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Record W4206528550 · doi:10.5539/nct.v6n2p22

Gender Differences in Academic Self-Concept among Standard Seven Pupils Using Learning Strategies in the Use of Information Communication Technology in Bungoma County, Kenya

2021· article· en· W4206528550 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNetwork and Communication Technologies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsNonprobability samplingPsychologyMathematics educationAcademic achievementSimple random sampleQualitative propertyGovernment (linguistics)PopulationSociologyStatisticsMathematics

Abstract

fetched live from OpenAlex

Despite introduction of Information Communication Technology in schools by Government of Kenya, minimal research has been done on influence of learning strategies in information communication technology use on academic self-concept of pupils. Academic self-concept has a reciprocal relationship with academic achievement. Poor trends in academic achievement are associated with pupils’ low academic self-concept as an outcome of continued use of traditional learning strategies. This may be alleviated by use of information communication technology in the learning process. The purpose of the present study was therefore to investigate gender differences in academic self-concept among pupils using learning strategies in the use of information communication technology. Multimedia Learning Theory, Collaborative Learning Theory and the Self Theory of Personality Development formed the theoretical framework of the study. A causal comparative ex post facto research design was used. The study employed mixed methods research by integrating qualitative and quantitative research. The study was done in Bungoma County. The target population was Standard Seven pupils in public primary schools in Bungoma County. A sample of 375 pupils was involved. Purposive sampling was used to select schools with computer program as treatment group and simple random sampling for schools using traditional learning strategies as comparison group. Independent and dependent variables were learning strategies and academic self-concept (measured in 3 dimensions) respectively. Data was collected through an adapted questionnaire with Academic Self-concept Scale and Learning Strategy Rating Scale for learning strategies. Oral interviews and non-participant overt observations were used to collect qualitative data from pupils and teachers who handled learners in the laptop computer programs. The reliability and validity of the instruments was established through a pilot study in 2 sampled schools which were not included in the main study. Data management and analysis was done using both inferential and descriptive statistics using Statistical Package for Social Sciences program. Pearson product moment correlation and t-test were used for inferential statistics. Results showed that there were no significant gender differences in academic self-concept among pupils using traditional learning strategies and those using learning strategies in the use of ICT (t=1.151, t=1.03,-1.494 df=168.191, 182.979 and 165.341, p> 0.05 and (t= 1.422, -0.178 and 0.386, df=178.3 94,180.903 and 175.616, p> 0.05) for treatment and comparison groups respectively. Recommendations for adoption of learning strategies in information communication technology use in classroom teaching and learning, policy development in education and curriculum development were made. Further research using pre-test and post-test experimental design with control group using samples at other levels of education and on individual subject academic self-concept was recommended.

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)0.001
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 score0.686
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.052
GPT teacher head0.318
Teacher spread0.266 · 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