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Factors Influencing International Student Success in a K-12 Blended Learning Program

2016· book-chapter· en· W2484321273 on OpenAlexaffabout
Annette Levesque, Doug Reid

Bibliographic record

VenueAdvances in early childhood and K-12 education · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsMacEwan UniversityEntomological Society of Canada
Fundersnot available
KeywordsBlended learningVariety (cybernetics)Mathematics educationPoint (geometry)English as a foreign languageMedical educationQuality (philosophy)PsychologyPedagogyEducational technologyComputer scienceMedicineMathematics

Abstract

fetched live from OpenAlex

This research explored the experiences of foreign students enrolled in the Canada eSchool distance learning program. The study included one secondary school in Nigeria and three in Malaysia that had students enrolled in a program based on a blended learning model. A mixed mode data analysis model including qualitative and quantitative data analysis was undertaken. The purpose of the study was to examine factors that influence student success in blended learning programs accessed by foreign students. Results indicated that students in the study were most successful if they were self-disciplined and had access to a variety of local supports including: an effective learning environment with access to quality technology; assistance in the development of English as a second language; and support in navigating pedagogical transitions between educational systems. In theory, the results of this study point to a connection between the local and Canadian support communities for foreign students enrolled in Canadian blended distance education programs, and their academic success.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.011
GPT teacher head0.330
Teacher spread0.320 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes2
Has abstractyes

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