Learning to write syntheses : the effect of process feedback and of observing models on performance and process behaviors
Writing a synthesis text involves interacting reading and writing processes, serving the comprehension of source information, and its integration into a reader-friendly and accurate synthesis text. Mastering these processes requires insight into process’ orchestrations. A way of achieving this is via process feedback in which students compare their process orchestration with examples. Access to such examples of enacted process orchestration models might have an additional learning effect. In the present study we replicated and extended the study of Vandermeulen et al. (Written Communication, 40(1), 90–144, 2023) on the effect of keystroke logging data-based process feedback with feed-forward exemplars when compared to national baseline performances. In addition, we report the effect of a brief extension in which learners had the opportunity to observe an enacted model of their choice, showing one of three orchestrations of the initial stage of writing a synthesis task. A total of 173 10th—grade students were randomly assigned to a process feedback condition with or without added models. A baseline, consisting of a nationally representative sample of upper-secondary students’ texts and processes, served as an alternative control group. Results showed that the process feedback, both with and without observation, had a significant effect on text quality. Regarding the process data, students in the feedback condition had a more prominent focus on the sources as they spent more time in them and switched more often between text and sources, compared to the baseline. The observation task magnified this effect.
Source (journal)
Reading and writing. - Dordrecht, 1989, currens
Dordrecht : 2023
0922-4777 [print]
1573-0905 [online]
(2023) , p. 1-31
Full text (Publisher's DOI)
Full text (open access)
Research group
Publication type
Publications with a UAntwerp address
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Creation 07.11.2023
Last edited 08.11.2023
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