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TAM


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Technology Acceptance Model Chronology & Evolution Nitin Joyram

1975 |

Theory of Reasoned Action (TRA)

Martin Fishbein

Icek Ajzen

Attitude Towards Behaviour Behavioural Intention

TRA suggests that a person's behavioural intention depends on the person's attitude about the behaviour (“Would I do this sort of thing normally?”) and subjective norms (“Would other people in the group do this?”).

Subjective Norm

Behaviour

1985 |

Theory of Planned Behaviour (TPB)

Icek Ajzen

TPB adds the notion of Perceived behavioural control which refers to a person’s perceptions of their ability to perform a given behaviour.

Attitude Towards Behaviour

Subjective Norm

Perceived Behavioural Control

Behavioural Intention

Behaviour

1985 |

Decomposed Theory of Planned Behaviour (TPB) Ease-of-Use Perceived Usefulness

Icek Ajzen

Attitude Towards Behaviour

Compatibility

Peer Influence Superior’s Influence

Subjective Norm

Self-efficacy Resource facilitating condition Technology facilitating condition

Perceived Behavioural Control

Behavioural Intention

Behaviour

1989 |

Technology Acceptance Model (TAM)

Fred D. Davis Perceived Usefulness Intention to Use When users are presented with a new technology, two key factors influence their decision about how and when they will use it: Perceived usefulness (PU) - the degree to which a person believes that using a particular system would enhance his or her job performance. Perceived ease-of-use (PEOU) - the degree to which a person believes that using a particular system would be free from effort.

Perceived Ease of Use

Usage Behaviour

2000 |

Technology Acceptance Model (TAM 2) Experience

Viswanath Venkatesh

Fred D. Davis

Subjective Norm

Image

Job Relevance TAM 2 sought to identify the variables that influence the perceived usefulness.

Voluntariness

Output Quality Result Demonstrability

Perceived Usefulness Intention to Use

Usage Behaviour

Perceived Ease of Use Technology Acceptance Model

2000 |

Technology Acceptance Model (TAM 2) These variables included:

Viswanath Venkatesh

Fred D. Davis

Subjective norm the influence of others on the user’s decision to use or not to use the technology; Image the desire of the user to maintain a favourable standing among others; Job relevance the degree to which the technology was applicable; Output quality the extent to which the technology adequately performed the required tasks; and Result demonstrability the production of tangible results. Furthermore, experience and voluntariness were included as moderating factors of the subjective norm.

2000 |

Extension of Technology Acceptance Model

Viswanath Venkatesh Perceived Usefulness

3. External Variables Two main groups of antecedents for the perceived ease of use were identified: anchors and adjustments. Anchors were considered as general beliefs about computers and computer usage. Adjustments were considered as beliefs that are shaped based on direct experience with the target system.

Attitude Toward Using

Intention to Use

2. Additional Belief Factors

1. Factors from Related Models

Perceived Ease of Use

Actual System Usage

2000 |

Extension of Technology Acceptance Model Three major directions of TAM extension could be deduced from a vast number of studies, thus introducing new factors and variables to the TAM that could be grouped into

Viswanath Venkatesh

1. Factors from related models: A number of factors from related models have been brought in such as subjective norm, perceived behavioural control, and self efficacy; 2. Additional belief factors: Some factors from a diffusion of innovation literature additionally addressing belief construct have been introduced, such as trialability, visibility, result demonstrability, and content richness; and 3. External variables: Various external variables or moderating factors to the two major belief constructs (perceived usefulness and perceived ease of use) have been introduced as well, such as personality traits and demographic characteristics or computer self-efficacy construct.

2006 | King R. William

Four Categories of TAM Modification 3

Jun He

Contextual Factors

1 In order to test the model’s applicability on the one hand and to enhance its predictive validity on the other, the applications of TAM on specific systems were identified as well. Consequently, TAM was updated with four major categories of modifications.

Technology Acceptance Model

Perceived Usefulness

Prior Factors

Usage

Behavioural Intention Attitude Perceived Ease of Use

2

Factors Suggested from Other Theories

Consequent Factors

4

2006 | King R. William

Four Categories of TAM Modification

Jun He

TAM as the ‘‘core’’ of a broader evolutionary structure that has experienced four major categories of modifications: 1. The inclusion of external precursors (prior factors) such as situational involvement, prior usage or experience, technology anxiety, personal computer self-efficacy and confidence in technology. 2. The incorporation of factors suggested by other theories that are intended to increase TAMs predictive power; these include subjective norm, expectation, task-technology fit, risk, and trust. 3. The inclusion of contextual factors such as gender, culture, and technology characteristics that may have moderator effects. 4. The inclusion of consequence measures such as attitude toward technology, perceptual usage, and actual usage of technology.

2008 |

Technology Acceptance Model 3 (TAM 3)

Viswanath Venkatesh

Hillol Bala

Venkatesh and Bala (2008) combined TAM2 and the model of the determinants of perceived ease of use and developed an integrated model of technology acceptance known as TAM3.

TAM |

Its Constructs

Constructs Behavioural Intention Attitude Towards Behaviour Perceived Usefulness Perceived Ease of Use

Constructs Subjective Norm Image Job Relevance Results Demonstrability Output Quality Constructs Computer Anxiety Perceived enjoyment Computer self-efficacy Computer playfulness Objective Usability Perception of external control

Definition An individual intends to act in a manner without guarantees to do so. The extent to which a person thinks that acting the behaviour is negative or positive. The extent to which an individual accepts that employing a certain application framework will raise his or her work performance inside an organization environment. Measures the level to which a person assumes that employing a system is effortless.

Definition The extent to which a person feels that individuals suppose he or she has to carry out the behaviour. can be characterized as the degree to which one's status is viewed to be improved by the employ of innovation in one's status of social systems The level to which the innovation is correlated to the job of someone. is distinct as visibility of results. Distinct as “what extent the novel technology executes work made by the user". Definition The concern of utilizes the computer or concern of the potential of utilizing a computer. Define as the level to which "the activity of applying a particular framework considered to be interesting in its own right, regardless of the consequences". Describe as the level to which persons believe they can achieve a particular work utilizing the computer. The fundamental inspiration to cooperate with the new framework. The technology-based comparison regarding the actual, instead of user perception, effort that is compulsory to achieve specific tasks. The level to which a person supposes that organizational assets are obtainable to ease the system use.

TAM | A hypothesised Use of TAM in Education Experience

Voluntariness

Subjective Norm

Image

Job Relevance Output Quality Result Demonstrability

Perceived Usefulness Intention to Use

Usage Behaviour

Perceived Ease of Use Technology Acceptance Model

Using TAM in Assessing Educators’ Intention to Use Online Teaching

TAM |

Using TAM in Assessing Educators’ Intention to Use Online Teaching (OT) The following depicts the hypothetical relationships between the various constructs and educators’ intention to use Online Teaching (OT):

Job Relevance

OT Usage Experience Perceived Usefulness Technology Proficiency

Students’ Engagement

Syllabus Coverage

External Variables

Attitude Towards Usage

Behavioural Intention to Use

Perceived Ease of Use Technology Acceptance Model

Hypotheses in relation to TAM variables H1: Perceived ease of use positively affects perceived usefulness of OT. H2: Perceived ease of use positively affects attitude towards using OT. H3: Perceived ease of use positively affects intention to use OT. H4: Perceived usefulness positively affects attitude towards using OT. H5: Perceived usefulness positively affects intention to use OT. H6: Attitude towards usage positively affects intention to use OT. Hypotheses in relation to external factors and TAM variables H7: Job relevance positively affects the perceived usefulness of OT. H8: Job relevance positively affects the intention to use OT. H9: OT usage experience positively influences perceived usefulness of OT. H10: OT usage experience positively influences perceived ease of use of OT. H11: OT usage experience positively influences attitude towards using OT. H12: Technology proficiency positively influences perceived ease of use of OT. H13: Technology proficiency positively influences attitude towards using OT. H14: Students’ engagement positively influences perceived usefulness of OT. H15: Syllabus coverage positively affects the perceived usefulness of OT.

TAM |

Using TAM in Assessing Educators’ Intention to Use Online Teaching (OT)

Theoretical Construct of how TAM can be used to assess educators’ intention to use online teaching. Hypotheses in relation to TAM variables H1: Perceived ease of use positively affects perceived usefulness of OT. H2: Perceived ease of use positively affects attitude towards using OT. H3: Perceived ease of use positively affects intention to use OT. H4: Perceived usefulness positively affects attitude towards using OT. H5: Perceived usefulness positively affects intention to use OT. H6: Attitude towards usage positively affects intention to use OT. Hypotheses in relation to external factors and TAM variables H7: Job relevance positively affects the perceived usefulness of OT. H8: Job relevance positively affects the intention to use OT. H9: OT usage experience positively influences perceived usefulness of OT. H10: OT usage experience positively influences perceived ease of use of OT. H11: OT usage experience positively influences attitude towards using OT. H12: Technology proficiency positively influences perceived ease of use of OT. H13: Technology proficiency positively influences attitude towards using OT. H14: Students’ engagement positively influences perceived usefulness of OT. H15: Syllabus coverage positively affects the perceived usefulness of OT.

H8

Job Relevance H7 H11

OT Usage Experience

Perceived Usefulness

H9

Technology Proficiency

Students’ Engagement

H12 H10

Attitude Towards Usage

H6

Behavioural Intention to Use

H2 H3

Technology Acceptance Model

H15

Syllabus Coverage External Variables

H4

H1

Perceived Ease of Use

H14

H5

H13

TAM |

Using TAM in Assessing Educators’ Intention to Use Online Teaching (OT)

The Theoretical Construct of how TAM can be used to assess educators’ intention to use online teaching would certainly bring insights to how educators view OT and to what extent they view the OT teaching strategy successful. Many researches are being carried with regards to OT and most of them are looking into the challenges faced by educators and students alike. TAM can be an effective tool in gaining knowledge about the various challenges and how they impacted on the educators' behavioural intention of actually using OT as substitute to the face-to-face interaction. As educator, I can also use the TAM model to assess the readiness or predisposition of my students regarding the use of OT. Consequently, the external variables will differ from the current TAM model and include teacher factor-, learning- and examination-related variables. This will lead to findings about whether students view OT as an effective teaching strategy.

END |

References Alharbi, S. and Drew, S., 2014. Using the Technology Acceptance Model in Understanding Academics’ Behavioural Intention to Use Learning Management Systems. International Journal of Advanced Computer Science and Applications, 5(1). Davis, F.D. (1986). A technology acceptance model for empirically testing new end-user information systems: theory and results. Doctoral dissertation. MIT Sloan School of Management, Cambridge, MA King, W.R., He, J. (2006). A meta-analysis of the technology acceptance model. Inf. Manag. 43, 740–755 Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11(4), 342–365 Venkatesh, V. and Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Science, 39 (2), 273-312. Venkatesh, V., Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204.