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Building a Better Mouse Trap - Using AI to catch Submitted AI work.

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Colorado Convention Center, Bluebird Ballroom Lobby, Table 28

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Presenters

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Professor
Dallas College
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Irving ISD

Session description

Determining the level of AI work being submitted by students is very difficult. The goal of this presentation is to provide instructors with various AI tools and techniques that can be used to determine the level of AI work being submitted.

Purpose & objective

Participants will be able to review submitted works by students to determine the level of authenticity and plagiarism using various AI search tools.
Participants can develop well-structured prompts on various Chatbot AI applications to perform relevant searches for information on applications and instructional topics.
Participants will be able to better understand the structure of AI prompts and queries.

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Outline

10 minutes - Introduction to AI Chatbots.
5 -10 minutes - Discuss what Generative AI is and how it works.
10 minutes - Discuss and demonstrate some AI tools students can use to do their work.
10 minutes - Demonstration of how to use various AI tools to determine the level of student authenticity and AI development.
The remainder of the time will be devoted to discussions and further demonstrations.

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Supporting research

Akimov, A., & Malin, M. (2020). When old becomes new: a case study of oral examination as an online assessment tool. Assessment & Evaluation in Higher Education, 45(8), 1205-1221.

Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62.

Berendt, B., Littlejohn, A., & Blakemore, M. (2020). AI in education: Learner choice and fundamental rights. Learning, Media and Technology, 45(3), 312-324.

Borsci, S., Malizia, A., Schmettow, M., Van Der Velde, F., Tariverdiyeva, G., Balaji, D., & Chamberlain, A. (2022). The Chatbot Usability Scale: the design and pilot of a usability scale for interaction with AI-based conversational agents. Personal and Ubiquitous Computing, 26, 95-119.

Chiu, T. K. (2021). A holistic approach to the design of artificial intelligence (AI) education for K-12 schools. TechTrends, 65(5), 796-807.

Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1-12.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642.

Hassoulas, A., Powell, N., Roberts, L., Umla-Runge, K., Gray, L., & Coffey, M. (2023). Investigating marker accuracy in differentiating between university scripts written by students and those produced using ChatGPT. Journal of Applied Learning & Teaching, 6(2).

Holstein, K., McLaren, B. M., & Aleven, V. (2019). Co-designing a real-time classroom orchestration tool to support teacher-AI complementarity. Grantee Submission.

Juarez Santiago, B., Olivares Ramirez, J. M., Rodríguez-Reséndiz, J., Dector, A., Garcia Garcia, R., González-Durán, J. E. E., & Ferriol Sanchez, F. (2020). Learning management system-based evaluation to determine academic efficiency performance. Sustainability, 12(10), 4256.

Khalil, M., & Er, E. (2023). Will ChatGPT get you caught? Rethinking of plagiarism detection. arXiv preprint arXiv:2302.04335.

Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M., Păun, D., & Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability, 13(18), 10424.

Lebovitz, S., Levina, N., & Lifshitz-Assaf, H. (2021). IS AI GROUND TRUTH REALLY TRUE? THE DANGERS OF TRAINING AND EVALUATING AI TOOLS BASED ON EXPERTS'KNOW-WHAT. MIS quarterly, 45(3).

Malinka, K., Peresíni, M., Firc, A., Hujnak, O., & Janus, F. (2023, June). On the educational impact of ChatGPT: Is Artificial Intelligence ready to obtain a university degree?. In Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 (pp. 47-53).

Mhlanga, D. (2023). Open AI in education, the responsible and ethical use of ChatGPT towards lifelong learning. Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning (February 11, 2023).

Nigam, A., Pasricha, R., Singh, T., & Churi, P. (2021). A systematic review on AI-based proctoring systems: Past, present and future. Education and Information Technologies, 26(5), 6421-6445.

Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning.

Wang, B., Rau, P. L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & information technology, 42(9), 1324-1337.

Williams, R., Ali, S., Devasia, N., DiPaola, D., Hong, J., Kaputsos, S. P., ... & Breazeal, C. (2023). AI+ ethics curricula for middle school youth: Lessons learned from three project-based curricula. International Journal of Artificial Intelligence in Education, 33(2), 325-383.

Villegas-Ch, W., Arias-Navarrete, A., & Palacios-Pacheco, X. (2020). Proposal of an Architecture for the Integration of a Chatbot with Artificial Intelligence in a Smart Campus for the Improvement of Learning. Sustainability, 12(4), 1500.

Villegas-Ch, W., Román-Cañizares, M., & Palacios-Pacheco, X. (2020). Improvement of an online education model with the integration of machine learning and data analysis in an LMS. Applied Sciences, 10(15), 5371.

Vincent-Lancrin, S., & Van der Vlies, R. (2020). Trustworthy artificial intelligence (AI) in education: Promises and challenges.

Zhang, H., Lee, I., Ali, S., DiPaola, D., Cheng, Y., & Breazeal, C. (2023). Integrating ethics and career futures with technical learning to promote AI literacy for middle school students: An exploratory study. International Journal of Artificial Intelligence in Education, 33(2), 290-324.

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Session specifications

Topic:
Emergent technologies
Grade level:
Community college/university
Skill level:
Beginner
Audience:
Principals/head teachers, Teachers, Teacher education/higher ed faculty
Attendee devices:
Devices useful
Attendee device specification:
Laptop: Chromebook, Mac, PC
Tablet: Android, iOS, Windows
Participant accounts, software and other materials:
None. The presenters will provide all links.
Subject area:
Math, Language arts
ISTE Standards:
For Education Leaders:
Equity and Citizenship Advocate
  • Cultivate responsible online behavior, including the safe, ethical and legal use of technology.
Empowering Leader
  • Support educators in using technology to advance learning that meets the diverse learning, cultural, and social-emotional needs of individual students.
For Educators:
Citizen
  • Mentor students in safe, legal and ethical practices with digital tools and the protection of intellectual rights and property.