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Record W2312495176 · doi:10.2190/et.43.2.e

Creating Interactive Audiences for Student Writers in Large Classes: Blogging on the NewsActivist Learning Network

2014· article· en· W2312495176 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

VenueJournal of Educational Technology Systems · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methodologies in Social Sciences
Canadian institutionsChamplain Regional College
Fundersnot available
KeywordsComputer scienceValue (mathematics)MultimediaSocial mediaMathematics educationWorld Wide WebPsychology

Abstract

fetched live from OpenAlex

This article considers how instructors with larger classes can utilize Web 2.0 tools to help students develop as writers. Meeting the needs of readers defines strong writing, yet students need to interact with authentic audiences to learn to do this well. A growing body of educators is exploring how blogging can be used to enhance student learning. In this article, we describe how a blogging platform, NewsActivist, was used to create an interactive audience for student writers in a large sociology course. The article provides details on course and assignment design to meet major learning outcomes and support student growth as writers. Data from reflective essays and a user survey are presented that demonstrate the value of NewsActivist and its interactive audiences for student writers. The platform was found particularly useful to motivate students to care about their writing and to provide feedback to help students learn.

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)0.016
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.059
GPT teacher head0.441
Teacher spread0.381 · 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