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Record W2028916880 · doi:10.3138/sim.9.2.004

Rethinking Online Space: Encouraging Student Immersion for Online and Hybrid Courses

2009· article· en· W2028916880 on OpenAlexvenueno aff
Aaron A. Toscano

Bibliographic record

VenueSIMILE Studies In Media & Information Literacy Education · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsImmersion (mathematics)Mathematics educationSpace (punctuation)PsychologyComputer scienceMultimediaMathematicsOperating system

Abstract

fetched live from OpenAlex

Active learning and student-centered courses have been important goals for education research because they appear to provide better, more effective learning environments for students. This article provides ways to bring a student-centered perspective to online and hybrid courses. By using rhetoric and composition theories that inform critical pedagogical stances, the author calls for incorporating online writing spaces for students across the disciplines. Because writing and thinking are connected, the author advocates that online and hybrid courses ask students to (re)present their understanding of course content online in order to have students move away from passive learning. These online spaces, similar to e-portfolios, are semester-long projects that allow students more chances for reflecting on the course material through media with which contemporary students are already familiar. Additionally, the online spaces in which students compose form an online learning community for individuals to showcase their work and, more importantly, their understanding of the course material. The article concludes by showing readers that students showcasing their work online makes the medium (the Internet) their message.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.005
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.465
Teacher spread0.420 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2009
Admission routes1
Has abstractyes

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