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Record W2807600164 · doi:10.12724/ajss.16.5

"Computerized Multimedia Package in Teaching and Learning Process of Social Sciences at Secondary School Level- An Experimental Study "

2010· article· en· W2807600164 on OpenAlexaff
Girija N Srinivasalu, S. Vijayalakshmi

Bibliographic record

VenueArtha - Journal of Social Sciences · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsSyllabusPresentation (obstetrics)Process (computing)AnimationContext (archaeology)MultimediaComputer scienceMathematics educationSocial studiesGraphicsTeaching methodPsychology

Abstract

fetched live from OpenAlex

In the present context of world peace, there is a great need of strengthening the Teaching of Social, Economical, Cultural, Religious and Technological Values in the society. Since Social Sciences a wonderful treasure house of information and values, teaching of Social Sciences should be made more interesting to the students to learn at all the levels. In this regard Instructional Media has stimulated Social Sciences teachers to seek innovative strategies in teaching learning process. These strategies are concerned with the systematic application of various media and skills to the requirements of educating the syllabus of Social Sciences.Based on instructional design, a Multimedia Package is prepared with the combination of text, graphics, sound, animation and video elements and presentation delivered by the computer. It is an individualized learning Package with Multimeda techniques which has built in self-evaluation process also. This was validated by different groups of experts at different levels and was also field tested. Finally the achievement test was administered to the learners.Thus the effectiveness of Multimedia package (SLM) on achievement was studied and analyzed statistically with the help of scores obtained.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.002
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.039
GPT teacher head0.393
Teacher spread0.354 · 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 designQualitative
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

Citations0
Published2010
Admission routes1
Has abstractyes

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