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Record W2597765787 · doi:10.5539/jel.v6n3p107

My Pocket Technology: Introducing a Mobile Assisted Inquiry Learning Environment (MAILE) to Promote Inquiries among Secondary Students

2017· article· en· W2597765787 on OpenAlex
Sreelekha Leelamma, Uma Devi Indira

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 · 2017
Typearticle
Languageen
FieldComputer Science
TopicMobile Learning in Education
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationCurriculumPsychologyInquiry-based learningMobile deviceComprehensionCognitionLearning environmentSituated learningPedagogyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This paper introduces the Mobile Assisted Inquiry Learning Environment (MAILE), an Experimental Instructional Strategy (EIS) which employs an inquiry-based learning approach to guide secondary school students to learn environmental science in an engaging way supported by mobile phones. The students are situated in both the real world and the virtual world to extend their learning experiences. The effectiveness of this innovative approach is determined by comparing the learning effectiveness of an Experimental Group (EG) exposed to the experimental strategy and a Control Group (CG) taught the same content using the pedagogy prescribed by the state curriculum. The results show significant positive results in favor of the EG in multiple dimensions of cognitive learning prescribed by Bloom’s Taxonomy: Knowledge, Comprehension and Application.

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)0.002
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 score0.596
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.014
GPT teacher head0.311
Teacher spread0.297 · 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