MétaCan
Menu
Back to cohort

Orienting Teaching Toward the Learning Process

2004· article· en· W2164607959 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAcademic Medicine · 2004
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsMcGill UniversityDalhousie University
Fundersnot available
KeywordsMetacognitionComponent (thermodynamics)CurriculumPsychologyMathematics educationProcess (computing)Experiential learningCognitionGraduation (instrument)Active learning (machine learning)Teaching methodPedagogyComputer scienceArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Based on developments in educational psychology from the late 1980s, the authors present a model of an approach to teaching. Students' learning processes were analyzed to determine teacher functions. The learning-oriented teaching (LOT) model aims at following and guiding the learning process. The main characteristics of the model are (1) the components of learning: cognition (what to learn), affect (why learn), and metacognition (how to learn); and (2) the amount of guidance students need. If education aims at fostering one's ability to function independently in society, an important general objective should be that one learns how to fully and independently regulate his or her own learning; i.e., the ability to pursue one's professional life independently. This implies a transition from external guidance (from the teacher) through shared guidance (by the student together with the teacher) to internal guidance (by the student alone). This transition pertains not only to the cognitive component of learning (content) but also to the affective component (motives) and the metacognitive component (learning strategies). This model reflects a philosophy of internalization of the teacher's functions in a way that allows optimal independent learning after graduation. The model can be shown as a two-dimensional chart of learning components versus levels of guidance. It is further elaborated from learners' and teachers' perspectives. Examples of curriculum structure and teachers' activities are given to illustrate the model. Implications for curriculum development, course development, individual teaching moments, and educational research are discussed.

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.

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)0.009
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.006
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 head0.093
GPT teacher head0.472
Teacher spread0.379 · 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