MétaCan
Menu
Back to cohort
Record W2778851245 · doi:10.5539/ies.v11n1p52

Learner Views about Cooperative Learning in Social Learning Networks

2017· article· en· W2778851245 on OpenAlexvenueno aff
Serkan Çankaya, Eyup Yünkül

Bibliographic record

VenueInternational Education Studies · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)PsychologyCooperative learningMathematics educationQualitative propertyQualitative researchProcess (computing)Scale (ratio)Data collectionPedagogyTeaching methodComputer scienceSociology

Abstract

fetched live from OpenAlex

The purpose of this study was to reveal the attitudes and views of university students about the use of Edmodo as a cooperative learning environment. In the research process, the students were divided into groups of 4 or 5 within the scope of a course given in the department of Computer Education and Instructional Technology. For each group, Edmodo small groups were formed, and the students used these Edmodo small groups to share and communicate with their group friends in relation to the group tasks assigned to them within the scope of the study. This process lasted one academic term. As the data collection tool, an online cooperative learning attitude scale and a semi-structured interview form were used. At the end of the academic term, 15 students were interviewed about their cooperative learning experiences within the scope of the course as well as about how they made use of Edmodo in the process. The results demonstrated that the students had positive attitudes towards online cooperative learning. The findings obtained via the qualitative data analysis were examined under the headings of “social networks used”, “preferences of forming groups”, “communication within group” and “views about the courses executed via Edmodo”.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
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 head0.099
GPT teacher head0.479
Teacher spread0.381 · 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 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

Citations18
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInternational Education StudiesSame topicImpact of Technology on AdolescentsFrench-language works237,207