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Record W4401490251 · doi:10.1186/s41239-024-00483-0

Rethinking assessment strategies to improve authentic representations of learning: using blogs as a creative assessment alternative to develop professional skills

2024· article· en· W4401490251 on OpenAlexaff
Mark O’Rourke, Andréanne Doyon

Bibliographic record

VenueInternational Journal of Educational Technology in Higher Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHigher educationAuthentic learningPsychologyPedagogyMathematics educationSociologyKnowledge managementComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Abstract This research explores using blogs as an innovative assessment tool to enhance authentic learning and professional skill development in students. Unlike traditional methods, blogs foster active knowledge building and peer interaction, making learning more engaging and aligned with industry contexts. The study involved third-year planning students, in the course Governance and Planning , and utilised questionnaires, focus groups, and blog post analyses. Results indicated that blogs promoted reflective practice, facilitated peer review, and improved learning efficiencies. Despite some initial resistance and concerns about academic rigor, students found that blogging enhanced their understanding of course content and professional practices. Teacher support and peer feedback played a crucial role in this process. The literature supports blogs’ effectiveness in motivating students and aligning learning activities with real-world applications. However, assumptions about students’ familiarity with blogging were challenged, highlighting the need for thorough induction and support. Overall, blog-based assessments proved beneficial in creating authentic learning experiences and preparing students for their future careers. Future research should consider long-term studies on graduate outcomes and further explore peer review mechanisms.

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)0.001
metaresearch head score (Gemma)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.484
Teacher spread0.447 · 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.

Study designTheoretical or conceptual
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

Citations2
Published2024
Admission routes1
Has abstractyes

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