Conference Session

Computers in Education Division Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Wen Huang, Arizona State University, Polytechnic campus

Tagged Divisions

Computers in Education

Teamwork ?,” Int. J. Innov. Sci. Math. Educ., vol. 25, no. 4, pp. 32–44, 2017.[4] Technavio, “VR in Education Market - Trends and Forecasts,” 2017. [Online]. Available: https://www.businesswire.com/news/home/20170515006621/en/VR-Education-Market--- Trends-Forecasts-Technavio.[5] C. Toh, S. Miller, and T. Simpson, “The impact of virtual product dissection environments on student design learning and self-efficacy,” J. Eng. Des., vol. 26, pp. 48–73, 2015.[6] A. G. Abulrub, A. Attridge, and M. A. Williams, “Virtual Reality in Engineering Education : The Future of Creative Learning,” in Global Engineering Education Conference (EDUCON), 2011, pp. 751–757.[7] A. Richert, M. Shehadeh, and F. Willicks, “Digital

Conference Session

Modeling and Simulation

Collection

2016 ASEE Annual Conference & Exposition

Authors

Elif Miskioglu, Bucknell University; Kaela M Martin, Embry-Riddle Aeronautical University, Prescott

Tagged Divisions

Computers in Education

instructionalsoftware emphasized lower-level cognitive processes,9 but a larger number report learning gainswhen implementing technology in the classroom through virtual experiments or onlineinstruction.10-13 Additionally, incorporating simulations into the classroom can increasevisualization and problem-solving processes,14,15 as well as show positive gains in student self-efficacy with respect to engineering skills.16Virtual experiments offer an opportunity to provide students with valuable experience at a lowcost (no laboratory space or consumables, only computer facilities, required), high flexibility(can be performed outside of class, does not require direct supervision, safety is not a directconcern), and great breadth (some disciplines may have

Conference Session

Data Analysis and Assessment

Collection

2015 ASEE Annual Conference & Exposition

Authors

David B. Knight, Virginia Tech, Department of Engineering Education; Cory Brozina, Virginia Tech; Eric M. Stauffer, Virginia Tech; Chris Frisina, Virginia Tech; Troy D. Abel, Virginia Tech

Tagged Divisions

Computers in Education

is an investigation of how studentsinteract with data or how faculty can use data to change teaching.3 Practices that select relevantdata traces and develop dashboards with learners instead of for learners may lead to strongerstudent self-efficacy, build on existing social learning theory, and benefit from perspectivesfound within human centered design practices.Our interdisciplinary team of faculty and graduate students from engineering education,computer science, human computer interaction, human centered design, learning sciences, andvisual communications are following a mixed-methods, human centered approach to dashboarddevelopment that breaks new ground in learning analytics by involving the end users throughoutthe dashboard design and

Conference Session

Technology-Related Educational Research

Collection

2016 ASEE Annual Conference & Exposition

Authors

Ting-Ting Wu, Graduate School of Technological and Vocational Education, National Yunlin University of Science and Technology; Yueh-Min (Ray) Huang, Cheng-Kung University; Rustam Shadiev, Department of Engineering Science, National Cheng Kung University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

discussion and collaborative leaning, they could get problem solutions and deepen theircognitive understanding and thus develop the abilities of critical thinking and professionaljudgment.According to the results of the experiment, the peer evaluation has the lowest score amongthe three evaluation methods because of the competition among peers, while the self-evaluation and the expert evaluation share a similar score. Additionally, the analysis of thelearning behaviors show that most of the students with low creativity read and downloadedinformation in the learning system and interacted with peers in the platform to have diverseviews and enhance their abilities of self-efficacy analysis; the students with high creativitywere willing to seek, explore

Conference Session

Computers in Education Division Technical Session 1: Topics Related to Engineering - Part 1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Fadi Castronovo, California State University, East Bay; Robert Schaffer, Mission College; Varsha Reddy Kandi

Tagged Divisions

Computers in Education

. Due to these successful pilot implementations, the next step in the research will be toevaluate the value of this curricular design. In the Spring of 2020, the authors will begin toevaluate the impact of the inclusion of this technology on students’ learning as it relates to theirself-efficacy, motivation, degree of engagement, and sense of belonging. The evaluation planwill entail a series of pre-test and post-test experiments. All students will receive pre-testmaterial based on the dependent measures, which include self-efficacy, motivation, degree ofengagement, and sense of belonging. These measures have already been constructed andvalidated and will provide a baseline. The authors aim at using the surveys developed by theLawrence Hall of

Conference Session

Technical Session 13: Digital Learning

Collection

2019 ASEE Annual Conference & Exposition

Authors

Sang Myong Yim, United States Military Academy; Christopher J. Lowrance, United States Military Academy; Eric M. Sturzinger, United States Military Academy

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

quitting, suggesting that the most pertinent information should appear in the first half ofthe video.Wu et al. investigated the key factors of student learning satisfaction in a blended e-learningenvironment, where instruction consisted of a mix of face-to-face and online education. 9 Theyargued that a blended learning environment has the potential to maximize the best advantages ofboth instructor-driven and online education. Using questionnaire data, they discovered thatcomputer self-efficacy, system functionality, content feature, and interaction all impact a student’sexpectations, learning climate, and satisfaction of a course.Lim et al. looked at the differences in learning outcomes and student perceptions betweenstudents enrolled in two

Conference Session

Computer-Based Tests, Problems, and Other Instructional Materials

Collection

2015 ASEE Annual Conference & Exposition

Authors

Dongdong Zhang, Prairie View A&M University; Xiaobo Peng, Prairie View A&M University; Bugrahan Yalvac, Texas A&M University; Deniz Eseryel, North Carolina State University; Uzair Nadeem, Prairie View A&M University; Atiq Islam, Prairie View A&M University; Deron Arceneaux, Prairie View A&M University

Tagged Divisions

Computers in Education

autonomy. The learner can stop,rewind, and replay a screencast as many times as she wants and move with her own pace. Shecan watch the screencast at any location and time on a world-wide-web browser that can be on apersonal computer, a tablet, or a smart phone. The initial learning is fast since students do not Page 26.737.3spend time in interpreting the steps and avoid the laborious trial-and-error process. Since astudent learns by observing the desired behavior of an expert on the screencast, it aids learnerswith low self-efficacy in exploring the demonstrated behaviors1. Teaching how to use CAD software with the screencasts has additional