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Record W2092608481 · doi:10.1145/2380552.2380602

Integrating mobile storage into database systems courses

2012· article· en· W2092608481 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile and Web Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer scienceMobile deviceMobile computingMultimediaField (mathematics)CurriculumResource (disambiguation)Mobile technologyMobile WebSoftwareCover (algebra)World Wide WebDownloadDatabaseOperating systemEngineeringComputer network

Abstract

fetched live from OpenAlex

The proliferation of smartphones and tablet computers is the newest paradigm shift occurring in the field of computing education. Mobile devices create serious resource and performance constraints that developers must keep in mind when creating applications for these platforms. In order to ensure that future developers have the knowledge required to create quality software solutions, academic institutions must seek to integrate mobile devices into their curricula. This paper presents an approach to integrate mobile application development in database systems courses, in the form of a short module designed to cover the approaches for persistent storage available on mobile devices. The Centre for Mobile Education and Research (CMER) has developed material, released as part of the CMER Academic Kit, including hands-on labs and assignments that instructors can freely download and integrate into their courses.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.018
GPT teacher head0.282
Teacher spread0.264 · 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

Quick stats

Citations7
Published2012
Admission routes1
Has abstractyes

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