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Record W2151783851

The Validity and Reliability of the Marmara Learning Styles Scale (MLSS).

2007· article· en· W2151783851 on OpenAlexaboutno aff
Mustafa Otrar

Bibliographic record

VenueDspace Repository (Marmara Üniversitesi) · 2007
Typearticle
Languageen
FieldPsychology
TopicLearning Styles and Cognitive Differences
Canadian institutionsnot available
Fundersnot available
KeywordsLearning stylesCronbach's alphaPsychologyMathematics educationScale (ratio)Cognitive styleQuarter (Canadian coin)CognitionPsychometricsDevelopmental psychologyGeographyCartography
DOInot available

Abstract

fetched live from OpenAlex

Abstract The science of education has focused on alternative educational approaches for years with a view to meeting the needs of wide student audiences in classes. One of the sources of the differences in learning performance at class environment is the learning styles. This study has been conducted to develop a learning styles scale for students at the secondary education level. Within the scope of the study, a learning styles scale for the secondary education level tailored to the conditions in Turkey has also been developed. The study was started with 223 items and implementations were carried out on 909 high school students. After the study, Cronbach's Alpha coefficient was determined as 0.95. Furthermore, it was determined that item-total and corrected item-total correlations were significant and items were discriminative. The factor analysis has yielded that the items group under a total of 8 factors, total variance amount described was around 0.56 and that significant correlations were present between the factors. Key Words Learning, Learning Styles, Cognitive Learning, Secondary Education Facts on learning are much richer and more complicated compared to quarter century ago in terms of kind and detail. The learning concept today totally abandons the learning approaches oriented in machine model that adopts as a black box and focuses more on cognitive explanations and facts discovered by cognitive psychologists which were nearly little or no quarter-century ago. Furthermore, even though the weight of different theoretical approaches in education and learning on current practices have changed, the core, theme and standing point of the efforts have not deflected and do not seem to deflect in the future. What is learning and how does it occur? The advancing technologies yield developments capable of routing the learning-teaching process in a way that could not even be imagined a couple of years ago. At the beginning of the 20th century, education was focused on the acquirement of literacy skills. These skills were, in most simple terms, reading-writing and the four key arithmetical operations. Directing people to critical way of thinking express themselves clearly and plausibly, solve complicated problems in science and mathematics were not the central principle of the educational systems of that time. At the beginning of a new century, these concepts have turned out to be the key knowledge/skills essential for almost everyone to adroitly cope with the complexities of life. Besides, investments dedicated to educational-scientific research are also observed at the fields of practice. All these developments in studies on learning have inaugurated a new era that builds up new bridges between the science and practice. These efforts on comprehending how the learns and the subsequent developments orientate and accelerate the changes in the education-teaching process (Bransford, Brown & Cocking, 1999). Cognitive-based explanations, the last link of the epistemic chain formed by approaches that conceptually study learning, have made their mark on the education approach in the second half of the 20th century. In view of the data presented by the cognitive learning approaches (Schauble, Glaser, Duschl, Schulze, & John, 1995), even though the fact that studies performed on the learning of animals [behavioral approaches] provide some supplemental information as to the learning process cannot be denied, studies and explorations focused rather on the learning of human and facilitating to the discovery of individualism and individual differences of people inside and outside and thereby revealing all set of potentials and secret powers of people have come to the foreground. Furthermore, the individual was started to be perceived as the learner not the learned. The education and teaching approach today is destined to an active-participative/searching student profile rather than a passive-listener, receiver one. …

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.257
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2007
Admission routes1
Has abstractyes

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