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Record W2737880791

Teaching Matters: Developing Teaching Dossiers to Showcase Teaching Success and Competency

2017· article· en· W2737880791 on OpenAlexaff
Danielle Brewer‐Deluce, Candace J. Gibson

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsWestern University
Fundersnot available
KeywordsExcellencePromotion (chess)PsychologyPresentation (obstetrics)Quality (philosophy)Medical educationPedagogyPolitical scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

Throughout academia, the value of developing a strong CV is pervasive, while teaching dossiers can be overlooked. Furthermore, though partaking in a teaching assistantship is often required, graduate teaching assistants (GTAs) are not always mentored in developing teaching-related skills, or in understanding their importance in future career success. Considering that the skills GTAs gain through teaching contribute significantly to their development of discipline-based expertise and presentation skills (Seldin et al., 2010), and that faculty appointments typically include a 40% teaching load, it is apparent that this problem poses a major challenge. GTAs and junior faculty are often unsure how to articulate and qualify their teaching experience, and appointment committees seeking demonstrated skill and excellence can not find adequate evidence. Finally, in an era of increased focus on research skills and productivity over teaching, it is increasingly important to find ways to promote a campus culture that is supportive of teaching. Fortunately, well-defined teaching philosophies support students, faculty and administrators in viewing teaching as a valuable scholarly activity, and promote a deep commitment to teaching as well as professional and personal growth (Goodyear & Allchin, 1998).\nTeaching dossiers offer an opportunity to convey a teaching philosophy by cataloguing concrete evidence and accomplishments supporting the scope and quality of teaching experience (Sidhu, 2015). The development process itself is useful for promoting self-reflection and growth (Foote & Vermette, 2001; Sidhu, 2015), as well as enhancing the quality of teaching (Sidhu, 2015), while the final product is a necessary portion of academic hiring/promotion decisions (Seldin et al., 2010). This workshop seeks to support participants in (1) understanding the importance of teaching and creating early career dossiers (Foote and Vermette, 2001); and (2) outlining teaching dossier content and structure (Foote and Vermette, 2001; Seldin, Miller, and Seldin, 2010; Sidhu, 2015) while focusing on critical reflective activities (Sidhu, 2015)to promote dossier content generation.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.038
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0050.004
Scholarly communication0.0080.008
Open science0.0020.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0220.010

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.

Opus teacher head0.226
GPT teacher head0.451
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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