Advances in computing and information technology are changing the way people meet and communicate. People can meet, talk, and work together outside of traditional meeting and office spaces. For example, with the introduction of software to help people plan meetings and facilitate decision-making or learning processes, geographic constraints are weakened and the dynamics of interpersonal communication are changing. Information technology also has a dramatic effect on the way people learn and learn.
As new information technologies infiltrate workplaces, homes and classrooms, research into user acceptance of new technologies has attracted a lot of attention from both professionals and academia. Software developers and vendors are beginning to realize that non-acceptance of technology by users can lead to losses of money and resources.
In the study of user acceptance and use of technology, TAM is one of the most cited models. The Technology Acceptance Model (TAM) was developed by Davis to explain computer usage behavior. The theoretical basis of the model was Fishbein and Ajzen’s Theory of Reasonable Action (TRA).
The Technology Acceptance Model (TAM) is an information systems theory (a system consisting of a network of all communication channels used in an organization) that models how users begin to accept and use technology. The model suggests that when users are introduced to a new software package, many factors influence their decision about how and when to use it, including:
Perceived Utility (PU) – was defined by Fred Davis as “the degree to which an individual believes that using a particular system would improve their performance at work.”
Perceived Ease of Use (PEOU) Davis defined this as “the degree to which a person believes that using a particular system will be effortless” (Davis, 1989).
The aim of TAM is “to provide a general explanation of computer acceptance determinants that is able to explain user behavior across a wide range of end-user computing technologies and user populations, while being both cost effective and theoretically valid.”
According to TAM, if a user sees a certain technology as useful, they believe in a positive relationship between use and performance. Since effort is a limited resource, the user is likely to accept the application when it is found to be easier to use than another. Consequently, educational technology with a high level of PU and PEOU can generate positive perceptions. The relationship between PU and PEOU is that PU mediates the effects of PEOU on attitude and destiny. In other words, while PU has a direct effect on attitude and use, PEOU affects attitude and use indirectly through PU.
User acceptance is defined as “a demonstrable readiness by a group of users to apply information technology to the tasks it is designed to support” (Dillon & Morris). While this definition focuses on the intended and intended uses of technology, research shows that individual perceptions of information technology are likely to be influenced by the objective characteristics of the technology, as well as interactions with other users. For example, the extent to which someone finds a new technology useful is likely to be using it. At the same time, his / her perception of the system is influenced by the way people around him / her evaluate and use the system.
Information technology research has consistently shown that user attitudes are important factors in the success of a system. Over the past few decades, many definitions of attitude have been proposed. However, all theories treat posture as a relation between a person and an object (Woelfel, 1995).
In the context of information technology, it is an approach to attitude testing – the Technology Acceptance Model (TAM). TAM suggests users to express a positive attitude towards technology when they perceive it as useful and easy to use (Davis, 1989).
A review of scientific research on AI acceptance and use suggests that TAM has emerged as one of the most influential models in this research stream. TAM provides an important theoretical contribution to understanding AI use and IS acceptance behavior. However, this model – with its original emphasis on designing system features – fails to take into account the social impact on the adoption and use of new information systems.