Uncovering the Complexities in Writing from Sources from an Activity Theory Perspective: A Cross-Case Analysis of Chinese International Graduate Students in Education
Bibliographic record
Abstract
With a skyrocketing international student population from Asia at Canadian universities in recent decades, second language (L2) students’ abilities to adapt to the (inter)textual practices of their prospective discourse communities have received increased attention in L2 writing research. This thesis study aimed to uncover the complexities and heterogeneity inherent in L2 student writers’ uses of textual sources. Through a multi-case study design (Stake, 2006), I examined the textual borrowing practices of 3 first-year international graduate students from China studying Education at an English-medium university in Canada. Drawing on Engeström’s (2001) activity theory and Ivanič’s (1998, 2005) analytic framework of writers’ construction of identity, I answered 2 research questions: (1) What activity systems do students from China experience while learning to read and write in China and writing assigned papers for master’s courses in Education in Canada? and (2) What challenges do these students encounter while writing papers from sources and how do the students address these challenges, with what consequences in their writing and identities? The instruments for this multi-case study were learning history and text-based interviews with each student along with data from their written assignments and certain source texts, a learner profile questionnaire, and a reading-writing questionnaire. My analysis revealed tensions and contradictions within and between the students’ former literacy learning activity systems in China and their current writing-from-sources activity systems in Canada. These tensions and contradictions posed challenges for the students to (a) effectively process source information and accurately and appropriately present that information to demonstrate comprehension and critical thinking, evident in their patchwriting, direct copying, inappropriately quoting, transposing from Chinese sources, and paraphrasing abstracts as purported summaries of their own; (b) cultivate a genuine interest in what they wrote and manifest deep or extended learning in their writing, evident in their tendencies to cite secondary sources without reading the originals of those sources; and (c) take ownership of the knowledge co-constructed through dialogic interactions between the source authors and the students or accept their roles in shaping the double-voiced discourse in the process of writing despite their (imprecise) uses of quotations, paraphrases, summaries, and syntheses to do so.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".