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Record W2466319500 · doi:10.5120/ijca2016908039

Experimenting the Effectiveness of Traditional vs Modern Learning of Web Technologies among Computer Professional Students

2016· article· en· W2466319500 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

VenueInternational Journal of Computer Applications · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsCanadian Standards Association
Fundersnot available
KeywordsComputer scienceMultimediaWorld Wide Web

Abstract

fetched live from OpenAlex

The objective of the study is to analyze the opinion about traditional and online learning methods with respect to course, content, teacher and reachability. Keeping this in view, a software study was conducted and which was aimed to develop the learning tool which is known as "Knowledge Connection" for Sank-Hara Computer Centre for Education and Learning. It is an intranet/internet based learning tool based on blended learning methodology. Pre Hypertext Processor, Apache Web Server and Mysql as the back end and other tools such as Dream weaver were used to create a learning model and SPSS 20 were used to interpret the results. Sample of 100 respondents were taken for the study based on simple random sampling method. The findings reveal that the students are much more interested towards online environment based on their mean value. This study is unique in the sense that new user friendly learning tool have been deployed to test the results. The results will be helpful to introduce more number of online courses which can be incorporated in the syllabus to enrich more knowledge towards knowledge society.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.018
GPT teacher head0.348
Teacher spread0.330 · 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