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Record W1536224405

Tutorless PBL Groups in a Medical School

2006· article· en· W1536224405 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAcademic exchange quarterly · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsnot available
Fundersnot available
KeywordsProblem-based learningContext (archaeology)Medical educationMedical schoolPsychologyComplaintMedicineMathematics education
DOInot available

Abstract

fetched live from OpenAlex

Abstract Problem-based learning (PBL) has become a popular teaching method in medical schools because of its emphasis on developing problem solving skills as well as delivering course content. Typically PBL depends on the availability of significant numbers of faculty to function as small group and is therefore very resource intensive. This study compared achievement of content knowledge and student satisfaction in tutorless and physician facilitated small groups in a 2nd year medical school course, and found no significant difference in these areas between the two groups. The one significant difference found was that students in groups with tutors worked longer than those without tutors. Introduction Problem-based learning (PBL) was introduced into medical education in the 1960's at McMaster Medical School in Ontario, Canada. For years, there had been concerns by medical school professors about the overuse of lectures. It was believed that students were too passive and that the lecture method was ineffective. Studies have shown that medical students forget much of what they have memorized from lectures before they reach their clinical years (Woods, 1993). Woods also found another complaint to be that medical students were not being trained as critical thinkers or problem solvers and that they were unable to apply their knowledge in a clinical setting. Proponents of PBL theorize that students learn best when learning in context (Schmidt, 1983). PBL provides students with an opportunity to experience the process of patient care and decision making without putting any actual patients at risk. PBL is also believed to promote life-long learning and to mirror real-life use of resources (Schmidt, 1983). Studies done comparing problem-based learning with traditional lecture curricula have found several positive trends with PBL. For example, in one study PBL graduates had similar, and sometimes better, performance on clinical examinations and faculty evaluations. They also were found to have board scores similar to those of traditional lecture students (Albanese & Mitchell, 1993; Norman & Schmidt, 2000). Learning appears to be better retained by PBL students as judged by faculty (Albanese & Mitchell, 1993) and PBL students have better problem-solving and information recall in clinical years (Norman & Schmidt, 2000; Vernon & Blake, 1993). Compared with lecture based instruction, students tend to report increased satisfaction with PBL. For instance, students considered the problem-based learning method to be more nurturing and enjoyable (Albanese & Mitchell, 1993; Norman & Schmidt, 2000; Vernon & Blake, 1993). Oklahoma State University Center for Health Sciences (OSU-CHS) Tulsa, Oklahoma has used this method of instruction in the Clinical Problem Solving course for 2nd year medical students since the early 1990's. Specifically, the students take a hybrid course with four hours of traditional lecture per week combined with four hours of small group work. The groups are composed of 6-9 students and one physician/tutor, also referred to as a facilitator. The groups work through carefully structured pre-designed cases to learn content while also developing problem-solving skills. Although this has been an effective format that is very popular with the students, there are several problems with the tutored groups: * Difficulty recruiting faculty due to time constraints. Theoretically, a non-physician tutor could be used, but studies have shown that there is less student satisfaction with this arrangement (Dolmans, Gijselaers, Moust, deGrave, Wolfhagen, & van der Vleuten, 2002). * Difficulty recruiting physician tutors from the community (non-faculty members), due to time and financial considerations. Small groups meet two mornings a week during prime office hours for most physicians. * Expense to Family Medicine Department to hire non-faculty tutors. …

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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)0.003
metaresearch head score (Gemma)0.000
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 score0.829
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.319
Teacher spread0.302 · 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