Maintaining Assessment Validity in the GenAI Era: Insights from Human-Machine Interaction

Generative Artificial Intelligence (GenAI) has been altering the way that educational institutions and businesses operate. Leveraging the significant opportunities of GenAI and addressing its challenges are essential for institutions to maintain the competitiveness of their graduates and educational processes. For a few decades now, human-machine interaction scholars have been investigating how humans can properly utilise machine capabilities without over-reliance. Building on these insights, this paper proposes a framework for maintaining the effectiveness of higher education assessments amid the pervasive use of GenAI. The framework incorporates these insights into its five interconnected components: assessment design, establishing an understanding of purpose and process, effective monitoring, feedback, and reflection and planning for change. The framework allows for creating the environment and culture for the responsible use of GenAI while ensuring education quality and imposing academic integrity. We present two case studies to demonstrate the applicability of the proposed framework to diverse educational requirements. Our findings demonstrate how the framework facilitates fostering student creativity while maintaining confidence in the validity of the assessment system.

Authors

Institutions

Publication Details

Published
2025-07-30
DOI
https://doi.org/10.1109/istem-ed65612.2025.11129292
Primary Topic
Advanced Data Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Maintaining Assessment Validity in the GenAI Era: Insights from Human-Machine Interaction

Aya Hussein
Advanced Data Processing Techniques
article

Maintaining Assessment Validity in the GenAI Era: Insights from Human-Machine Interaction

Aya Hussein
article en

Abstract

Generative Artificial Intelligence (GenAI) has been altering the way that educational institutions and businesses operate. Leveraging the significant opportunities of GenAI and addressing its challenges are essential for institutions to maintain the competitiveness of their graduates and educational processes. For a few decades now, human-machine interaction scholars have been investigating how humans can properly utilise machine capabilities without over-reliance. Building on these insights, this paper proposes a framework for maintaining the effectiveness of higher education assessments amid the pervasive use of GenAI. The framework incorporates these insights into its five interconnected components: assessment design, establishing an understanding of purpose and process, effective monitoring, feedback, and reflection and planning for change. The framework allows for creating the environment and culture for the responsible use of GenAI while ensuring education quality and imposing academic integrity. We present two case studies to demonstrate the applicability of the proposed framework to diverse educational requirements. Our findings demonstrate how the framework facilitates fostering student creativity while maintaining confidence in the validity of the assessment system.

University of Canberra (AU)
Openalex Percentile: Top 73%
Advanced Data Processing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Maintaining Assessment Validity in the GenAI Era: Insights from Human-Machine Interaction — Aya Hussein · (2025) | TGRS Research Map | TGRS