Сучасний підхід до проблеми виникнення університету як соціокультурного феномену
Abstract
Стаття представляє ретроспективний аналіз соціокультурних характеристик середньовічних університетів. Соціальний аспект розкривається шляхом порівняльного аналізу організаційної структурної і функцій таких соціально-економічних інститутів середньовіччя як цехи і гільдії з організаційною структурою університету; культурний - шляхом аналізу впливу корпоративної структури університету на формування специфічного культурного суб-простору притаманного йому як соціальному інституту. Взаємодія університету з інститутами влади розглядається в контексті інституціоналізації його статусно-рольової структури, норм, правил і процедур, спрямованих на приведення їх в систему, здатну забезпечити визнання її соціальної значимості.The paper presents the current retrospective analysis of socio-cultural I characteristics of medieval universities. The social aspect is revealed by comparative analysis of I organizational and structural features of the socio-economic institutions like the medieval guilds I and guild organizational structure of the university; Cultural - by analyzing the impact of the I corporate university structure on the formation of a specific sub-cultural space characteristic of I him as a social institution. The interaction of university with government institutions considered I in the context of institutionalization of its status and role structures, rules, regulations and I procedures to bring them in, capable of ensuring recognition of its social significance.
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A binary BERT classifier was fine-tuned for each Bloom's Taxonomy category on 21,380 learning objectives from 5,558 university courses.
“We fine-tuned a binary BERT classifier [24] for each Bloom's Taxonomy category on 21,380 LOs from 5,558 university courses.”
From A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education (2024) · cites this paper as [24]
Each learning objective was categorized into one of six levels of the revised Bloom's taxonomy using a fine-tuned BERT classifier.
“Using the fine-tuned BERT classifier [24] (Section 4 has details), each LO was categorized into one of the six levels of the revised Bloom's taxonomy [19].”
From A Comparative Study of AI-Generated (GPT-4) and Human-crafted MCQs in Programming Education (2024) · cites this paper as [24]
Long-term use of social media leads to changes in people's mood and personality patterns and their learning processes and academic life are influenced, especially during a crisis, as seen during the COVID-19 Pandemic.
“In addition, long-term use of social media leads to changes in people’s mood and personality patterns and their learning processes and academic life are influenced, especially during a crisis, as seen during the COVID-19 Pandemic (3).”
Inefficient self-regulation, neglect of personal life, cognitive preoccupation, mood modifying experiences, lack of tolerance, concealment of addictive behaviors, and escapism are signs of social media addiction.
“Inefficient self-regulation, neglect of personal life, cognitive preoccupation, mood modifying experiences, lack of tolerance, concealment of addictive behaviors, and escapism are signs of social media addiction (3, 7, 8, 19).”
Existing AI-centric datasets primarily focus on high-level metadata such as acceptance rates and discussion dynamics and do not provide explicit or reproducible labels for textual merge conflicts.
“While these datasets offer valuable insights into how AI-generated contributions are created and reviewed, they primarily focus on high-level metadata such as acceptance rates and discussion dynamics. They do not provide explicit or reproducible labels for textual merge conflicts, limiting our ability to systematically quantify the integration friction introduced by AI-generated changes.”
From AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub (2026) · cites this paper as [38]
There is a moderate level of addiction among university students.
“Thus, it can be concluded that there is a moderate level of addiction among the University students (3, 4, 21).”
Yearly or daily usage can have a positive correlation with social media addiction.
“Yearly or daily usage can have a positive correlation with social media addiction.”
Age has a negative significant correlation with social media addiction.
“Meanwhile, age was found to have a negative significant correlation with social media addiction (3).”
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- Authors
- Aslan
- Venue
- Electronic Volyn National University Institutional Repository
- Published
- 2018-01-01
- OpenAlex
- W2951209485
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- journal article
- Language
- uk
- Open access
- closed
- Locations
- Electronic Volyn National University Institutional Repository (submittedVersion)
- Funders
- National Institute on Aging (K23AG051681)
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Historical Studies and Socio-cultural Analysis
- Social Sciences › Education › University Challenges and Reforms
- Social Sciences › Education › Historical Education Studies Worldwide
- Keywords
- medieval universities, university as institution, university organization, guilds
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