MétaCan
Menu
Back to cohort

Serving Adult Learners From International Backgrounds at Two Canadian Universities

2020· book-chapter· en· W3098440046 on OpenAlexaffabout
Lorraine Carter, Alanna Carter

Bibliographic record

VenueAdvances in educational technologies and instructional design book series · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsToronto Metropolitan UniversityMcMaster University
Fundersnot available
KeywordsMainstreamContinuing educationFlexibility (engineering)DutyMedical educationUnit (ring theory)PedagogyAdult educationDistance educationClass (philosophy)PsychologySociologyMathematics educationPolitical scienceMedicineManagementComputer science

Abstract

fetched live from OpenAlex

McMaster University Continuing Education (Hamilton, Ontario) and the Real Institute in the Chang School, Ryerson University (Toronto, Ontario) are two university continuing education units that respond to the needs of adult learners from newcomer and international backgrounds. McMaster Continuing Education is known for its expertise in online education and support of adult learners as they seek professionally focused education. The Real Institute provides dedicated in-class programming and support strategies for younger adult learners. In this chapter, the experiences of older and younger adults from diverse cultural backgrounds studying at the two units are presented. The authors suggest that the needs of this learner group may be better met within the continuing education unit than within the mainstream academy. Innovative learning strategies and flexibility are key elements in this position. Finally, it is suggested that the two profiled units take their duty of care and commitment to student success seriously.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.586
Threshold uncertainty score0.823

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.003

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.

Opus teacher head0.015
GPT teacher head0.266
Teacher spread0.252 · 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 designQualitative
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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueAdvances in educational technologies and instructional design book seriesSame topicAdult and Continuing Education TopicsFrench-language works237,207