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The integration of print and digital content for providing learners with constructive feedback using smartphones

2012· article· en· W1946077495 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBritish Journal of Educational Technology · 2012
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Council
KeywordsConstructiveComputer scienceHyperlinkLeverage (statistics)MultimediaDigital contentOdeMathematics educationHuman–computer interactionWorld Wide WebPsychologyArtificial intelligenceProcess (computing)Mathematics

Abstract

fetched live from OpenAlex

Abstract Timely feedback is considered essential for supporting professional growth and personal development. However, it is difficult to employ such feedback in traditional learning environments. Recently, smartphones are considered as educational tools for supporting instructional activities. Therefore, this study attempts to leverage the advantages of physical textbooks and mobile devices. A pedagogical strategy called constructive feedback was proposed to provide learners with real‐time and personalized suggestions according to the results of electronic assessment. Two types of connectivity techniques, namely QR C odes and hyperlinking, were applied for integrating printed materials and digital content. An experiment was conducted in a university course entitled C omputer N etworks, and a total of 80 students were recruited to participate in this experiment. The findings revealed that the strategy of constructive feedback had a significant influence on learning performance. However, no significant differences on learning performance were found between using QR C odes and using hyperlinking. Finally, implications of the findings were discussed for further research directions and practical applications.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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