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Record W4213140252 · doi:10.46793/uzdanica18.ii.099p

Korišćenje elektronske knjige u vreme zdravstvene krize od strane studenata učiteljskih i pedagoških fakulteta Zapadnog Balkana

2021· article· en· W4213140252 on OpenAlexaboutno aff
Daliborka Purić, Ljiljana Kostić

Bibliographic record

VenueУзданица · 2021
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)The InternetCoronavirus disease 2019 (COVID-19)Medical educationCompetence (human resources)PsychologyClosure (psychology)PedagogyLibrary scienceSociologyPolitical scienceMedicineGeographyWorld Wide WebComputer science

Abstract

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The closure of educational and cultural institutions during the COVID-19 pandemic has led to changes in the traditional teaching model and the transition to online teaching. Since access to textbooks and professional literature was significantly difficult in completely new conditions, the resources of information and communication technologies were included in the teaching process, among which the e-book took an important place. The authors examine the experiences of students of teacher training faculties and faculties of education (N = 394) in relation to (a) the use of e-book for study purposes; (b) the impact of the COVID-19 pandemic on the use of e-book for study purposes and (c) the factors that initiated the use of e-book. Research results show that two thirds of the respond- ents use this book format. According to the experience of more than a third of students, the current health crisis has contributed to the use of e-books to a greater extent than before, while a quarter of the respondents were motivated to start using it. The use of e-books was initiated mostly under the influence of professors and by independent internet search. Future class teachers and preschool teachers from the Western Balkans are open to the use of modern technologies, and the current pandemic has intensified the use of e-books for the purpose of their education, which has contributed to overcoming the dif- ficulties caused by the health crisis, as well as to gaining competence in efficient work with future generations of readers of various forms of text.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.716
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.030
GPT teacher head0.320
Teacher spread0.290 · 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.

Study designNot applicable
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

Citations1
Published2021
Admission routes1
Has abstractyes

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