Analysis of portfolio assessment as pedagogy in technical writing instruction
Bibliographic record
Abstract
Portfolio assessment-as-pedagogy, as implemented in a college writing course, is examined in light of the themes present in the literature concerning portfolio assessment. The instructional processes used in English 155, Scientific and Technical Writing, at Lethbridge Community College, are described; and ten students' portfolios are analyzed, with primary emphasis on students' learning as expressed in their final reflective letters. Consideration is also given to their reflection worksheets and to drafts and revisions of individual projects. Together, these documents reveal the students' insights into their development as writers and into the significance of their writing products. Grounded in a constructivist view of learning, a portfolio classroom fosters social construction of knowledge. When students develop a sense of community, their participation in collaborative writing and peer revision can become an important part of composing. Because portfolios are informed by process theory of composition, they are not only a means of assessing writing, but they also guide student learning by documenting their writing processes and giving them a voice in interpreting their development. This reflection helps students identify themselves as writers who have ownership over their work and their learning. Portfolios also give the instructor a window into students' rhetorical awareness, perceptions of thinking and writing, and sentence skill development. Although this project was limited to one course, the depth of learning demonstrated by the students suggests that they may benefit from increased power in creating and assessing their portfolios. Other future possibilities include collaborative assessment among writing instructors and program-wide applications of portfolio assessment.
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".