International Journal of Algorithms Design and Analysis Review Review Article

Enhancing ABET Summative Direct Assessment with AI and Blockchain: A Framework for Personalized Learning and Secure Evaluation

  1. Qutaiba I. Ali Faculty Member, Department of Computer Engineering, Mosul University

Abstract

Accreditation Board for Engineering and Technology (ABET) emphasizes the achievement of specific measurable learning outcomes. However, conventional assessment methods often find it challenging to accurately capture the complexities of student learning and program effectiveness within the ABET framework. This study proposes a novel framework that enhances ABET summative direct assessment by integrating a carefully structured, weighted assessment system with the transformative potential of artificial intelligence (AI) and blockchain technologies. The framework leverages AI to personalize learning pathways, automate feedback generation, and drive data-driven curriculum improvement, while blockchain technology ensures secure data management, transparent grade recording, and verifiable student credentials. By grounding this integration in sound pedagogical principles and addressing ethical considerations, the proposed framework aims to create a more efficient, trustworthy, and learner-centric assessment experience that empowers both students and educators to achieve better learning outcomes. This study also describes the roadmap of the integration of AI and blockchain technologies with the ABET assessment framework which involves the examination of the practicality, efficiency, and impact of these technologies at different stages of the assessment process. Another contribution is to identify and recommend the most suitable AI and blockchain tools for effective implementation in ABET assessment. This involves a comparative analysis of available technologies, considering factors such as compatibility with ABET principles, data security, and the potential to enhance transparency, efficiency, and personalization in student assessments. We aim to reinforce the proposed approach by harnessing modern technologies in AI and advanced security measures to enhance the effectiveness, efficiency, and security of our proposed assessment framework.

Keywords

References (23)

  1. Ali QI. Surveying Different Student Outcome Assessment Methods for ABET Accredited Computer Engineering Programs. Research Reports on Computer Science. 2023:56-76. doi:10.37256/rrcs.2120232577
  2. Bachnak R, Marikunte S, Abu-Ayyad M, Shafaye A. Fundamentals of ABET Accreditation with the Newly Approved Changes. 2019 ASEE Annual Conference & Exposition Proceedings. doi:10.18260/1-2--32868
  3. Osman A, Yahya AA, Kamal MB. A Benchmark Collection for Mapping Program Educational Objectives to ABET Student Outcomes: Accreditation. Advances in Intelligent Systems and Computing. 2018:46-60. doi:10.1007/978-3-319-78753-4_5
  4. Cook C, Mathur P, Visconti M. Assessment of CAC self-study report. 34th Annual Frontiers in Education, 2004. FIE 2004. Savannah, GA: IEEE; 2004. p.T3G/12-T3G/17. DOI: 1109/FIE.2004.1408546.
  5. Department of Computer Science, Faculty of Computing and Information Technology King Abdulaziz University, Saudi Arabia, Hussain Khan I. A Unified Framework for Systematic Evaluation of ABET Student Outcomes and Program Educational Objectives. International Journal of Modern Education and Computer Science. 2019;11(11):1-6. doi:10.5815/ijmecs.2019.11.01
  6. Ahmad N, Qahmash A. Implementing fuzzy AHP and FUCOM to evaluate critical success factors for sustained academic quality assurance and ABET accreditation. PLOS ONE. 2020;15. DOI: 1371/journal.pone.0239140. PubMed: 32941488.
  7. Alhakami HH, Al-Masabi BA, Alsubait TM. Data Analytics of Student Learning Outcomes Using Abet Course Files. Advances in Intelligent Systems and Computing. 2020:309-325. doi:10.1007/978-3-030-52249-0_22
  8. Dawood MUZ, Buragga KA, Khan AR, Zaman N. Rubric based assessment plan implementation for Computer Science program: A practical approach. Proceedings of 2013 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE). 2013:551-555. doi:10.1109/tale.2013.6654498
  9. Schoepp K, Danaher M, Kranov AA. The computing professional skills assessment: An innovative method for assessing ABET's student outcomes. 2016 IEEE Global Engineering Education Conference (EDUCON). 2016:45-52. doi:10.1109/educon.2016.7474529
  10. Hussain W, Spady WG, Naqash MT, Khan SZ, Khawaja BA, Conner L. ABET Accreditation During and After COVID19 - Navigating the Digital Age. IEEE Access. 2020;8:218997-219046. doi:10.1109/access.2020.3041736
  11. Karimi A, Manteufel R. Preparation of Documents for ABET Accreditation During the COVID-19 Pandemic. ASEE 2021 Gulf-Southwest Annual Conference Proceedings. doi:10.18260/1-2--36394
  12. Mohamed O, Bitar Z, Abu-Sultaneh A, Elhaija WA. A simplified virtual power system lab for distance learning and ABET accredited education systems. International Journal of Electrical Engineering & Education. 2021;60(4):397-426. doi:10.1177/0020720921997064
  13. Essa E, Dittrich A, Dascalu S. ACAT: A Web-Based Software Tool to Facilitate Course Assessment for ABET Accreditation. 2010 Seventh International Conference on Information Technology: New Generations. 2010:88-93. doi:10.1109/itng.2010.224
  14. Lam WWM, Xie H, Liu DYW, Yung KWH. Investigating Online Collaborative Learning on Students' Learning Outcomes in Higher Education. Proceedings of the 2019 3rd International Conference on Education and E-Learning. 2019:13-19. doi:10.1145/3371647.3371656
  15. Cabezas I. On combining gamification theory and ABET criteria for teaching and learning engineering. IEEE Frontiers in Education Conference (FIE). El Paso, TX: IEEE; 2015. p.1-9. DOI: 1109/FIE.2015.7344111.
  16. McKenzie FD, Mielke RR, Leathrum JF. A successful EAC-ABET accredited undergraduate program in modeling and simulation engineering (M&SE). 2015 Winter Simulation Conference (WSC). 2015:3538-3547. doi:10.1109/wsc.2015.7408513
  17. Peridier V. A Faculty-directed Continuous Improvement Regimen with Intentional ABET/SO 1-7 Scaffolding. 2020 ASEE Virtual Annual Conference Content Access Proceedings. doi:10.18260/1-2--34000
  18. Zambrano C. Continuous improvement model to systematize curricular processes in the context of ABET accreditation. In: Arabnia H, Deligiannidis L, Tinetti FG, Tran QN, editors. Proceedings of the International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS). Las Vegas: CSREA Press; 2019. p.88–93.
  19. G.A. R, P S, T.G. G. Developing a knowledge structure using Outcome based Education in Power Electronics Engineering. Procedia Computer Science. 2020;172:1026-1032. doi:10.1016/j.procs.2020.05.150
  20. Methodologies and Outcomes of Engineering and Technological Pedagogy. Advances in Educational Technologies and Instructional Design. 2020. doi:10.4018/978-1-7998-2245-5
  21. Manzoor A, Aziz H, Jahanzaib M, Wasim A, Hussain S. Transformational model for engineering education from content-based to outcome-based education. International Journal of Continuing Engineering Education and Life-Long Learning. 2017;27(4):266. doi:10.1504/ijceell.2017.087136
  22. Min B, Ross H, Sulem E, Veyseh APB, Nguyen TH, Sainz O, et al. Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey. ACM Computing Surveys. 2023;56(2):1-40. doi:10.1145/3605943
  23. AYDIN Ö. Google Bard Generated Literature Review: Metaverse. Journal of AI. 2023;7(1):1-14. doi:10.61969/jai.1311271