Deepening source criticism in higher education to avoid plagiarism
Bibliographic record
Abstract
This is a presentation made during the pedagogical conference NU2020 (7-9 October 2020)What should teachers do with Wikipedia? Many students at the university do not really know how to find relevant information and cite important sources in their field. On the one hand, the challenge is even more difficult in language courses as the students focus on skills without paying attention to source information. In this perspective, they get used to plagiarism attitudes consisting in patchwriting strategies (Pecorari, 2015). On the other hand, teachers do not have time to help students to find the required information, they take this competency for granted in higher education. This contrast can reinforce misunderstandings between students and teachers and lead to a form of passive plagiarism, where students seek for information and gather different meanings taken in different sources. This mimetic attitude has to be questioned at the very beginning of the academic life (Krathwohl, 2002). By preparing students to a better reflection on their sources and by inviting teachers to pay attention to source criticism, a generic form of “constructive alignment” is possible (Hunt, Chalmers, 2012). The presentation proposes an exercise to test the critical capacity of students when it comes to the use of Wikipedia sources. The experiment was made during three semesters in a class of French (“Culture and society in France”) where the students had to study different materials including some Wikipedia articles recommended by the teacher (Premat, 2019). When they wrote the exam, they had to answer a metalinguistic question on the use of Wikipedia articles. The presentation analyzes the answers of the students by proposing a typology of discourses and attitudes on Wikipedia sources.There is a paradox between students’ practices (almost all of them recognize that they use Wikipedia) and between the discourse that they have (most of them would not dare citing a Wikipedia article in an academic essay). The presentation proposes pedagogical activities where students would be encouraged to deepen source criticism (Peters, Cadieux, 2019; Premat, 2020). -Hunt, L., Chalmers, D. (eds.) (2012). University teaching in focus: a learning-centred approach. Abingdon, Oxon: Routledge.-Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: an overview. Theory into practice, vol. 41, n. 4, 212-218.-Pecorari, D. (2015). Plagiarism in second language writing: Is it time to close the case? Journal of Second Language Writing, 30, pp. 94-99.-Peters, M., Cadieux, A. (2019). Are Canadian professors teaching the skills and knowledge students need to prevent plagiarism?. International Journal of Educational Integrity 15, 10 (2019). https://doi.org/10.1007/s40979-019-0047-z (See a summary in Aktuell högskolepedagogisk forskning, 1, 2020, https://su.powerinit.com/Modules/Campaign/Newsletter.aspx?n=7745&e=christophe.premat@su.se&r=372722&h=FE54B47668C0493D5A6BED122B73BBC4)-Premat, C. (2019). Hur kan man lära studenter att undvika plagiering? Figshare. Paper. DOI: https://doi.org/10.17045/sthlmuni.7850993.v1-Premat, C. E. (2020). Wikipedia Practices, Quick Facts, and Plagiarism in Higher Education. In E. Ezza, & T. Drid (Eds.), Teaching Academic Writing as a Discipline-Specific Skill in Higher Education (pp. 199-221). Hershey, PA: IGI Global. https://doi:10.4018/978-1-7998-2265-3.ch009
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | Research integrity Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.019 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".