Evaluation of Digital Feedback Tools in Writing Tutorials: A Step Towards Inclusion and Critical Literacy

Abstract

This study analyzes the use of digital tools employed in academic writing tutorials with a threefold aim: to determine the extent to which they promote inclusive practices, to categorize the types of feedback they offer according to inclusion criteria, and to assess how they contribute to the development of critical literacy. To this end, a corpus of 21 tools was examined, to which six criteria were applied to measure the degree of inclusion (CEDEC and INTEF, 2019) and seven indicators to describe how they contribute to the development of critical literacy (Cassany, 2021).

The results reveal variability in the degree of compliance with the inclusion criteria. Interactivity and accessibility of textual content are the most highly rated criteria, which means that these tools make content accessible to students with cognitive diversity. However, adaptability and interaction received low ratings, evidencing a lack of mechanisms to personalize learning and offer intuitive communication. In terms of the comparative description of the type of feedback offered by the tools, while static formative documents proved to be the least inclusive, bibliographic management platforms and information search tools show moderate capacity due to their specialized focus. In contrast, Artificial Intelligence (AI) assistants, such as ChatGPT, achieved the highest levels of inclusion thanks to their ability to generate elaborate and personalized feedback. However, it was found that many non-formative tools continue to prioritize superficial technical correction over the writing process.

The conclusions indicate that, despite advances toward inclusion in the design of digital tools, there is still a gap between the available technology and the implementation of truly adaptive processes aligned with Universal Design for Learning (UDL). With regard to critical literacy, it is emphasized that the tool alone is not enough; instructional support is essential to guide students toward ethical, reflective, and metacognitive use of technology, especially in light of the rise of AI, whose guided, supervised, and educational access is necessary to ensure such formative use. In this way, literacy as the ability to understand, produce, and transform texts in multimodal and digital environments will be a true driver of inclusion.

The study has limitations due to the small sample size, so it is recommended that the research be replicated in new contexts beyond peer academic tutoring, and with a wider range of tools to validate the current findings. In terms of future lines of research, it is a priority to design pedagogical scaffolds that guide the educational use of artificial intelligence. It is also essential to explore in greater depth how the volume of feedback influences students' self-regulation and co-regulation processes, specifically in scenarios where direct intervention by the tutor is limited.