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Record W4382752350 · doi:10.3389/feduc.2023.1192754

Assessment purposes and methods used by EFL teachers in secondary schools in Jordan

2023· article· en· W4382752350 on OpenAlexaff
Malak Swaie, Muath Algazo

Bibliographic record

VenueFrontiers in Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsWestern University
Fundersnot available
KeywordsDescriptive statisticsMedical educationPsychologyMathematics educationEnglish as a foreign languagePedagogyMedicineMathematics

Abstract

fetched live from OpenAlex

This study examines the purposes and methods of classroom-based assessment (CBA) used by English as a Foreign Language (EFL) teachers in secondary schools in Jordan. The study data was collected through an online questionnaire that surveyed 54 participants and follow-up semi-structured interviews with three teachers. The questionnaire data were analyzed in SPSS using descriptive statistics, while the interviews were transcribed and coded for recurrent themes. The data showed that teachers use assessment to achieve various goals, including those related to students’ performance, instruction, and administration. The study also found that teachers employed a range of assessment methods of which teacher-made tests was the most common. Additionally, teachers’ choices of assessment methods were found to be influenced by factors such as the National Exam (Tawjihi), students’ proficiency level, as well as their own knowledge of assessment. These findings have implications for prompting awareness among EFL stakeholders in Jordan about the vital role of CBA and the necessity to improve teacher training and professional development programs in order to enhance teachers’ assessment knowledge and practices.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.019
GPT teacher head0.415
Teacher spread0.396 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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