Writing-Based Learning Analytics for Education

Abstract

Computer-driven analytics are becoming increasingly essential to various disciplines. Written language in particular has received a great deal of attention, and many tools now exist to gather information about compositions. This research has resulted in Internet search programs, translators, and computerized narrators. However, analytics have yet to be rigorously applied to the field of academic writing. Within this specialized area, there are many prospects for how analytics may be applied. These details, however, first require definitions of analytics and writing analytics in particular, consideration on how they may be used, and the tools available for their collection and implementation.

Review of Research on the Use of Information and Communication Technologies (ICTs) in ELT-related Academic Writing Classrooms

“…This writing strategy tool also has the capacity to automatically score and evaluate students' written pieces and provide them with formative feedback by using text analysis tools such as Coh-Metrix which explores the cohesive features of a text. Mi-Writer is another learning analytic tool that has the potential to capture data in the recursive process of writing (planning, composing, reviewing, editing), plus giving feedback and recording the students' writing performance, behavior and interaction with peers and teachers in real-time which can open the possibility of facilitating automated real-time feedback that is tailored to the individual learners' performances and abilities (Clemens et al, 2013). Criterion, a commercial writing evaluation tool developed by Educational Testing Service (ETS), also provides holistic scores and detailed diagnostic trait feedback on the students' written texts based on level-specific models considering both the age and proficiency levels of the learners as well as some essay planning tools and reference handbooks to assist the learners in understanding and evaluating the feedback provided, which is an invaluable asset for ESL/EFL learners.…”

Text mining in education

“…It is vital to provide analytics to instructors for improving the educational environment and providing feedback to students continually (Dzikovska et al, ; Lyons, Aksayli, & Brewer, ). In this context, the ETM methods have been adopted to extract information from activities such as writing production (Clemens, Kumar, & Mitchnick, ) and forum/chat/e‐mail interactions (Aghaee, ; Ferguson & Shum, ). The majority of the applications extract information that could potentially help the instructor to analyze the students' performance and behavior.…”