The Role of AI, Blockchain, Cloud, and Data (ABCD) in Enhancing Learning Assessments of College Students

Abstract

Purpose: This study attempts to examine how ABCD (Artificial Intelligence, Blockchain, Cloud, and Data) technologies influence postsecondary learning measurements. It specifically examines students' beliefs, behavior, and action intentions, and how the ABCD technologies impact customized learning, academic integrity, collaboration, and belief in grading.

Study design/methodology/approach: A quantitative design was applied with a structured survey distributed to university students. Statistical tests of correlation and regression tests were carried out to test the relationships between Perceived Usefulness (PU), Perceived Ease of Use (PEU), and Behavioral Intention (BI) in the adoption of ABCD technologies.

Findings: Results did not imply a strong correlation between Perceived Usefulness, Perceived Ease of Use, and Behavioral Intentions, stating students' adoption of ABCD technologies is less likely to be accounted for by individual factors, i.e., institutional support, infrastructure, and faculty participation. Although students are aware of potential benefits of ABCD technologies in terms of enhancing assessment efficiency and security, concerns over fairness, usability, and engagement remain barriers to greater adoption.

Originality/value: The present research adds to the Technology Acceptance Model (TAM) and Constructivist Learning Theory (CLT) by emphasizing the role of context and institutional drivers in the adoption of technology. It presents pragmatic advice to educational institutions for improving faculty development, digital infrastructure, and policy mechanisms for efficient and moral utilization of ABCD technology in assessment in learning.