapidly 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. 

It is challenging to effectively educate in large classes with students from a multitude of backgrounds. Many introductory engineering courses in universities have hundreds of students, and some online classes are even larger. Instructors in these circumstances often turn to online homework systems, which help greatly reduce the grading burden; however, they come at the cost of reducing the quality of feedback that students receive. Since online systems typically can only automatically grade multiple choice or numeric answer questions, students predominately do not receive feedback on the critical skill of sketching free-body diagrams (FBD). An online, sketch-recognition based tutoring system called Mechanix requires students to draw free-body diagrams for introductory statics courses in addition to grading their final answers. Students receive feedback about their diagrams that would otherwise be difficult for instructors to provide in large classes. Additionally, Mechanix can grade open-ended truss design problems with an indeterminate number of solutions. Mechanix has been in use for over six semesters at five different universities by over 1000 students to study its effectiveness. Students used Mechanix for one to three homework assignments covering free-body diagrams, static truss analysis, and truss design for an open-ended problem. Preliminary results suggest the system increases homework engagement and effort for students who are struggling and is as effective as other homework systems for teaching statics. Focus groups showed students enjoyed using Mechanix and that it helped their learning process.