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Record W1552784665

Experimenting with Problem-Based Learning in Constitutional Law

2002· article· en· W1552784665 on OpenAlexaboutno aff
Barbara J. Flagg

Bibliographic record

VenueOpen Scholarship Institutional Repository (Washington University in St. Louis) · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsLawConstitutional lawPolitical scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Problem-based learning (PBL), first developed for use in a professional setting at McMaster University in Ontario, Canada in the 1960s, is an approach to adult education that has gained widespread acceptance in medical education, most notably in the United States at Harvard Medical School. The goal of PBL is to develop students’ skills at “clinical reasoning” and “self-evaluation and study.” In other words, the problem-based approach emphasizes applied knowledge and aspires to help students learn how to learn. In the spring semester of 2001, I adopted a variant of the PBL approach in my Constitutional Law II course, which covers the Fourteenth Amendment and is an elective open to second- and third-year law students. In the body of this Essay, I first elaborate the concerns that led me to tinker with, and eventually abandon, the Socratic method of teaching in Constitutional Law II. I next briefly describe the various active learning techniques I tried before settling on PBL, and assess them from the standpoint of the concerns that led me to them. Finally, I provide a detailed account of my semester with PBL, and analyze its successes and failures in light of its own internal objectives as well as my and my students’ concerns and goals.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.006
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.315
Teacher spread0.261 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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