MétaCan
Menu
Back to cohort
Record W3136836781 · doi:10.1680/jenge.20.00086

Geotechnical and geoenvironmental engineering education during the pandemic

2021· article· en· W3136836781 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

VenueEnvironmental Geotechnics · 2021
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsPolytechnique Montréal
FundersNational Natural Science Foundation of China
KeywordsEngineering educationPandemicEngineeringFlexibility (engineering)Equity (law)Public relationsMedical educationEngineering ethicsPsychologyPolitical scienceCoronavirus disease 2019 (COVID-19)Engineering managementMedicineManagement

Abstract

fetched live from OpenAlex

This paper reports the impact of coronavirus disease 2019 on the practice and delivery of geotechnical and geoenvironmental engineering (GGE) education modules, including lectures, lab sessions, student assessments and research activities, based on the feedback from faculty members in 14 countries/regions around the world. Faculty members have since adopted a series of contingent measures to enhance teaching and learning experience during the pandemic, which includes facilitating active learning, exploring new teaching content related to public health, expanding e-learning resources, implementing more engaged and student-centred assessment and delivering high-impact integrated education and research. The key challenges that faculty members are facing appear to be how to maximise the flexibility of learning and meet physical distancing requirements without compromising learning outcomes, education equity and interpersonal interactions in the traditional face-to-face teaching. Despite the challenges imposed by the pandemic, this could also be a good opportunity for faculty members obliged to lecture, to rethink and revise the existing contents and approaches of professing GGE education. Three future opportunities namely, smart learning, flipped learning and interdisciplinary education, are identified. The changes could potentially provide students with a more resilient, engaged, interactive and technology-based learning environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.394
Threshold uncertainty score1.000

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 communication0.0000.000
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 head0.002
GPT teacher head0.163
Teacher spread0.161 · 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