It’s What’s on the Inside That Counts: Analyzing Student Use of Sources in Composition Research Papers
Bibliographic record
Abstract
Objective – This study is designed to discover what kinds of sources are cited by composition students in the text of their papers and to determine what types of sources are used most frequently. It also examines the relationship of bibliographies to in-text citations to determine whether students “pad” their bibliographies with traditional academic sources not used in the text of their papers. Methods – The study employs a novel method grounded in multidisciplinary research, which the authors used to tally 1,652 in-text citations from a sample of 71 student papers gathered from English Composition II courses at three universities in the United States. These data were then compared against the papers’ bibliographic references, which had previously been categorized using the WHY Method. Results – The results indicate that students rely primarily on traditional academic and journalistic sources in their writing, but also incorporate a significant and diverse array of other kinds of source material. The findings identify a strong institutional effect on student source use, as well as the average number and type of in-text citations, which demographic characteristics do not explain. Additionally, the study demonstrates that student bibliographies are highly predictive of in-text source selection, and that students do not exhibit a pattern of “padding” bibliographies with academic sources. Conclusion – The data warrant the conclusions that an understanding of one’s own institution is vitally important for effective work with students regarding their source selection, and that close analysis of student bibliographies gives an unexpectedly reliable picture of the types and proportions of sources cited in student writing.
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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 | 0.010 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".