Automated writing evaluation (AWE) feedback: a systematic investigation of college students' acceptance. Issue 9 (8th December 2022) - Zhai, Na; Ma, Xiaomei
Abstract: Automated writing evaluation (AWE) has been used increasingly to provide feedback on student writing. Previous research typically focused on its inter-rater reliability with human graders and validation frameworks. The limited body of research has only discussed students' attitudes or perceptions in general. A systematic investigation of the driving factors contributing to students' acceptance is still lacking. This study proposes an extended technology acceptance model (TAM) to identify the environmental, individual, educational, and systemic factors that influence college students' acceptance of AWE feedback and examine how they affect college students' usage intention. Structural equation modeling (SEM) was used to analyze the quantitative survey data from 448 Chinese college students who had used AWE feedback for at least one semester. Results revealed that students' behavioral intention to use AWE feedback was affected by the subjective norm, facilitating conditions, perceived trust, AWE self-efficacy, cognitive feedback, and system characteristics. Among them, subjective norm, perceived trust, and cognitive feedback positively influenced perceived usefulness; facilitating conditions, AWE self-efficacy, and system characteristics were significant determinants of perceived ease of use; anxiety played no role for experienced users. Implications from these findings to AWE developers and practitioners are further elaborated.