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Record W3179057367 · doi:10.36713/epra7488

RESULTS-BASED ANALYSIS OF STUDENTS’ ACADEMIC PERFORMANCE IN ENGLISH UNDER DISTANCE LEARNING

2021· article· en· W3179057367 on OpenAlexaboutno aff
Mariel Kristine M. Cortez

Bibliographic record

VenueEPRA International Journal of Research & Development (IJRD) · 2021
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsnot available
Fundersnot available
KeywordsDistance educationDescriptive statisticsMathematics educationPsychologyQuarter (Canadian coin)Test (biology)Academic yearSubject (documents)StatisticsMathematicsComputer scienceGeographyLibrary science

Abstract

fetched live from OpenAlex

Using the descriptive research design, this study aimed to do a results-based analysis of online and modular distance learning of the students’ academic performance in English on first and second quarter of school year 2020-2021 in Don Manuel Rivera Memorial National High School. The respondents of the study were composed of 50 Online Distance Learning (ODL) Students and 250 Modular Distance Learning (MDL) Students from Grades 7 to Grade 10 levels of Don Manuel Rivera Memorial National High School. This is a descriptive study using the questionnaire as the main tool in gathering the data. The data gathered were treated using frequency distribution and percentage statistics, weighted mean, standard deviation, and T-test. The mean level of parents’ support to ODL students was 2.72 interpreted as “Moderately Supportive” indicates that parents are somehow extending additional support to their children in accomplishing the tasks given to them. On the other hand, the mean level of parents support to MDL students was 2.95 interpreted as “Moderately Supportive” indicates that only few parents extend their support to their children despite the awareness that their children have no direct contact to their subject teachers to give them assistance in understanding the lessons. This concludes that students under online distance learning gets more instructional support rather than the students under modular distance learning which gives a huge impact to their academic performances.

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)0.008
metaresearch head score (Gemma)0.004
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 score0.077
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.088
GPT teacher head0.459
Teacher spread0.371 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2021
Admission routes1
Has abstractyes

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