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Record W2000933160 · doi:10.1145/1143549.1143739

Mobile learning with bluetooth-based E-learning system

2006· article· en· W2000933160 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
TopicWireless Networks and Protocols
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBluetoothComputer scienceMultimediaJavaThe InternetMobile deviceClass (philosophy)Key (lock)Wireless networkE learningWirelessComputer networkWorld Wide WebComputer securityArtificial intelligenceTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

This paper introduces a bluetooth-based e-learning system, which enables mobile learning from anywhere using a variety of devices, including cell phones, PDAs, and laptops. Different from current e-learning systems, which require the access to the Internet or other pre-established networks, the bluetooth-based e-learning system can establish a wireless network on the spot in an ad hoc fashion. To accommodate with the characteristic of portable devices, the system is designed for low power consumption and low learning cost. With the help of the system, an instructor can receive instant feedback from the students and check students' performance at any time. Students, on the other hand, can actively participate in the class and answer instructor's questions in an easier way. The system architecture, security issues, and key techniques on establishing the communication between cell phones and computers using bluetooth on Java 2 platform are explained in detail in the paper.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score0.412

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 communication0.0000.000
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 head0.004
GPT teacher head0.198
Teacher spread0.193 · 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

Citations18
Published2006
Admission routes1
Has abstractyes

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