Exploring the potential of process-tracing technologies to support assessment for learning of L2 writing
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Assessment for learning (AfL) seeks to support instruction by providing information about students’ current state of learning, the desired end state of learning, and ways to close the gap. AfL of second-language (L2) writing faces challenges insofar as feedback from instructors tends to focus on written products while neglecting most of the processes that gave rise to them, such as planning, formulation, and evaluation. Meanwhile, researchers studying writing processes have been using keystroke logging (KL) and eye-tracking (ET) to analyze and visualize process engagement. This study explores whether such technologies can support more meaningful AfL of L2 writing. Two Chinese L1 students studying at a U.S. university who served as case studies completed a series of argumentative writing tasks while a KL-ET system traced their processes and then produced visualizations that were used for individualized tutoring. Data sources included the visualizations, tutoring-session transcripts, the participants’ assessed final essays, and written reflections. Findings showed the technologies, in combination with the assessment dialogues they facilitated, made it possible to (1) position the participants in relation to developmental models of writing; (2) identify and address problems with planning, formulation, and revision; and (3) reveal deep-seated motivational issues that constrained the participants’ learning.
This is a manuscript of an article published as Ranalli, Jim, Hui-Hsien Feng, and Evgeny Chukharev-Hudilainen. "Exploring the potential of process-tracing technologies to support assessment for learning of L2 writing." Assessing Writing 36 (2018): 77-89. DOI: 10.1016/j.asw.2018.03.007. Posted with permission.