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The Application of Cognitive‐Developmental or Mediated Cognitive Learning Strategies in Online College Coursework

2011· article· en· W2137202072 on OpenAlex
Richard A. Pruitt

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

VenueTeaching Theology & Religion · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsColumbia College
Fundersnot available
KeywordsCourseworkVariety (cybernetics)CognitionPsychologyOnline learningSubject matterProcess (computing)Mathematics educationOnline discussionPedagogyComputer scienceMultimediaCurriculumWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract This research article explores the active use of cognitive‐developmental or mediated cognitive learning strategies in undergraduate online courses. Examples and applications are drawn from two online sessions integrating online interaction, essay and discussion assignments, as well as a variety of multimedia components conducted during the spring of 2008. While focus on the interaction among students remains an important aspect of the online discussion environment, particular attention is given to the interaction between the student and the instructor. This paper argues that while online learning environments are ultimately student‐controlled, they should be teacher‐centered. The findings of this research suggest that students are more directly influenced by an instructor's intentional effort to mediate the learning process than by the course objectives, material, or subject matter. Successful use of online technologies requires deliberate action on the part of the instructor to integrate various mediated cognitive learning strategies: (a) student participation and response is significantly increased, and (b) student motivation and morale is dramatically influenced.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.331
Teacher spread0.307 · 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