MétaCan
Menu
Back to cohort
Record W2294365348 · doi:10.5539/jel.v5n1p176

Mobile Learning as a Method of Ubiquitous Learning: Students’ Attitudes, Readiness, and Possible Barriers to Implementation in Higher Education

2016· article· en· W2294365348 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.

venuePublished in a venue whose home country is Canada.
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

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMobile deviceMobile technologyLearning environmentMathematics educationMultimediaComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

<p>The purpose of this study was to explore the attitudes and level of readiness, and possible barriers to implementing Mobile Learning as a part of ubiquitous learning. In addition, the study attempted to find out to what extent students are interested in mobile learning. It also aimed to answer the question regarding the readiness of college students to use mobile learning technologies. Furthermore, the level of students experience in electronic learning was examined. The study was conducted to gather valuable data about are the possible advantages and disadvantages of mobile learning, and the barriers do students expect facing when implementing the mobile learning technologies. To answer the research questions, a questionnaire was administered to 1000 college students, with some of them being interviewed for in-depth information. The findings of the study showed that students had highly positive attitudes toward mobile learning, and they had the necessary technical knowledge to implement mobile learning. However, students were found to have very little experience in electronic and mobile learning. Students have mentioned some advantages of mobile learning among which was the possibility of learning outside the classroom and at any time. Some disadvantages were mentioned such as the fact that students might become annoyed with receiving too many text messages per day. Finally, students listed some barriers they expect to face the implementation of mobile learning. The study concluded with suggestions for future research and recommendations to university officials to better implement mobile learning.</p><p><br /><strong></strong></p>

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.016
GPT teacher head0.385
Teacher spread0.368 · 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