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Record W4379184804 · doi:10.5430/jct.v12n3p233

Equilibrium or Studying Attractors to Upgrade Educational Suitability, Teaching Presence, Social Presence and Learning Results in MOOCs

2023· article· en· W4379184804 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 Curriculum and Teaching · 2023
Typearticle
Languageen
FieldComputer Science
TopicEducation and Learning Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsStructural equation modelingDescriptive statisticsConfirmatory factor analysisPsychologyUpgradeMathematics educationBootstrapping (finance)Computer scienceStatisticsMathematicsMachine learningEconometrics

Abstract

fetched live from OpenAlex

The purpose of this research is to find the equilibrium or studying attractors to upgrade educational suitability, instructional existing, social existing and learning results in Korean Massive Open Online Courses (K-MOOCs). To conduct this study, learners who had taken K-MOOC were selected for the study; data were collected from 369 K-MOOC learners. The data were studied using the SPSS 26.0 and AMOS 26.0 platforms. About the methodology of analysis, descriptive statistics analysis was carried out first, followed by an examination of the correlation. The measurement model was then confirmed using confirmatory factor analysis (CFA), and structural equation modeling (SEM) was used to validate the structural links and mediating effects between the variables. Further, to verify a mediating effect on educational performance, the numerical importance of the mediating result was verified using bootstrapping. Analysis outcomes are as the following: First, this study discovered that K-MOOC educational appropriateness positively impacted learning results. Second, this study discovered that K-teaching MOOC's presence meaningfully and statistically significantly moderated the association between educational appropriateness and learning outcomes. Lastly, this research discovered that K-social MOOC's presence had a statistically significant impact on moderating the link between educational appropriateness and learning results. The conclusions that can be derived from the analyses' findings are the following: To improve the learning performance of K-MOOC, which is operated through the national budget, education authorities must first deeply understand the learning needs of learners in accordance with social changes. It is also important to secure educational suitability by preparing and providing a variety of educational courses in consideration of learners' learning motives and learning goals. Lastly, it is important to increase the satisfaction and immersion in education by expanding the components of teaching existence and social existence to derive actual learning results. This study is meaningful in that it examines the direct and indirect effects of the state-led K-MOOC's educational suitability on learning outcomes, and in that it confirms the influence of teaching existence and social existence in that they enhance education outcomes.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.185
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.045
GPT teacher head0.363
Teacher spread0.317 · 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