Effects of self-assessment diaries on academic achievement, self-regulation, and motivation

ABSTRACT

Although students who self-assess effectively often learn better, creating effective, low-cost interventions to help them do so is a critical challenge. This study examined the effects of a self-assessment diary intervention on 74 Form 1 (M_age = 12.2 years) students’ academic achievement, self-regulation, and motivation. After each homework assignment, students in the experimental group (n = 37) completed a standardised self-assessment diary, while students in the control group (n = 37) did no additional work. Difference-in-differences analyses showed that self-assessment diaries significantly enhanced students’ academic achievement, self-efficacy, and intrinsic value. Students with lower past achievement benefited more than other students from the intervention. The intervention had no significant impact on effort regulation and self-reflection. Furthermore, effort-regulation, self-reflection, self-efficacy, and intrinsic value all did not mediate the link between self-assessment diaries and academic achievement. The findings can inform researchers and educators aiming to help students self-assess effectively to improve their learning.

KEYWORDS:

• Self-assessment
• diary
• self-regulation
• motivation
• learning intervention

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed here.

Notes

1. Effect sizes can be calculated from qualitative data as long as that data is processed quantitatively. For instance, data collected with observations (qualitative data) could be used to calculate frequencies and then run quantitative analysis (e.g., t tests).

Additional information

Funding

This work was supported by a Research Cluster Fund 2017/2018 from the Education University of Hong Kong [Project No.: RG 51/2017-2018R].

Notes on contributors

Zi Yan

Zi Yan is an Associate Professor in the Department of Curriculum and Instruction at The Education University of Hong Kong. His main publications and research interests focus on two related areas, i.e., educational assessment in the school and higher education contexts with an emphasis on student self-assessment; and Rasch measurement, in particular its application in educational and psychological research.

Ming Ming Chiu

Ming Ming Chiu is Chair Professor of Analytics and Diversity at The Education University of Hong Kong. He invented (a) artificial intelligence Statistician, (b) statistical discourse analysis (SDA) to model online and face-to-face conversations, (c) multilevel diffusion analysis (MDA) to detect corruption in the music industry, and (d) online detection of sexual predators. He studies inequalities, culture, and learning in 65 countries, and automatic statistical analyses.

Po Yuk Ko

Po-yuk Ko is Professor (Practice) at the Department of Curriculum and Instruction, and Director of the Centre for Excellence in Learning and Teaching, The Education University of Hong Kong. Her research interests include Learning Studies, teacher professional development, and language education. She established a research network in Hong Kong and a number of overseas universities on Learning Study.