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Pregled bibliografske jedinice broj: 1093475

From Knowledge Transmission to Knowledge Construction: A Step towards Human-Like Active Learning


Kulikovskikh, Ilona; Lipić, Tomislav; Šmuc, Tomislav
From Knowledge Transmission to Knowledge Construction: A Step towards Human-Like Active Learning // Entropy (Basel. Online), 22 (2020), 8; 906, 11 doi:10.3390/e22080906 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1093475 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
From Knowledge Transmission to Knowledge Construction: A Step towards Human-Like Active Learning

Autori
Kulikovskikh, Ilona ; Lipić, Tomislav ; Šmuc, Tomislav

Izvornik
Entropy (Basel. Online) (1099-4300) 22 (2020), 8; 906, 11

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
item information ; pool-based sampling ; multiple-choice testing ; item response theory ; active learning ; deep learning

Sažetak
Machines usually employ a guess-and-check strategy to analyze data: they take the data, make a guess, check the answer, adjust it with regard to the correct one if necessary, and try again on a new data set. An active learning environment guarantees better performance while training on less, but carefully chosen, data which reduces the costs of both annotating and analyzing large data sets. This issue becomes even more critical for deep learning applications. Human-like active learning integrates a variety of strategies and instructional models chosen by a teacher to contribute to learners’ knowledge, while machine active learning strategies lack versatile tools for shifting the focus of instruction away from knowledge transmission to learners’ knowledge construction. We approach this gap by considering an active learning environment in an educational setting. We propose a new strategy that measures the information capacity of data using the information function from the four-parameter logistic item response theory (4PL IRT). We compared the proposed strategy with the most common active learning strategies—Least Confidence and Entropy Sampling. The results of computational experiments showed that the Information Capacity strategy shares similar behavior but provides a more flexible framework for building transparent knowledge models in deep learning

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove:
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Tomislav Lipić (autor)

Avatar Url Tomislav Šmuc (autor)

Citiraj ovu publikaciju

Kulikovskikh, Ilona; Lipić, Tomislav; Šmuc, Tomislav
From Knowledge Transmission to Knowledge Construction: A Step towards Human-Like Active Learning // Entropy (Basel. Online), 22 (2020), 8; 906, 11 doi:10.3390/e22080906 (međunarodna recenzija, članak, znanstveni)
Kulikovskikh, I., Lipić, T. & Šmuc, T. (2020) From Knowledge Transmission to Knowledge Construction: A Step towards Human-Like Active Learning. Entropy (Basel. Online), 22 (8), 906, 11 doi:10.3390/e22080906.
@article{article, year = {2020}, pages = {11}, DOI = {10.3390/e22080906}, chapter = {906}, keywords = {item information, pool-based sampling, multiple-choice testing, item response theory, active learning, deep learning}, journal = {Entropy (Basel. Online)}, doi = {10.3390/e22080906}, volume = {22}, number = {8}, issn = {1099-4300}, title = {From Knowledge Transmission to Knowledge Construction: A Step towards Human-Like Active Learning}, keyword = {item information, pool-based sampling, multiple-choice testing, item response theory, active learning, deep learning}, chapternumber = {906} }
@article{article, year = {2020}, pages = {11}, DOI = {10.3390/e22080906}, chapter = {906}, keywords = {item information, pool-based sampling, multiple-choice testing, item response theory, active learning, deep learning}, journal = {Entropy (Basel. Online)}, doi = {10.3390/e22080906}, volume = {22}, number = {8}, issn = {1099-4300}, title = {From Knowledge Transmission to Knowledge Construction: A Step towards Human-Like Active Learning}, keyword = {item information, pool-based sampling, multiple-choice testing, item response theory, active learning, deep learning}, chapternumber = {906} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


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