Displaying all 16 results
- Conference Session
- The Best of Computers in Education Division (COED)
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Phyllis J. Beck, Mississippi State University; Mahnas Jean Mohammadi-Aragh, Mississippi State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
formative times in their computing education [6, 8]. There have been many attempts at developing novel approaches to support various aspects of programming metacognition, improve self-efficacy, and provide automated feedback and assessment for students in introductory programming courses [5, 6, 8]. Programming metacognition can be broadly defined as how students think about programming and the problem-solving strategies they employ to achieve a goal when given a programming task [9]. However, most of these methods have yet to be successfully scaled and applied in the classroom. Previous studies suffer from issues such as being too small, difficult to validate or replicate, and software that is not shared or is abandoned
- Conference Session
- The Best of Computers in Education
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Jayma Koval, Georgia Institute of Technology; Diley Hernandez, Georgia Institute of Technology; Tom McKlin; Douglas Edwards, Georgia Institute of Technology; Rafael A. Arce-Nazario; Joseph Carroll-Miranda; Isaris Rebeca Quinones Perez, University of Puerto Rico, Rio Piedras; Lilliana Marrero-Solis; Jason Freeman, Georgia Institute of Technology; Taneisha Lee Brown; Pascua Padro; Stephen Garrett; Analia E. Rao; Marion Usselman, Georgia Institute of Technology
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
] and measured to what extent students felt included,valued and respected. We used this scale with the purpose of exploring students’ sense ofbelongingness, specifically in CS, and modified the items to include “in computing.” Adefinition of computing was also included, “Computing is defined as doing things like making anapp, coding, fixing a computer or mobile device, creating games, making digital music, etc.”Sample questions then asked students to indicate the extent to which they agreed with statementssuch as, “I feel comfortable in computing” and “Compared with most other students at myschool, I know how to do well in computing.”Self-Efficacy: Self-efficacy captures students’ beliefs that they can accomplish designated tasks[38] related to
- Conference Session
- COED: Skills for Moving from Computing Student to Professional
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Stephanie Jill Lunn, Florida International University; Veon Brewster, Florida International University
- Tagged Divisions
- Computers in Education Division (COED)
job seekers. The system, called VirtualInterview (VI)-Ready, offers an immersive role-play of interview scenarios with 3D virtual agentsserving as hiring managers. We applied Bandura’s concept of self-efficacy as we investigated: 1)overall impressions of the system; 2) the impact on students’ job interview preparedness; and 3)how internal perceptions of interview performance may differ from external evaluations by hiringmanagers. In our study, we employed a convergent parallel mixed methods approach.Undergraduate and graduate students (n = 20) underwent virtual job interviews using theplatform, each interacting with one of two different agents (10 were randomly assigned to each).Their interactions were video recorded. Participants then
- Conference Session
- COED: AI and ML Topics
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Jonathan Adam Niemirowski, Louisiana Tech University; Krystal Corbett Cruse, Louisiana Tech University; David Hall, Louisiana Tech University
- Tagged Divisions
- Computers in Education Division (COED)
dataset. This dataset incorporated condition-base scaling to account for the six operational modes within the data (Figure 3), as each mode could have its own nominal sensor values and failure points. Studentswere instructed to write a report showing their models’ performance: Figure 4 shows onestudent’s visualization of their RNN model, measuring the predicted RUL value to the test data’sRUL value for five engine units. The model’s performance accounted for 30% of their grade,compared to a baseline linear regression model with no data processing. Figure 4. Final Project RNN Model Performance (From Student’s Final Project)Results of pre and post course surveysA self-efficacy survey was selected as the primary
- Conference Session
- Computers in Education Division (COED) Poster Session
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Quintana (Quincy) Clark, Oregon State University; Chidinma Grace Okoye; Theodore Ja
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
(1994) usability inspection methods, usability testing will be done throughfocus groups to explore participants’ perceptions of the user interface design, identify designproblems, and uncover areas to improve the user interface and user experience in Ecampus andhybrid courses (RQ1). A heuristics evaluation [16, 17] of the user interface will be conducted toensure that usability principles are followed to provide a user interface with inclusivity andaccessibility (RQ2). A Likert scale will be adapted from Bandura’s (1989) MultidimensionalScales of Perceived Self-Efficacy [18] to explore participants' self-regulatory efficacy (RQ3).Planned InterventionThe proposed study will combine elements of both exploratory and quasi-experimental
- Conference Session
- COED Programming Education 2: Instructional Approaches
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Richard Whalen, Northeastern University; Joshua L. Hertz, Northeastern University
- Tagged Divisions
- Computers in Education Division (COED)
introduction to hardware applications. Oncethey have gained facility in the programming language, they then apply this knowledge tohardware applications. In an alternative approach being piloted during this study, students areintroduced to programming and algorithmic thinking via the hardware applications; the material isintroduced concurrently instead of sequentially.Findings from pre and post-surveys indicate that students taught using both approaches had similarimprovements in self-efficacy to code and build projects with basic circuitry. In addition, moststudents appreciated the approach used in their class; if taught with a hardware-first approach, theythought a hardware-first approach provides greater learning, and if taught with a software
- Conference Session
- COED: Grading Systems
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Marko V. Lubarda, University of California, San Diego; Alex M. Phan, University of California, San Diego; Aidan Daniel Carrigg; Karthik Srinivasan; Josephine Relaford-Doyle, University of California, San Diego
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
differences in GPA alone. Analysis of students’survey responses shows that real-time feedback and unlimited submission attempts helpedstudents assess their learning progress and motivated them to continuously improve theirsolutions. Instant feedback and unlimited submission attempts were regarded by students aslikely having positively impacted academic integrity in the course. The effect of automatedfeedback and optional assignments on students’ need to visit office hours is explored.Implications for future pedagogical practice and research are discussed.IntroductionTimely and effective feedback provided to students on their submitted work has the potential tosignificantly enhance learning, improve student self-efficacy, reduce drop-out rates, and
- Conference Session
- COED: AI and ML Topics
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Nebojsa I. Jaksic, Colorado State University, Pueblo; Bahaa Ansaf, Colorado State University, Pueblo
- Tagged Divisions
- Computers in Education Division (COED)
experiences and projects are important partsof learning. Later, Kolb, in his Experiential Learning Cycle (KLC) [2], placed large importance onexperiencing and applying/doing as essential elements of optimal learning. Positive experientiallearning from accomplishing successful projects is also emphasized as an important component ofincreasing self-efficacy [3]. Therefore, it is not surprising that KLC implementations were reportedin most of the engineering disciplines like civil engineering [4] – [6], mechanical engineering [6],chemical engineering [4], [5], [7], aeronautical engineering [6], industrial engineering [8], andmanufacturing engineering [4], [5], [9]. Bansal and Kumar [10] describe a state-of-the-art IoTecosystem that includes edge devices
- Conference Session
- Computers in Education Division (COED) Poster Session
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Valerie A Carr, San Jose State University; Jennifer Avena, University of Northern Colorado; Maureen Smith; Wendy Lee, San Jose State University; David Schuster, San Jose State University; Belle Wei, San Jose State University
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
Engineering Education, 2024 Work in Progress: Community College Student Experiences with Interdisciplinary Computing Modules in Introductory Biology and Statistics CoursesAbstractInterdisciplinary professionals with both domain and computing skills are in high demand in ourincreasingly digital workplace. Universities have begun offering interdisciplinary computingdegrees to meet this demand, but many community college students are not provided learningexperiences that foster their self-efficacy in pursuing them. The Applied ProgrammingExperiences (APEX) program aims to address this issue by embedding computing modules intointroductory biology and statistics courses at community colleges. Here, we describe an
- Conference Session
- Computers in Education Division (COED) Poster Session
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Lisa Cullington, Sacred Heart University; Mary V Villani, Farmingdale State College, SUNY, New York; Nur Dean, Farmingdale State College, SUNY, New York; Moaath Alrajab, Farmingdale State College, SUNY, New York; Arthur Hoskey, Farmingdale State College SUNY, New York; Ilknur Aydin, Farmingdale State College, SUNY, New York
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
’ Sense of Belonging: A Key to Educational Success for AllStudents. (2nd ed.). Routledge, 2018.[5] C. Gillen-O’Neel, “Sense of belonging and student engagement: A daily study of first- andcontinuing-generation college students,” Research in Higher Education, vol. 62, no. 1, pp. 45-71,Feb. 2021.[6] M. Bong and E.M. Skaalvik, “Academic self-concept and self-efficacy: How different arethey really?,” Educational Psychology Review, vol. 15, pp. 1-40, Jan. 2003.[7] D.W. Johnson, R.T. Johnson and K.A. Smith. Active Learning: Cooperation in the CollegeClassroom. Edina, MN: Interaction Book Company, 1991.[8] M.J. Baker, “Collaboration in collaborative learning,” Interaction Studies: Social behaviourand communication in biological and artificial systems
- Conference Session
- Computers in Education Division (COED) Poster Session
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Ahmed Ashraf Butt, Carnegie Mellon University; Eesha tur razia babar, University of California, Irvine; Muhsin Menekse, Purdue University, West Lafayette; Ali Alhaddad, Purdue University, West Lafayette
- Tagged Topics
- Diversity
- Tagged Divisions
- Computers in Education Division (COED)
the OR: exploring use of augmented reality to support endoscopic surgery,” in Proceedings of the 2022 ACM International Conference on Interactive Media Experiences, in IMX ’22. New York, NY, USA: Association for Computing Machinery, 2022, pp. 267–270. doi: 10.1145/3505284.3532970.[30] T. Khan et al., “Understanding Effects of Visual Feedback Delay in AR on Fine Motor Surgical Tasks,” IEEE Transactions on Visualization and Computer Graphics, vol. 29, no. 11, pp. 4697–4707, Nov. 2023, doi: 10.1109/TVCG.2023.3320214.[31] M. Menekse, S. Anwar, and S. Purzer, “Self-Efficacy and Mobile Learning Technologies: A Case Study of CourseMIRROR,” in Self-Efficacy in Instructional Technology Contexts, C. B. Hodges, Ed., Cham
- Conference Session
- Simulations and Virtual Learning
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- David M. Feinauer P.E., Virginia Military Institute; James C. Squire P.E., Virginia Military Institute; Gerald Sullivan, Virginia Military Institute
- Tagged Divisions
- Computers in Education Division (COED)
scenarios to understand aconcept or relationship. The tool measures the students’ self-efficacy beliefs with respect to theirknowledge gained from using the tool, and objectively measures their understanding of theconcepts as well as their confidence in their understanding.The Methods section details the study instruments and the software tools developed. The Resultssection provides details on the recorded differences in student learning attainment as measuredby student performance on the interactive posttest. Multiple factors affecting studentperformance including time spent exploring the software tool and interface type (continuous vsdiscrete) were explored. The new direct metric of student interaction time combined with theincreased sample size
- Conference Session
- Programming Education 1
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Chi Yan Daniel Leung, zyBooks, A Wiley Brand; Joe Mazzone, zyBooks, A Wiley Brand; Efthymia Kazakou, zyBooks, A Wiley Brand; Chelsea Gordon, zyBooks, A Wiley Brand; Alex Daniel Edgcomb, zyBooks, A Wiley Brand; Yamuna Rajasekhar, zyBooks, A Wiley Brand
- Tagged Divisions
- Computers in Education Division (COED)
had on programming labs’ completion. Such analysis may compare courses where hints were provided and courses where hints were not provided for the same problems, including controls for other confounds, such as different instructors, course offerings, student demographics, and more. Future work may also evaluate student self-efficacy, including a student's belief that the hint system impacted that student's self-efficacy.Conclusion dvanced zyLabs includes many powerful features, for students and instructors, includingAindustry-standard IDEs, highly-customizable development environment and tools, Linux machine’s desktop, collaborative environments, and more. Nonetheless, each metric of student usage was about the
- Conference Session
- COED: Computing in K-12 / Early Childhood Education
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Jaejin Hwang, Northern Illinois University; sungchul lee, Sun Moon University, South Korea; Yanghee Kim; Mobasshira Zaman, Northern Illinois University; Sobhit Pokhrel
- Tagged Divisions
- Computers in Education Division (COED)
Paper ID #37589Active Project: Supporting Young Children’s Computational ThinkingSkills Using a Mixed-Reality EnvironmentDr. Jaejin Hwang, Northern Illinois University Dr. Jaejin Hwang, is an Associate Professor of Industrial and Systems Engineering at NIU. His expertise lies in physical ergonomics and occupational biomechanics and exposure assessment. His representative works include the design of VR/AR user interfaces to minimize the physical and cognitive demands of users. He specializes in the measurements of bodily movement as well as muscle activity and intensity to assess the responses to physical and environmental
- Conference Session
- Computers in Education Division (COED) Poster Session
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Syed Hasib Akhter Faruqui, Sam Houston State University; Nazia Tasnim, University of Texas at Austin; Iftekhar Ibne Basith, Sam Houston State University; Suleiman M Obeidat, Texas A&M University; Faruk Yildiz, Sam Houston State University
- Tagged Divisions
- Computers in Education Division (COED)
practice examples to build their self-efficacy, while those who are highly motivated maybenefit from more challenging tasks to maintain their engagement. Furthermore, linguistic diver-sity must also be acknowledged, considering language preferences. Non-native English speak-ers may require additional language support to comprehend complex texts. The ideal technologywould be able to comprehend these conditions, interpret the knowledge and provide personalizedand context-aware explanations similar to a human instructor. This level of adaptability wouldsignificantly enhance the learning experience, making it more engaging, effective, and tailored toindividual students’ needs.In recent years, advances in artificial intelligence (AI), machine learning
- Conference Session
- The Best of Computers in Education
- Collection
- 2023 ASEE Annual Conference & Exposition
- Authors
- Shameel Abdulla, Texas A&M University, Qatar; Yasser M. Al Hamidi, Texas A&M University, Qatar; Marwan Khraisheh, Texas A&M University, Qatar
- Tagged Divisions
- Computers in Education Division (COED)
Invisible Understaffing Epidemic | Learning Innovation.," [Online]. Available: https://www.insidehighered.com/blogs/learning-innovation/higher- ed%E2%80%99s-invisible-understaffing-epidemic. [Accessed 6 2 2023].[9] L. Boyle and J. P. M. Reid, "Turning Office Hours into Study Sessions: Impacts on Students' Homework and Exam Grades," in 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference, 2021.[10] R. V. Adams and E. Blair, "Impact of Time Management Behaviors on Undergraduate Engineering Students' Performance," SAGE Open, vol. 9, p. 215824401882450, January 2019.[11] T. A. B. Sophia Lerner Pink and S. Sheppard, "What Makes an Inquisitive Engineer? An Exploration of Question-Asking, Self-Efficacy, and