Understanding Instructors’ Cognitive Structure Toward the Academic Use of Social Network Sites: The Means–End Chain Theory

Abstract

Employing social network sites (SNSs) for academic purposes has been investigated in the literature; however, there is not enough scientific knowledge about university instructors’ behavioral perceptions and values that drive their academic use of SNSs. Therefore, a systematic cognitive framework, regarding SNSs academic usage, is beneficial to understand these behavioral perceptions. This research utilizes the means–end chain (MEC) analysis approach to investigate university instructors’ cognitive structure toward the academic use of SNSs. It identifies important requirements for the effective academic use of SNSs by recognizing the relationship between the critical features of SNSs and instructors’ perceived values derived from these features. The findings show that seven significant features of SNSs form 45 MECs that appear to be the most useful features used by university instructors for academic purposes. These seven features were found to be cognitively associated with 10 positive benefits, which are crucial to the fulfillment of nine of the instructors’ personal values. Of the seven features, following others and being a group member were used most frequently by instructors in their academic practices. These two features were of significant value for the instructors to achieve a sense of accomplishment. The findings have practical implications for instructors and educational institution policy makers to enhance the effectiveness of SNSs use in academic settings.

Applying means‐end chains theory to understanding psychological cognitive structure of online video sharing platforms: A study of user behavior in TikTok

“…Zhang and Yuan (2020) used the theory to determine which resource factors affect the perceived quality of information on academic social networking sites. Al‐Abdullatif and Aladsani (2021) discovered that academic social networking sites have seven key attributes that enable users to obtain 10 benefits and that are associated with nine values. In addition, Skalkos et al (2020) reported that whether Internet users use privacy‐enhancing software is not only influenced by the attributes and functions of the software but also influenced by whether using the software satisfies the users' personal needs, enables them to conform to social influences, and is in line with their personal values.…”

Self‐disclosure of Mentally Ill individuals in Private Facebook Groups: The Means‐End Chain Model

“…For example, “size” as an attribute can lead to “convenient” as a consequence, which can then lead to “satisfaction” as a value (Al‐Abdullatif1 & Aladsani, 2021). In the context of the present study, the aim of MECA is to understand how individuals with mental illness perceive their use of Facebook private groups for the purpose of self‐disclosure.…”