Perceived impact of online written feedback on students’ writing and learning: a reflection

Abstract

In this reflective study, I perceive the impact of my own written feedback on students’ academic writing skills in particular and on learning in general. Anchored on Schon’s reflection-on-action (ROA) framework, my reflection arose from a content analysis of my written feedback on 80 student drafts and 44 feedback responses. I found that my written feedback is of two types: focus on form and focus on meaning. Coding the feedback led to an identification of six feedback functions: instructive/using imperatives (18.36%); suggestive (15.31%); asking questions/probing (23.98%); stating a personal opinion (6.12%); corrective (29.59%); and affirming/negating (6.63%). The categorisation of feedback according to these functions was influenced by Wolsey’s feedback functions (2008) which was adapted by Alvarez, Espasa and Guasch. Results revealed that I employ corrective feedback, probing questions and instructive feedback more frequently than suggestive feedback, personal statement or affirmation/negation. I also found that my feedback on form (59%) is higher than my feedback on meaning (41%). I explain the relationship of these findings by identifying some confounding factors that enabled me to interrogate my assumptions, along with a discussion of their implications.

Keywords:

• Reflection
• online written feedback
• feedback types
• feedback functions
• learner dependence
• learning autonomy

Notes

1. In Singapore, academics who are teaching in the university are called lecturers. However, in this paper, lecturers and teachers mean the same.

2. Learning advisors provide English language and statistics assistance to students at JCU Singapore. Although different from lecturers in terms of job scope, they support lecturers in helping students achieve academic success through online written feedback, face-to-face consultations, workshops and just-in-time teaching (see Context section below).

3. JCU Singapore has acquired a license to use Qualtrics as a survey platform.

4. Leximancer is software that allows researchers to map themes, concepts and their associated relationships from a body of text. It is a concept mining tool ‘offering objective, actionable insight in the form of visually compelling concept maps and dashboard reports’ (Pacific Transcription, 2016, ‘Using Leximancer for Qualitative…’).