skip to main content

Title: Mini-Hints for Improved Spatial Visualization Training
The pedagogical approach of Zone of Proximal Development (ZPD) is based on the belief that effective learning occurs when students are challenged just beyond the level they can do on their own. An expert teacher looking over the shoulder of a student would give just the right amount of hints; too much hinting gives away the solution which deprives the student of the productive struggle that is needed for learning new concepts. Alternatively, no hinting may leave the student frustrated to the point where they give up. A key challenge with online learning is how to provide the right level of hints as if an expert teacher were there. This paper describes the evolution of hints for spatial visualization training using a mobile app. Students sketch orthographic and isometric sketches, which are automatically graded by the app. When a student draws an assignment incorrectly, they are provided with the option of a hint or peeking at the solution. This paper discusses the development of the app feedback and how it has impacted student behavior in using the app. In a first implementation, some students who excessively peeked at the solution without trying very hard on the assignments, did not significantly more » improve their spatial visualization ability as measured by the standardized PSVT:R test. To address the over-use of peeking, gamification was added that rewarded students to try on their own before looking at a hint or peek. In this paper, we look at a classroom trial that used a version of the spatial visualization mobile app with gamification. In general, gamification increased the post PSVT:r test scores. However, there was also a partial negative effect that and we see instances where the gamification lead to student frustration and waste of time because they avoided using hints to maximize their gamification points. We realized that the encompassing the knowledge of an expert teacher in providing hints just when needed, is difficult to implement in an algorithm. Specific examples are presented along with proposed improvements to the in-app hints. The final paper will include data comparing results of a class in January 2018 that used the original hints, with a class in January 2019 that will use the newer hints. « less
; ; ;
Award ID(s):
Publication Date:
Journal Name:
2019 ASEE Annual Conference & Exposition
Sponsoring Org:
National Science Foundation
More Like this
  1. Mobile devices are becoming a more common part of the education experience. Students can access their devices at any time to perform assignments or review material. Mobile apps can have the added advantage of being able to automatically grade student work and provide instantaneous feedback. However, numerous challenges remain in implementing effective mobile educational apps. One challenge is the small screen size of smartphones, which was a concern for a spatial visualization training app where students sketch isometric and orthographic drawings. This app was originally developed for iPads, but the wide prevalence of smartphones led to porting the software to iPhone and Android phones. The sketching assignments on a smartphone screen required more frequent zooming and panning, and one of the hypotheses of this study was that the educational effectiveness on smartphones was the same as on the larger screen sizes using iPad tablets. The spatial visualization mobile sketching app was implemented in a college freshman engineering graphics course to teach students how to sketch orthographic and isometric assignments. The app provides automatic grading and hint feedback to help students when they are stuck. Students in this pilot were assigned sketching problems as homework using their personal devices. Students weremore »administered a pre- and post- spatial visualization test (PSVT-R, a reliable, well-validated instrument) to assess learning gains. The trial analysis focuses on students who entered the course with limited spatial visualization experience as identified based on a score of ≤70% on the PSVT:R since students entering college with low PSVT:R scores are at higher risk of dropping out of STEM majors. Among these low-performing students, those who used the app showed significant progress: (71%) raised their test scores above 70% bringing them out of the at-risk range for dropping out of engineering. While the PSVT:R test has been well validated, there are benefits to developing alternative methods of assessing spatial visualization skills. We developed an assembly pre- and post- test based upon a timed Lego™ exercise. At the start of the quarter, students were timed to see how long it would take them to build small lego sets using only visual instructions. Students were timed again on a different lego set after completion of the spatial visualization app. One benefit of the test was that it illustrated to the engineering students a skill that could be perceived as more relevant to their careers, and thus possibly increased their motivation for spatial visualization training. In addition, it may be possible to adapt the assembly test to elementary school grade levels where the PSVT:R test would not be suitable. Preliminary results show that the average lego build times decreased significantly after using the mobile app, indicating an improvement in students’ spatial reasoning skills. A comparison will also be done between normalized completion times on the assembly test and the PSVT:R tests in order to see how the assembly test compares to the “gold standard”. In addition to the PSVT-R instrument, a survey was conducted to evaluate student usage and their impressions of the app. Students found the app engaging, easy to use, and something they would do whenever they had “a free moment”. 95% of the students recommended the app to a friend if they are struggling with spatial visualization skills. This paper will describe the implementation of the mobile spatial visualization sketching app in a large college classroom, and highlight the app’s impact in increasing self-efficacy in spatial visualization and sketching« less
  2. Spatial visualization training has been shown to increase GPAs and graduation rates in science, technology and math. Furthermore, prior research has correlated sketching on paper to improvement on the standardized spatial visualization test PSVT:R. To take advantage of touchscreen technology, an App, in which students draw orthographic and isometric assignments, was developed for spatial visualization training. Students draw on the touchscreen and then submit their sketch to be graded automatically. If the sketch is incorrect, the students are provided with the option to try again or get customized guidance from the app. This allows students to work independently and get immediate feedback. In 2014, a trial using the App with college engineering students showed that it increased students’ performance on the PSVT:R. The 2014 trial also showed that student persistence, as measured by the number of times they tried a sketch again without asking for help, correlated to increases in the PSVT:R. Since 2014, the App was modified significantly. The assignments were rewritten to take advantage of the touchscreen interface, and persistence was encouraged using gamification and by providing varying levels of guidance. In 2017, two trials were conducted with college engineering students; an elective class (n=32) and a requiredmore »class (n=137). Overall the persistence metric increased from 40% in 2014 to 77% in 2017. The overall gains on the PSVT:R increased from 7% to 9%. However, much larger gains occurred among students who entered the class with low PSVT:R scores (70% and below). These students are considered “at-risk” in terms of low graduation rate due to low spatial visualization ability. In 2014, 23% of these at-risk students improved to the point of moving out of the at-risk category. In 2017 this percentage increased to 82% and 67%. This paper describes the modifications to the App that led to the successful trials in 2017. In O=one of the 2017 trials , the app was implemented as homework, thereby not taking up classroom lecture time, which further eases the incorporation of spatial visualization training into a crowded curriculum.« less
  3. In recent years, it has increasingly been recognized that spatial visualization skills are important in supporting student success in Science, Technology, Engineering, and Math (STEM) education and retention of these students in STEM careers. Many first year college engineering programs and high schools with pre-engineering curriculum have incorporated spatial visualization training into their courses. However, there is no reason why spatial visualization training could not occur at a much younger age, like elementary school. Often at the high school and college level, the Purdue Spatial Visualization Test: Rotations (PSVT:R), which is recognized as a gold standard assessment tool, is used to measure students’ spatial skills learning gains. The PSVT:R is a 20 minute timed test consisting of 30 three-dimensional rotations problems. While the PSVT:R test has been well validated, there are benefits to developing alternative methods of assessing spatial visualization skills suitable for elementary school grades. Researchers at XXX developed an assembly pre- and post- test based upon a timed Lego™ exercise. Students are timed to see how long it would take them to build small Lego shapes using only a picture of the final assembly, but no instructions. The test was implemented at the beginning and then at themore »end of the quarter/semester. The beauty of this assessment is that it lends itself well to K-12 students. The 20 minute, timed PSVT:R test is too challenging for elementary aged children and is not engaging. In order to validate the new instrument, the Lego™ Assembly test was implemented in a pilot study in 2 college freshman engineering courses using students who could do both the PSVT:R and the Lego Assembly™ assessments. At the beginning of the class all students took the PSVT:R test, and half the students performed a Lego™ assembly of one shape and the other half did the assembly test with another shape. During the class the students completed spatial visualization training which taught them how to sketch orthographic and isometric assignments using a mobile sketching app. At the end of the class the PSVT:R test was repeated for all students. The Lego Assembly™ test was also completed, but the students switched which shape they were building. This approach allowed us to normalize the difficulty of the assembly tasks based upon the average time it took to build the shapes in the pre-test. The Lego Assembly™ test was first implemented in winter and spring of 2018. The data showed a correlation of the R-Squared of 0.11 between the assembly times and the PSVT:R scores in pre-test and 0.14 in post-test. However, analysis of the assembly times indicated that the difficulty of the 2 Lego shapes were significantly different, which could skew the normalization of the assembly times. Accordingly, the test was repeated in winter and spring 2019 with Lego shapes of similar difficulty. This paper describes the results of the assembly tess in all 4 classes, and its suitability for a spatial visualization assessment for elementary school age students.« less
  4. Within intelligent tutoring systems, considerable research has in-vestigated hints, including how to generate data-driven hints, what hint con-tent to present, and when to provide hints for optimal learning outcomes. How-ever, less attention has been paid to how hints are presented. In this paper, we propose a new hint delivery mechanism called “Assertions” for providing unsolicited hints in a data-driven intelligent tutor. Assertions are partially-worked example steps designed to appear within a student workspace, and in the same format as student-derived steps, to show students a possible subgoal leading to the solution. We hypothesized that Assertions can help address the well-known hint avoidance problem. In systems that only provide hints upon request, hint avoidance results in students not receiving hints when they are needed. Our unsolicited Assertions do not seek to improve student help-seeking, but rather seek to ensure students receive the help they need. We contrast Assertions with Messages, text-based, unsolicited hints that appear after student inactivity. Our results show that Assertions significantly increase unsolicited hint usage compared to Messages. Further, they show a signifi-cant aptitude-treatment interaction between Assertions and prior proficiency, with Assertions leading students with low prior proficiency to generate shorter (more efficient) posttest solutions faster. We alsomore »present a clustering analysis that shows patterns of productive persistence among students with low prior knowledge when the tutor provides unsolicited help in the form of Assertions. Overall, this work provides encouraging evidence that hint presentation can significantly impact how students use them and using Assertions can be an effective way to address help avoidance.« less
  5. This Research to Practice work-in-progress paper examines the impact of eGrove Education’s Spatial Vis touchscreen application for teaching spatial visualization. Research has shown that competency with spatial visualization is correlated with success in engineering, but few engineering programs explicitly teach this skill. In this paper, we describe a controlled trial (n=55) in which the app was assigned as homework for the experimental group, but no additional lecture time was dedicated to spatial visualization training. Our analysis focuses on students who entered the course with limited spatial visualization experience as identified based on a score of ≤70% on the PSVT:R (a reliable, well-validated instrument). Among these low- performing students, those who used the app showed remarkable progress – 8 of 13 (62%) raised their test scores above 70% compared to just 2 of 14 (14%) in the control group. Students in both the experimental and control groups showed statistically significant increases between the pre- and post-test scores (paired t-test), though the difference in the gains between the two groups was statistically insignificant as the study was underpowered. While larger trials will be needed, this work suggests that the Spatial Vis app is a promising intervention for training spatial visualization skills.