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Record W562664693 · doi:10.5860/choice.50-1234

Encyclopedia of the Sciences of Learning

2012· article· en· W562664693 on OpenAlexfundno aff

Bibliographic record

VenueChoice Reviews Online · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsnot available
FundersUniversity of Illinois at ChicagoUniversity of California, IrvineLingnan UniversityStockholms UniversitetUniversidade do MinhoNational Taiwan Normal UniversitySyddansk UniversitetUniversità Cattolica del Sacro CuoreUniversity of HaifaCentre National de la Recherche ScientifiqueUniversiti Putra MalaysiaOrta Doğu Teknik ÜniversitesiVrije Universiteit AmsterdamLomonosov Moscow State UniversityRadboud UniversiteitHarvard Graduate School of EducationUniversity of AucklandInstitut National de la Santé et de la Recherche MédicaleGriffith UniversityCenter for Advanced Study, University of Illinois at Urbana-ChampaignKU LeuvenPomona CollegeUniversity of New South WalesAnadolu ÜniversitesiMonash UniversityUniversity College CorkMassey UniversityAustralian Catholic UniversityCardiff UniversityUniversity of SussexUniversity of California, Los AngelesUniversità degli Studi di MilanoSaint Louis UniversityManchester Metropolitan UniversityUniversity College LondonUniversity of SouthamptonMax Planck Instituut voor PsycholinguïstiekKent State UniversityWellcome TrustUniversity of OxfordMcMaster UniversityNorges Teknisk-Naturvitenskapelige UniversitetIndiana University BloomingtonUniversidade Estadual de CampinasUniversity of BernCarnegie Mellon UniversityRobert Gordon UniversityiMindsImperial College LondonUniversity of MemphisUniversity of OklahomaYork UniversityQueen's UniversityUniversity of MiamiUniversity of Central FloridaNorthwestern UniversityUniversity of MissouriUniversiteit UtrechtTU Graz, Internationale Beziehungen und MobilitätsprogrammeUniversité de LyonUniversity of Technology SydneyIllinois State UniversityUniversity of ConnecticutMcGill UniversityUniversität SalzburgUniversität des SaarlandesUniversiteit GentWorcester Polytechnic InstituteBrown UniversityQueensland Brain InstituteUniversity of Wisconsin-MadisonDepartment of Epidemiology, Biostatistics and Occupational Health, McGill UniversityUtah State UniversityPrinceton UniversityUniversity of Illinois at Urbana-ChampaignUniversity of GeorgiaPennsylvania State UniversityWestern Michigan UniversityHarvard UniversityUniversity of Pennsylvania
KeywordsEncyclopediaHistoryLibrary scienceComputer science

Abstract

fetched live from OpenAlex

Learning is existential, and so its study must be complex and interdisciplinary.Over the past centuries, researchers from different fields have posited many theories to explain how humans and animals learn and behave, i.e., how they acquire, organize, and deploy knowledge and skills.Basically, learning is defined as a relatively permanent change in behavior and/or in mental associations due to experience.Learning is a response to environmental requirements and different from biological maturation, which, however, is a fundamental basis for learning.From a historical point of view, learning had been an issue of epistemology and philosophy since ancient times.Nevertheless, the twentieth century may be considered as the century of psychology of learning and related fields of interest, such as motivation, cognition, and metacognition.It is really fascinating to see the various currents of the twentieth century research in learning, remembering, and forgetting.And it is interesting to see that many basic assumptions of early theories have survived the paradigm shifts of psychology and epistemology that occurred during the twentieth century.Beyond folk psychology and naı ¨ve theories of learning, psychological learning theories can be grouped into several basic categories, such as behaviorist and connectionist learning theories, cognitive learning theories, and social learning theories.However, learning theories are not limited to psychology and related fields but can be traced back to ancient philosophers, such as Socrates, Plato, and Aristotle.It is certainly true that the topic of learning also played a significant role in the philosophy of the Middle Ages (e.g., St. Thomas Aquinas), and in the modern era philosophers such as Descartes, Hume, Locke, Kant, and many others were interested in the topic.The same holds true for philosophers of the twentieth century, who were highly interested in learning.It is noteworthy that the so-called fathers of psychology as a discipline, Wilhelm Wundt (1832-1920) and William James (1842-1910), were both originally professors of philosophy.In the 1880s, Wundt began studying rote learning of lists of nonsense verbal items, and a short time later, James foreshadowed many aspects of modern neurobiology of learning and even connectionist theory.Whereas Wundt and James remained closely aligned with the field of philosophy and the application of introspective self-observation, Hermann Ebbinghaus (1850-1909) began studying human memory and higher cognitive processes (such as meaningful learning) by means of experimental methods.This transported the study of learning and remembering out of philosophy and into the realm of empirical research, providing valuable tools until today.Ebbinghaus' seminal work on learning and remembering can be considered as the beginning of systematic psychological research on learning and remembering for the twentieth century.Another strong influence was Pavlov's reflexology and his experiments with animals.This can be considered as the beginning of research on animal learning, which was also characteristic, to a large extent, of the emerging fields of associative psychology (e.g., Thorndike) and Gestalt psychology (e.g., Ko ¨hler).At the beginning of the twentieth century, these two sources -associative psychology and reflexologygave rise to connectionism and the idea of learning by trial and error, whose most prominent supporter became Thorndike .Clearly, the first half of this century was strongly influenced by connectionism (and behaviorism) and Gestalt psychology, whereas the second half can be considered as the period of the emergence of cognitive and constructivist conceptions of learning.Psychologists and biologists have studied learning in animals and humans within the realm of both paradigms.Nowadays, animal and human learning and cognition are separate but related fields of study within psychology and biology, each with an identifiable history that is often intertwined with the other.Beyond psychology and biology, disciplines such as anthropology, sociology, and education focused on the topic of human learning in the course of the past centuries.However, one of the most important innovations for research on learning resulted from the emerging computer sciences and their focus on machine learning.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.276
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.007
Science and technology studies0.0010.003
Scholarly communication0.0100.007
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.2760.125

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 head0.098
GPT teacher head0.365
Teacher spread0.267 · 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 designNot applicable
Domainnot available
GenreReview

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".

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Citations241
Published2012
Admission routes1
Has abstractyes

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