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Record W3109824948 · doi:10.29303/jpmpi.v3i2.512

Pendampingan Guru Biologi dalam Penyusunan Instrumen Penilaian Berorientasi HOTS di Kabupaten Lombok Barat

2020· article· id· W3109824948 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Pengabdian Magister Pendidikan IPA · 2020
Typearticle
Languageid
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsImmunoPrecise (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Telah dilakukan kegiatan pendampingan pada guru Biologi dalam penyusunan instrumen penilaian berorientasi HOTS di Kabupaten Lombok Barat. Kegiatan pendampingan guru dalam penyusunan instrumen penilaian berorientasi HOTS ini dilaksanakan dalam bentuk (1) penyampaian materi secara klasikal, (2) pemberian contoh dalam membuat soal HOTS, dan (3) pendampingan guru dalam menyusun instrumen penilaian HOTS. Sebelum penyampaian materi dan latihan diberikan, terlebih dahulu dilakukan Survei dengan menggunakan angket. Hasil survei menunjukkan bahwa sebagian besar (55%) guru biologi yang ada di Kabupaten Lombok Barat belum pernah mengikuti kegiatan pelatihan pembuatan instrumen penilaian yang berorientasi HOTS. Semua guru (100%) setuju dan bersedia diberikan pelatihan terkait dengan HOTS. Kegiatan pelatihan dilaksanakan secara daring menggunakan zoom meeting. Peserta pelatihan terdiri dari 39 orang guru. Sebagian besar guru yang ikut pelatihan (52%) berasal dari Pulau Lombok. Sementara itu sisanya, 28% guru berasal dari Pulau Bali dan 20% guru berasal dari Pulau Sumbawa. Hasil pelatihan dan pendampingan menunjukkan bahwa guru-guru biologi yang ada di Kabupaten Lombok Barat masih mengalami kesulitan dalam pembuatan stimulus. Faktor penyebab guru mengalami kesulitan diantaranya disebabkan oleh kemampuan literasi dasar sekitar 30 – 40% dan kesulitan dalam melakukan kegiatan pengembangan media sekitar 50%. Karena itu, kegiatan pendampingan lanjutan yang melibatkan forum MGMP masih diperlukan.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0030.003
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.005

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 head0.056
GPT teacher head0.312
Teacher spread0.256 · 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