Understanding how Learner Outcomes Could be Affected through the Implementation of Augmented Reality in an Introductory Engineering Graphics Course

The study was designed to investigate the implementation of AR in an introductory engineering graphics course. In order to investigate the potential of AR, the software and assignments were aligned with course content. The study was driven by three research questions that examined how AR influenced student motivation, enhanced the learning experience, and/or affected the spatial visualization ability of students. To address these questions the three data collection methods used were the MSLQ, PSVT-R and student questions. The MSLQ results indicated that AR had a positive impact on the student’s intrinsic motivation. The PSVT-R results showed an increase of spatial visualization scores. The student questions revealed that the students enjoyed the experience and believed that it was beneficial to their success in the course. Overall, the results from the two instruments and student questions were inconclusive, but the compilation of data highlights the potential of the technology and builds upon previous research. Introduction The study was designed and built upon previous research surrounding the use of augmented reality (AR) in engineering graphics courses (Chen, Chi, Hung, & Kang, 2011; Haley-Hermiz, et al., 2012; Huffman & Miller, 2012). The intention was to investigate the effectiveness of AR as a supplemental learning tool in an introductory engineering graphics course. The study investigated the impact of AR from three different perspectives. For one, the study was designed to determine how AR affected the motivational attitudes of students. Additionally, the study examined the role of AR as a tool to improve spatial visualization skills of students. Finally, the study investigated how students were able to manipulate, experiment, and engage with the augmented models. Methodology The sample used in the study consisted of 50 (N = 50) students from two different sections of an introductory engineering graphics course at a large public southeastern university. The majority of the sample population was male (70%) and predominately composed of engineering majors (92%). For most of the students this was their first engineering based course. The AR intervention was conducted over six weekly sessions. Each session lasted for 90 minutes and required students to complete an assignment with the assistance of AR. All of the assignments aligned with the course content and were designed to reinforce previously taught engineering concepts. Upon entering the classroom 69th EDGD Midyear Conference Proceedings 49 Understanding How Learner Outcomes Could be Affected through the Implementation of Augmented Reality in an Introductory Engineering Graphics Course students were given an iPad with a pre-loaded AR model that aligned with an assignment from the course book. Students then used the AR model to assist them in the creation of the assignment in SolidWorks. Results To measure the effectiveness of the AR system used in the study, multiple data collection methods were incorporated. This consisted of two different measurements: Motivated Strategies Learning Questionnaire (MSLQ), Purdue Spatial Visualization for Rotations (PSVT-R), and seven questions involving the approach of basic interpretive methodology on the student experience with AR. Both the MSLQ and PSVT-R used a preand post-test format, while the seven-questions were administered at the conclusion of the study. The use of a pre-testintervention-post-test design is an appropriate method of investigation to determine the effects of innovations on education (Dugard & Todman, 1995). MSLQ. The MSLQ was selected because of its ability to measure student motivation (Pintrich, Smith, Garcia, & Mckeachie, 1993). An abbreviated version of the MSLQ was used in the study and has been used in numerous studies (Bye, Pushkar, & Conway, 2007; Clark, Ernst, & Scales, 2009; Matthews, 2004). The abbreviated MSLQ consisted of five motivation subscales and an overall MSLQ score. The first subscale, intrinsic goal orientation, was the only subscale to show a statistical difference between the preand post-test scores (p = .01) see table 1. Subscales of extrinsic goal orientation, task value component, control of learning beliefs, and self-efficacy showed no statistical difference between preand post-test scores. In addition, there was no statistical difference between the preand post-tests scores on the overall MSLQ survey. Based on these findings, the null hypothesis that AR will have no significant impact on the motivational attitudes of students was not rejected. Table 1 Paired Samples Test for MSLQ Subscales and Overall Summary 95% Confidence Interval of the Difference Mean Std. Deviation Std. Error Mean Lower Upper T Df Sig. 2tailed