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Record W2018508070 · doi:10.1002/nha3.10117

Evaluation of Adult Learners: Ethical Issues

2000· article· en· W2018508070 on OpenAlexaff
Jean L. Crowe

Bibliographic record

VenueNew Horizons in Adult Education and Human Resource Development · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsUniversity of the Fraser Valley
Fundersnot available
KeywordsCredibilityCurriculumEthical issuesQuality (philosophy)Assessment for learningPsychologyComputer scienceEngineering ethicsPedagogyFormative assessmentPolitical scienceEngineering

Abstract

fetched live from OpenAlex

In this article, the author presents an overview of the different types of evaluation, or assessment, typically used in college and university settings. Three ethical issues commonly identified when evaluating adult learners are discussed: learner readiness, evaluation credibility, and the power issue. Learner‐centred or collaborative programs are suggested as the type of learning experience that could best resolve the ethical dilemmas when assessing adults. As more and more adults are returning to the classroom, the question of how to provide meaningful evaluation is a challenge facing many educators. Increasing numbers of adult learners are demanding a high quality learning experience, including assessments that are appropriate to their needs. An examination of the various styles of evaluation available will provide insight into how facilitators can make such changes in their curricula. In this article, I will describe the methods of evaluation typically used to assess adult learners in self‐directed learning (SDL) and in teacher‐directed learning (TDL) situations. Some advantages and disadvantages of each method will be stated, followed by a description of selected ethical issues associated with evaluation in each case. I will also discuss the middle ground between SDL and TDL. In my opinion, this middle ground, often called learner‐centred and collaborative learning, is becoming popular in institutional programs. I will examine the possibility that evaluation techniques in this middle zone may act to resolve some ethical dilemmas of assessing adults.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.090
GPT teacher head0.452
Teacher spread0.362 · 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 teacher head, not a consensus.

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

Citations5
Published2000
Admission routes1
Has abstractyes

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