Identifying the Aesthetic Criteria of Academic Library Websites Using a Delphi Panel

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Purpose

In the digital era, enhancing the visibility and usability of websites is essential, especially for university library websites that serve as critical knowledge-sharing platforms. This study identifies the aesthetic criteria for Iranian academic library websites.

Methodology

A Delphi panel method with snowball sampling was employed, involving 21 experts in the first round and 15 in the second. SPSS software was used for data analysis, with Cronbach's alpha calculated to assess internal consistency.

Findings

A total of 68 aesthetic criteria were identified and grouped into five categories: digital image aesthetics, technical design elements, visual complexity, user-centric aesthetics, and content quality. A checklist with 37 scales was developed, achieving strong reliability (Cronbach’s alpha > 0.9). The study also identified 17 highly significant components prioritized by Delphi experts, such as up-to-date content, ease of navigation, and responsive design.

Conclusion

The findings offer a robust framework for improving the aesthetic quality and usability of academic library websites. While designed for Iranian websites, the results are adaptable to other cultural contexts. The study contributes significantly to the field by providing a comprehensive tool for website evaluation and emphasizing the need for culturally nuanced designs.

Value: 

This research is the first in Iran to apply a Delphi approach for identifying aesthetic website criteria, contributing significantly to the global understanding of web aesthetics in academic contexts.

Language:
Persian
Published:
نشریه مطالعات دانش پژوهی, Volume:3 Issue: 3, 2025
Pages:
73 to 106
https://www.magiran.com/p2817874  
سامانه نویسندگان
  • Tavosi، Maryam
    Author (1)
    Tavosi, Maryam
    .Ph.D Knowledge and Information Science, Kharazmi University, Tehran, Iran
  • Mahboub، Siamak
    Author (4)
    Mahboub, Siamak
    Assistant Professor Data Science and AI, سازمان اسناد و کتابخانه ملی ایران
اطلاعات نویسنده(گان) توسط ایشان ثبت و تکمیل شده‌است. برای مشاهده مشخصات و فهرست همه مطالب، صفحه رزومه را ببینید.
مقالات دیگری از این نویسنده (گان)