Beyond Self-Reports: Addressing Bias and Improving Data Quality in Educational Research


AKBULUT Y.

JOURNAL OF MEASUREMENT AND EVALUATION IN EDUCATION AND PSYCHOLOGY-EPOD, cilt.16, sa.2, ss.116-124, 2025 (ESCI, TRDizin) identifier

Özet

The use of self-report in educational research has facilitated data collection by enabling quick access to diverse populations. However, research indicates that these opportunities accompanied by significant challenges. From inadequate response efforts to culturally influenced answers, numerous issues can undermine the validity of research findings. Discrepancies between self-reports and objective data often reveal underlying biases. Poor data quality - exacerbated by social desirability in sensitive constructs, individual and environmental factors, and changes in scale structure - has underscored the limitations of current methods which may reduce generalisability and contribute to the replicability crisis. However, these limitations can also lead to opportunities for improving both survey design and data interpretation. Our experiences highlight the need to integrate multiple data sources, enhance survey development and adaptation practices, and make greater use of true experimental studies. By reflecting on these challenges, we propose new directions for survey implementation in educational research to improve the reliability and replicability of our findings while deepening our understanding of complex human