Displaying all 8 results
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- The Best of Computers in Education Division (COED)
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- 2024 ASEE Annual Conference & Exposition
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- Phyllis J. Beck, Mississippi State University; Mahnas Jean Mohammadi-Aragh, Mississippi State University
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- Diversity
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- 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
- Computers in Education Division (COED) Poster Session
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- 2024 ASEE Annual Conference & Exposition
- Authors
- Quintana (Quincy) Clark, Oregon State University; Chidinma Grace Okoye; Theodore Ja
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(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
- 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
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- Diversity
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- 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
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- 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
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- 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
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- 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
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- 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
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- Programming Education 1
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- 2024 ASEE Annual Conference & Exposition
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- 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
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- 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
- 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