Social cognitive theory (SCT) is a theory of learning that presents cognitive variables that mediate between stimuli and responses to prove that individuals have control over their behaviour. Common tenets to all the different models of social learning theories are:
1. An individual’s behaviour can be stimulated by either reward or punishment. 2. In addition to learning through actual participation, man acquires knowledge
and skills by visual, vicarious learning.
3. An individual’s behaviour can be shaped by the imitation of people that he or she is associated with.
Albert Bandura has an authority on the cognitive Social Learning Theory (SLT) development in general and, more particularly, on the notion of modelling that is also known as the vicarious learning model. He has also contributed significantly to social learning concepts like self-efficacy, reciprocal determinants, and the idea of temporal variation in cause and effect through lapse of time. From his analysis of Miller and Dollard’s Social Learning and Imitation, he determined that there are four cognitive sub- functions that affect SLT: attention, representation, enactive translation, and motivation.
4.8.1 Conceptual components of SCT
SCT covers a comprehensive set of key factors, some examples of which follow.
Reciprocal determinism. As shown in the Figure 4-8, there is a triadic and mutual relationship among behaviour, environmental factors, and personal factors.
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The dynamic relationship among these three factors leads to inequality in their levels of influence that is dependent on individual circumstances like social and physical environmental influences (Pajares, 2002).
Vicarious capacity. This is the idea that humans are capable of learning through visual observation of others without needing to actually enact the ideas. Actual performance is not a requirement, as people do not transform all of their ideas into actions (Bandura, 1989).
Forethought. The capacity for forethought allows individuals to motivate themselves and to guide their actions based on outcomes that they anticipate.
Self-regulatory capability. This is the idea that people are capable of self- regulation of their behaviour that is influenced by social and moral standards as well as by self-produced goals and motivations.
Self-reflective capability. Self-reflection is a unique characteristic of humans as rational beings, in that it is a product of the critical analysis of thoughts and experiences. Other factors that may influence an individual’s standards for evaluating his or her own thoughts and actions are self-experiences, vicarious observations, social persuasions, and the appraisal of his or her own strengths and weaknesses.
Self-efficacy. Bandura (1986) defines self-efficacy as a person’s judgments of his or her own capability to execute an action plan. These judgments are not really concerned with skills, but the judgments themselves affect how a person maximises the skills that he or she does possess. An individual will act and execute performance based on this belief unless a supervening or qualifying element changes the circumstances and demands reassessment.
4.8.2 Self-efficacy and computing
The validity of self-efficacy has been studied together with the IS/IT domain- related factors to interpret the acceptance or adoption of wide-ranging technologies of individuals. Among the notable researchers are Compeau and Higgins (1995a), who
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studied the validity of the self-efficacy of computers together with its impact and antecedents. They concluded that computer self-efficacy (CSE) is a judgment of one’s ability to manipulate the computer, measured by several dimensions of self-efficacy, including “Magnitude”, “Confidence level” and “Generalisability”.
Magnitude reflects the expected level of capability. A high magnitude of CSE is a sign that an individual believes that he/she is capable of accomplishing computing-related tasks almost without the need for supervision or assistance.
Confidence is one’s competence in the performance of multiple computing tasks indicates strong CSE. Generalisability refers to the extent to which one’s CSE applies to different activities involving software or hardware configurations. The degree of generalisability is directly proportional to the expected level of ability in doing various systems computer tasks.
Compeau and Higgins (1995b) developed a research model based on the social cognitive theory known as the modelling intervention. In this model, prior performance and behaviour modelling are correlated directly to CSE, outcome expectations, and performance. The study tested the modelling intervention by showing a 20-minute videotape of educational clips on the use of the computer in different variations to eight research groups. Figure 4-9 shows the modelling behaviour as per SCT.
Figure 4-9: SCT modelling behaviour. Source: Compeau and Higgins (1995b).
Prior Performance Behaviour Modeling Computer Self-efficacy Performance Outcome Expectations
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The CSE formulation by Marakas et al. (1998) was used by Johnson and Marakas (2000) in their proposed model, which is a replication of the behaviour modelling effect on performance from Compeau and Higgins’ (1995b) study. Johnson and Marakas (2000) also expanded the study of Compeau and Higgins (1995b) with their theoretical explanations as to the issues left unanswered by the latter through presenting a modified model that can accurately reflect both SCT and the relevance of interest. Figure 4-10 illustrates the modified model by Johnson and Marakas (2000).
Figure 4-10: The proposed model (derived from Marakas et al. [1998]). Source: Johnson and Marakas (2000).
Comparing the two models, the Marakas et al. (1998) measures were more effective at capturing changes in the levels of CSE throughout the experiment because the revised model was able to capture the relationship of prior experience with the effect of mastery. Furthermore, the Compeau and Higgins (1995b) analysis was able to predict the behaviour response as influenced by modelling training with the assertion that it is more able to capture changes in CSE due to vicarious experience.
Using the foundations laid down by Marakas et al. (1998) on GCSE and CSE, Agarwal et al. (2000) scrutinised the development of self-efficacy beliefs over time through a software training environment study that included social influences,
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demographic variables (such as computer experience and prior performance) and beliefs related to self-perception of ability. Figure 4-11 illustrates the research model.
Figure 4-11: Research model of Agarwal et al.’s study. Source: Agarwal et al. (2000).