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Behavioral insights in education: Intellectual data analysis for management

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  • معلومة اضافية
    • بيانات النشر:
      IEECA, 2024.
    • الموضوع:
      2024
    • Collection:
      LCC:Business
    • نبذة مختصرة :
      This research utilizes intellectual data analysis to deepen insights into educational dynamics by examining university professors' behavioral responses to education management amidst socioeconomic uncertainty. The study applied sophisticated regression and cluster analysis tools to sociological survey data, focusing on professors' attitudes toward distance education. The survey assessed perceptions of its advantages and disadvantages, aiming to uncover factors influencing professors' inclinations toward this mode of teaching. Results revealed six distinct behavioral "profiles" or clusters of professors, each with unique responses to distance education. These insights guide recommendations for educational policy priorities aimed at addressing weaknesses in education management. Key strategies proposed include forming databases of behavioral responses and employing algorithms for deep intellectual analysis. Such measures intend to align educational practices with the values, welfare needs, and communication preferences of the scholarly community, thereby enhancing their propensity for distance education. The study concludes that a higher level of academic engagement in distance education can be achieved by tailoring educational strategies to the specific needs and values of different professor groups. This approach promises to improve the effectiveness of education management and the overall quality of education, benefiting both professors and students by creating a more supportive and effective teaching environment.
    • File Description:
      electronic resource
    • ISSN:
      2328-8272
      2328-8280
    • Relation:
      https://ieeca.org/journal/index.php/JEECAR/article/view/1573; https://doaj.org/toc/2328-8272; https://doaj.org/toc/2328-8280
    • الرقم المعرف:
      10.15549/jeecar.v11i4.1573
    • الرقم المعرف:
      edsdoj.f34d37525e4c40fb9ed7d57dc2ad77f6