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Record W2126916152 · doi:10.1002/meet.14504701439

What do LIS faculty need for professional development?

2010· article· en· W2126916152 on OpenAlexaboutno aff
Trudi Bellardo Hahn, June Lester

Bibliographic record

VenueProceedings of the American Society for Information Science and Technology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
FundersPenn State College of Medicine
KeywordsCaucusProfessional developmentFaculty developmentContinuing professional developmentMedical educationProfessional associationPsychologyPublic relationsMedicinePolitical science

Abstract

fetched live from OpenAlex

Abstract Although there are some reports of research and activities related to professional development and continuing education for faculty in other fields, no such study has been conducted in the information field. Therefore a survey was conducted in the spring of 2010, for the purposes of (1) determining the professional development needs of faculty in schools of library and information studies in the U.S. and Canada, (2) determining whether support mechanisms and activities to meet these needs are available in the schools or the universities that employ these faculty, and (3) identifying other sources of professional development on which faculty rely. Data were obtained via an anonymous online survey of the full‐time faculty members in the schools. Among the findings were that professional development needs and preferences are significantly different for faculty in traditional library schools compared to those faculty whose schools are members of the iSchool Caucus. In general, opportunities for development and training are much more prevalent at the university level than at the school level. Results of this study will inform enhancement of professional development activities by the schools, the host universities, and professional associations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0020.004
Scholarly communication0.0010.029
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.311
Teacher spread0.297 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2010
Admission routes1
Has abstractyes

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