MétaCan
Menu
Back to cohort
Record W2886884589

Grade Monitoring System: A Prototype for Thulamela Secondary Schools

2018· article· en· W2886884589 on OpenAlexaboutno aff
Pardon Takalani Ramazhamba, Thulani Mashiane, Zama Dlamini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsUnavailabilityQuarter (Canadian coin)SituatedWork (physics)Order (exchange)Report cardComputer scienceMedical educationBusinessEngineeringPsychologyPedagogyMedicineGeographyArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

In South Africa, the Department of Basic Education commissioned that every school must issue out a report card to every learner at the end of each term/quarter as a standard communication tool between parents/guardians and school. To adhere to this, schools distribute messages through various ways in order to summon parents/guardians to come and collect learner report card on specific dates proposed by the school. In Thulamela, a section in the Limpopo province in South Africa, most of the schools require parents/guardians to collect the reports in person. Some parents or guardians usually come across situations whereby it is not feasible to collect the report on that specific date due to unavailability due to work, lack of transportation, poor health conditions etc. In order to overcome such challenges, this study proposes the use of technology in the form of a system that will allow parents or guardians to monitor learner performance which is assessable in an easier and more efficient manner. The study was based on secondary schools which are situated around Thulamela Municipality.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.760
Threshold uncertainty score0.324

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 science0.0010.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.295
Teacher spread0.268 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicSoftware Engineering Techniques and PracticesFrench-language works237,207