From Preservice to Practice: Expectations of/in the Secondary ELA Classroom
Bibliographic record
Abstract
The paper explores how preservice ELA teachers’ expectations of teaching compare to the reality of their experiences during the first year of teaching. The authors consider common concerns of beginning ELA teachers and their implications for teacher self-efficacy. The paper is informed by narrative research, which provides practical and specific insights into the lived experiences of participants. The first data set consists of reflective writings on a self-identified topic connected to ELA teaching and/or learning throughout the semester. Two, one-hour individual interviews conducted during the first year of teaching form the second data set. The paper provides empirical insights about how preservice experiences inform ELA teachers’ expectations of first-year teaching and their development of self-efficacy. Their two major concerns – classroom management and building rapport – identified their fears and insecurities about managing disruptive students and establishing connections with students. These struggles offer a connection between expectations, experiences and self-efficacy. Likewise, they point to the need for teacher education to address preservice teachers’ self-efficacy as a way to support their successful entry into the classroom. The paper includes implications for the development of increased opportunities to study and experience critical concerns of the profession. Such learning experiences offer preservice teachers meaningful opportunities to engage with experiential learning, applied practice and critical reflection before their first year in the field. The paper fulfills an identified need to study how differences between expectation and reality can be difficult for beginning ELA teachers to reconcile, a disconnect that lends itself to considerations of teachers’ self-efficacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".