Analysing the Integration of Models of Technology Diffusion and

Acceptance in Nigerian Higher Education

Muhammad Sadi Adamu

and Philip Benachour

School of Computing and Communications, Lancaster University, U.K.

Keyword: Higher Education, Education Technologies, Blended Approach, Technology Integration and Utilisation.

Abstract: The use of technology in learning environments has produced a series of different theories and models about

how technology is adopted, accepted and used. This paper attempts to show the relevance of combining the

diffusion of innovation model (DIM) and a context-specific model of technology acceptance (TAM) to

understanding the acceptance or rejection of educational technologies in Nigerian universities. Using

empirical evidence, the analysis attempts to determine the extent to which the adoption, acceptance, and use

of educational tools support or contradicts the components of the two models, emphasising how a range of

technological, pedagogical, institutional, socio-cultural, and design-related factors informed, facilitated, and

discouraged the diffusion, adoption, acceptance and use of blended eLearning systems in three Nigerian

universities. The analysis suggests the ‘relevance’ and ‘limit’ of the determining components and identifiers

of both models, arguing instead for a critical examination of the relationship between different models as to

understanding the factors that might lead to the acceptance or rejection of technological innovation.

1 INTRODUCTION

The diffusion and adoption of eLearning systems,

either through a blended approach or through online

learning, has become a common approach to

education in developed and developing countries. The

assumption is that the adoption of technology brings

about optimal ways to the practices of teaching,

learning, and management of educational processes.

However, the process and practice of transiting from

traditional ways to education to a blended approach is

one that has both positive and negative implications.

The presumption is that technology is a

transformative catalyst that can bring the old and the

new together, and thus relevant to the renaissance of

education in most developing countries (Gulati,

2008). Research has also pointed to how the mere

transfer of innovation from developed to developing

countries is not entirely a technological phenomenon,

but rather a pedagogical, social, economic, and

organisational agenda (Reagan, 2004). A range of

frameworks for the adoption and implementation of

blended learning are proposed (Graham et al., 2013;

https://orcid.org/0000-0002-2314-7414

https://orcid.org/0000-0001-8578-4024

Bervell and Umar, 2017). What might seem universal

and relevant to a multitude of cultural contexts might

however not be relevant to the decolonisation

movement of education in Africa. This calls for a

critical re-examination of how stereotypical models

fit into such an educational context. The literature in

the field of blended learning has also emphasized the

requirement of examining the different factors that

promote or hinder the adoption of technology (Castro,

2019). This raises the issue of considering how well-

known models are relevant to the socio-cultural

context and pedagogical needs of Nigerian higher

education institutions.

With the perceived differences between

developed and developing countries, the

understanding of the socio-economic and contextual

conditioning of different institutions and users

(Tarhini et al., 2017), becomes important for

integrating a range of learning models to determine

the institutional, pedagogical, organisational, social

and technological factors that influence and shape the

adoption and acceptance of a blended approach to

education (Marangunić and Granić, 2015; Okocha,

2019). This paper focusses on examining how the

178

Adamu, M. and Benachour, P.

Analysing the Integration of Models of Technology Diffusion and Acceptance in Nigerian Higher Education.

DOI: 10.5220/0009572101780187

In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 1, pages 178-187

ISBN: 978-989-758-417-6

diffusion and acceptance models can take into

account the peculiarity and specificity of the Nigerian

context. It seeks to understand the different factors

that support and promote or discourage the adoption

of a blended approach and the acceptance of

eLearning systems in three Nigerian universities. We

examine differences in pedagogical needs,

educational and social background, institutional

structures and policies, socio-economic relations, and

technological capabilities in the different institutions.

Consequently, the question that we seek to examine

is whether the integration of diffusion of innovation

and technology acceptance model can provide a better

understanding of the factors that should be

championed for a blended approach to

teaching/learning in Nigerian universities?

2 THEORETICAL CONTEXT

The notion of technology adoption and acceptance

has become a common phenomenon in studies

relating to the field of information system, education

technology, and human-computer interaction (HCI).

Different models have identified a range of factors

that assist in predicting and facilitating the diffusion,

adoption, acceptance and use of technology in a

variety of social and organisational context. The more

common is the technology acceptance model

(Venkatesh and Davis, 2000) and the unified theory

of acceptance and use of technology (UTAUT)

(Venkatesh et al., 2003). These models point to the

importance of user’s attitude and intention towards

the adoption, acceptance and use of technology. The

models provide a range of variables that allows

understanding the factors that support or hinder the

perception of using technology. However, most of the

studies in the literature report of findings from

developed countries, suggesting indicators primarily

relevant to industrialised social settings (Marangunić

and Granić, 2015).

However, within the context of developing

countries, there has been a surge of studies that

examine how socioeconomic and cultural factors

might influence the acceptance and adoption of

technology (Musa, 2006). The general premise for

most of the models has been about the availability of

technology and that the determining factor is the end-

user. In situations where the availability of

technology is scarce and where other external factors

are readily influential, the applicability of TAM and

its extended models are put to the test (Boateng et al.,

2016). Although the revised models have proven

useful to outlining how differences in capacities

(accessibility and exposure to technology) and values

(socio-economic, contextual, cultural, political

factors) might provide insights that could bring about

understanding the behavioural intention and attitude

toward use (Olatubosun et al., 2015; Nicholas-

Omoregbe et al., 2017; Okocha, 2019), a deeper

understanding of the determinants influencing and

shaping the adoption and acceptance of eLearning

systems are scarce.

What is missing in the literature of education

technology is the analysis of how context-specific

factors might have warranted the diffusion of

technology in education. There is a limited account of

the identifying factors (socio-cultural and contextual)

that have supported or hindered the acceptance of

available eLearning systems by lecturers and

students. Most of the attention has been given to the

primary components of the TAM models, specifically

the relevance of perceived usefulness and perceived

ease of use, rather than on how usage can be

maintained and promoted (Turner et al., 2010). Less

attention has also been given to the institutional,

pedagogical, socio-cultural, contextual, and design-

related factors that might have facilitated the

continual acceptance of blended approach to

teaching/learning in Nigeria; or the factors that might

have warranted the lack of acceptance and use by

students and lecturers. Within the gaps identified, we

sought to determine the extent to which the diffusion

of innovation and technology acceptance models

support the analysis of factors that came out of our

review of the present landscape of blended learning

in three Nigerian universities and the study of the

work practice of software designers/developers. Such

a report provides a broader picture of the link between

the factors that necessitate adoption, design strategies

that influence the acceptance or rejection of specific

educational tools, and factors that could shape current

and future use.

2.1 Technology Acceptance Models

The TAM is considered as the most well-known and

adopted model for determining the perception,

attitude and behavioural intention to accept or reject

technology. Its core component includes the

perceived usefulness (PU), perceived ease of use

(PEOU), attitude towards use (AT), behavioural

intention to use (BI), and actual use (AU) (Davis et

al., 1989). It has proven useful to the prediction of 30-

70% usage of technology. The model has been

adopted, extended and used in a range of social

context. Examples of which are the TAM2

(Venkatesh and Davis, 2000), UTAUT (Venkatesh et

Analysing the Integration of Models of Technology Diffusion and Acceptance in Nigerian Higher Education

179

al., 2003; Venkatesh, et al., 2012), and DeLone and

McLean’s success model (DeLone and McLean,

2003).

Figure1: The original technology acceptance model.

Such models outline the consideration of factors

like perceive usefulness, perceived ease of use,

perceived ubiquity, performance and effect

expectancy, innovativeness of the technology,

subjective norms, social influence and contextual

determinant (facilitating conditions) of the

technology as factors that might suggest the

determinant towards the intention of accepting or

rejecting technology. However, some argue that the

level of prediction of usage might be more subjected

to behavioural intention than perceived usefulness

and ease of use (Turner et al., 2010)

Within the Nigerian context, these models were

adopted in analysing a range of factors that predict the

adoption and acceptance of eLearning systems

(Olatubosun et al., 2015; Nicholas-Omoregbe et al.,

2017; Okocha et al., 2017; Yakubu and Dasuki, 2019;

Okocha, 2019). However, even with its usefulness,

the extension of TAM and UTAUT has proven

difficult in examining a range of other factors,

specifically socio-cultural and contextual factors that

might have influenced the adoption or rejection of

technology (Legris et al., 2003). Others have

examined a three-dimensional view of evaluating the

adoption and acceptance of eLearning system through

the analysis of the different phase of use, the users

involved and the components at each stage (Persico et

al., 2014). Most of the studies not provided sufficient

indicators for determining the implications of both the

characteristics of the innovation and the adopter to the

pedagogical processes and learning activities. We

focus on the aspect of the tool that could predict the

level of adoption and use.

2.2 Diffusion of Innovation Model

As technology has penetrated every facet of our life,

our perception of adopting or rejecting an innovation

might be based on our belief of the importance and

relevance of the innovation to some aspect of our life.

With the prevalence of tools developed and often not

adopted, the diffusion of innovation model came

about as to provide a unified theory of diffusion. The

model integrates the innovation-decision processes,

the individual’s innovativeness, the rate of adoption

and the perceived attitude of the potential adopter

towards the innovation in determining the

acceptability or rejection of an innovation (Rogers,

2010). In determining the level of diffusion of

technology in an organisation, the adopter uses a

range of construct to facilitate or impede their

perception and attitude towards acceptance/rejection

(Moore and Benbasat, 1991). The constructs include

the relative advantage of using an innovation against

previously used tools; the visibility of seeing others

adopt the same tool; the compatibility of the tool to

one’s prior experience and values; the tangible

outcome of adopting the tool (demonstration); and the

perceived acceptability of planned used (trialability)

(Rogers, 2010). What the model offers is an

understanding of the decision processes involved

(and the factors that shape one’s decision) and the

characteristic of the innovation towards the reduction

of uncertainty (in the perception of potential adopters)

of acceptance or rejection. The components provide

insights into the rate at which a particular tool could

be accepted or rejected within an organisational

context, thereby having a lesser prediction power

(Sahin, 2006).

However, as Sahin noted, the model has shown

greater relevance in understanding factors that

facilitate or impede the adoption of technology in

higher education. It also outlines the characteristic (of

both the innovation and the adopter) that influence the

decision process, the rate of adoption and the

perceived behaviour and attitude of an adopter. This

is relevant to our analysis as it provides a means for

identifying what necessitates the decision to adopt a

blended approach, the design strategies that led to

certain attributes of the innovation, and the

institutional implementation mechanisms that have

supported the transition from conventional methods

to a blended approach.

2.3 Integration of TAM and DIM

While a lot of studies have attempted to identify and

determine a range of factors that support/hinder the

adoption and acceptance of technological innovation,

there appears to be a varied interpretation and

extension of existing models in the analysis of

eLearning systems. A range of studies have examined

how different factors, such as self-efficacy,

performance and effect expectancy, social influence,

quality of service, subjective norms, interaction, and

satisfaction might provide determinant insights into

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user’s perception and intention for accepting and

using an eLearning system (Persico et al., 2014;

Rahmi et al., 2018). Others have pointed to the

implication of integrating different models in

determining the intention and attitude towards

adopting and accepting technology (Marangunić and

Granić, 2015), and specific to the context of Nigerian

(Nicholas-Omoregbe et al., 2017). Consequently, the

integration of different models, specially TAM and

DIM have shown significant influence in

understanding the factors that drive or hinder

acceptance (Persico et al., 2014; Tshabalala et al.,

2014; Al-Rahmi et al., 2019). Lee and colleagues

(2011) attempted to integrate the TAM and DIM as to

determine the relationship between motivation and

determinants of various factors to the adoption of a

blended approach and the acceptance of eLearning

systems. Al-Rahmi and colleagues (2019) report on

how the integration of TAM and DIM can assist in

developing insights that would inform the decisions

of planning, implementing and evaluating the use of

eLearning systems. What these studies have shown is

that TAM and DIM complement each other, and their

integration provides insights that would determine the

level of acceptance and rejection of an innovation.

However, within the context of sub-Saharan

Africa, Bervell and Umar (2017) analysis points to

the lack of integration of different models to

determine the factors that might have promoted or

hindered the adoption and acceptance of eLearning

systems. Most studies adopt and extend the TAM,

with only a few utilizing the integration of both TAM

and DIM in their analysis (for example, Tshabalala et

al., 2014). Most studies focus on the perspective of

end-users (lecturers and students), neglecting the

perspective of educational managers and software

designers/developers in the analysis of the factors that

motivate, inform, facilitate, or impede

adoption/acceptance. With the perceived differences

between developed and developing countries and the

understanding of the socio-economic and contextual

conditioning of different communities, it becomes

important integrating a range of models to determine

the different factors that might have necessitated the

adoption of technology in education and the attributes

that might have led to the acceptance/rejection of

blended eLearning systems in most Nigerian

universities. As we analyse data collected from a

range of actors, the factors that facilitate or impede

adoption and acceptance might vary, and what we

sought to point to is how a range of institutional,

pedagogical and technological factors shape the

diffusion of technology in Nigerian higher education.

We also identify design related and adopter related

factors that might have led to the acceptance or

rejection of the eLearning system like Moodle,

google classroom, canvass, and blackboard to support

the processes and activities of teaching/ learning.

3 EVALUATIVE APPROACH

The purpose of the study was to determine the extent

to which different components and identifiers of the

models of technology diffusion and acceptance

provide a better understanding of the factors that

might have led to the acceptance or rejection of

educational technologies within the context of

Nigerian Higher education. Qualitative data –

interviews and focus group discussion – was collected

across three universities and three education

technology companies in Nigeria. Both the author’s

institution and the host institutions/companies

granted ethical approval. Different forms of

reflexivity and relational accountability was

practised, before, during and after the fieldwork,

mainly due to the political implications of the field

researcher’s positionality as an in-outsider

(Nigerian).

In responding to the gaps identified in the

literature considering the lack of qualitative evidence

in the analysis of the factors that foster or impeded the

acceptance/rejection of technological innovation,

qualitative data was collected from both public (2)

and private (1) universities, and educational

technology companies (3). All of the three

universities might be considered at an exploration–

adoption stage (early implementation), mainly

because only a few departments and people adopt and

accept the technologies diffused into the educational

practice of their institution. Whereas the three

companies might be considered techno-educational

driven and with a wider client base. The data

collected and considered in the analysis consisted of

five focus group discussions with twenty-nine

students, fourteen interviews with lecturers, and three

interviews with education managers across the three

universities. Also, seven interviews from software

designers/developers across the three companies

were considered in the analysis. As the data that

informs the analysis is part of a project concerned

with decoding and untangling the thread of

postcolonialism in the process and practice of using

technology in Nigerian higher education, we adopted

an existing grounded approach to thematic analysis

where relational extracts that support or contradict the

components of both the TAM and DIM models are

highlighted and mapped to the issue problematised in

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181

this paper. It is our belief that the collective data from

a range of stakeholders would adequately show how

the integration of the two models might provide

insights into a range of factors that might have

motivated, informed, facilitated or discouraged

acceptance/rejection of educational technologies.

From the pool of the data considered, we attempted to

identify other relevant and context-specific factors

that might have impacted on the level of adoption,

acceptance, or rejection of eLearning systems. These

factors are important as we not only focus on the end-

user, as widely reported in the literature, but also on

those that design and evaluate the tools deployed, and

those that decide on which technological innovation

to incorporate into the educational practice. To re-

emphasise, our evaluative approach seeks to focus on

bringing forth an understanding of specific indicators

and strategies that can be considered peculiar to the

Nigerian context (but might also be relevant to other

developing countries).

4 RESULTS

In this section, we present the findings from the

evaluative analysis of participants’ data; presenting

an understanding of the factors that promote and

impede the practices of a blended approach. We

emphasize on the perspective of education managers

and software developers/designers, thereby providing

a new approach to that was normally adopted in the

education technology adoption and acceptance

literature.

4.1 Rationale for Diffusion and

Adoption of Technology

From the analysis of the data from educational

managers, it evident that the factors that motivate the

adoption of a blended approach to education are

driven by a pedagogical necessity, an organisational

culture, a socio-cultural demand and a technological

opportunity. Organisationally, the motive for

blending within the private university is mainly

because of the aim to provide ‘British standard

education in Nigeria’. The assumption is that

leveraging technology can bring about an effective

means for “providing quality educational services,

streamline operational processes, reduce operational

cost, and improve transparency” (Admin 1). There are

also ideas about how different organisational

structures and strategies, management frameworks

and support systems might have supported the motive

for blending. The strategies include an analysis of the

practices of a range of institutions globally that

implemented the blended approach, what model’s

they adopted, the sort of mechanisms put in place for

change management and mitigation of risk, and an

examination of how relevant that might be to the

Nigerian context. There are also ideas about how the

institutional policy of identifying potential avenues

where their instructional practices can be improved

through the use of technology might have supported

the adoption of a blended approach. socio-culturally,

the participants identify a range of factors that have

had some significant impact on the decision to blend.

This includes; the societal attitude of people towards

the advancement of technology globally (mostly

mobiles), the availability and accessibility of mobile

technologies among a range of users, the need for

flexibility and autonomy in educational processes and

practices, and also the need for a quantifiable value

for the money paid for education.

Although one might expect of a university that

strives to provide ‘standard’ British education that it

would be technically well equipped, the shared

understanding of the pedagogical needs of most

students/lecturers still warranted the adoption of a

blended approach. Some preferred conventional

means of education (through human interaction and

dialogue); others preferred the online form of

learning, therefore placing a pedagogical and a socio-

cultural requirement for an approach that is relational

to the needs of different people. Such an approach

responds to the educational needs of various people

but also moves towards developing students’

technical, employability and entrepreneurship skills.

It also supports understanding students’ performance

over time, identifying where one needs support and

thus might increase retention rates and reduce

attrition rates of students. Equally relevant is that to

facilitate the adoption of a blended approach, the

institutional diffusion model emphasis the design of

implementation mechanisms that provides the

necessary support for transition and change

management. This is achieved through the processes

of awareness creation, training of lecturers, and

incentivising and championing uptake for both

students and lecturers. This has drastically

popularised the enthusiasm for a blended approach.

For public universities, the organisational motive

for a blended approach was mainly because of a

pedagogical policy and a socio-cultural demand for

flexibility among a range of stakeholders. By

pedagogical policy, we mean to suggest, as

highlighted by a participant that “with the level of

development in the country, the classic online

learning is classically not suitable for us. We are in a

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system where people are transiting, and people tend

to hold certain things that are part of the past…..we

still want to have some form of human element

because it doesn't tie down with our African

background and context…..we believe that it is not

everybody that has the same orientation towards

learning, so we provide them with a platform whereby

they can identify what they are more attune to….the

blended approach is the focus” (Admin 2). This is a

pedagogical and a socio-cultural requirement placed

on most public universities. What the data suggest is

that traditional methods of education are not in line

with the institutional vision of becoming global and

also not contextually relevant to the needs of most

community members. The general assumption is that

the blended approach is appropriate to the established

guidance laid out by the relevant regulatory agencies.

What is common among the public universities is that

there is a determination to adopt best practices, and

leverage on technological development, as it would

encourage institutions to compete locally and

globally. As the proliferation of technology has

shown how educational processes and practices can

be supported and enhanced by technology, the

prediction is that the blended approach would

eventually become the practice of the day. This places

universities in the position of competing towards

becoming a key promoter of the blended approach.

Although the public universities might be facing

issues concerning lack of funding, infrastructure

deficit, the higher number of students, limited

accessibility to resource, and effect irregularities and

lack of enforcement mechanism, there are relatively

few institutional implementation mechanisms in

place that promote the blended approach to a range of

stakeholders. These mechanisms include budgetary

provision for equipment’s, staff training, and policy

directions. What is not in place is an effective change

management strategy that could inform the processes

of promoting and incentivising the adoption of a

blended approach. In a nutshell, what the analysis

might suggest, for both public and private universities

is that the blended approach is widely considered to

be the future of education in Nigeria. It also shows

how a range of constructs – organisational,

pedagogical, socio-cultural, contextual, and

technological – have shaped, promoted, and

popularised the adoption of a blended approach.

These constructs are relational to the attributes of the

diffusion model, in particular, they point to different

characteristics of the social and organisational

context where the technology is deployed, the

different actors involved, and the contextual factors

that shape the decision to blend or not. These

‘determining insights’ popularise the blended

approach. From the analysis, a pedagogical necessity,

an organisational culture, a socio-cultural demand,

and a socio-economic opportunity are to be

considered as supportive components to DIM’s

decision processes and attributes of innovation. Other

factors like awareness creation, incentivisation, and

the development of relevant change management

strategies and support systems are relational to factors

that can increase the adoption rate. It is our position

that the factors identified have shown an active link

to the process of developing an effective institutional

action plan guiding the decision processes that would

frame the implementation of eLearning systems in a

blended educational context.

4.2 Effective and Ineffective Design

Strategies

As we are after identifiers that could predict and

influence/discourage the level of acceptance and

usage of eLearning systems (either for new users or

for continual use by existing users), both effective and

ineffective strategies are identified. From the

analysis, the effective design strategies that we

understood to have had significant implications on the

acceptance and use of educational tools include the

methods used in understanding user requirement, the

design and development framework that inform the

design processes, the level of user engagement in key

design decisions and evaluations, and the

responsiveness and sensitivity of the design (in term

of different user values and other socio-cultural

needs). These are higher-level identifiers that inform

the practices of developing educational tools that the

data suggests hold more significant implication to the

processes and activities both students and lecturers

can undertake. There are also low level, and equally

relevant, identifiers like the tool’s level of integration

with existing user systems; the compatibility of the

tool to a range of devices; the usability, user-

friendliness and simplicity (or customisation to the

university context) of the tool; and the quality,

performance and security of the tool. Most of these

identifiers determine the level of user’s interaction,

engagement and satisfaction while using the tool.

They also influence the user’s perception of a tool,

determine their behavioural intention and attitude

towards use and thus critical to the acceptance or

rejection of technology.

There are other factors that, even though the

participants might not admit are ineffective practices,

might jeopardise the acceptance of deployed

educational tools. We believe that these factors

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183

significantly promote the rejection of educational

tools. Most of the inefficient practices, which all

participants suggested, are warranted by the

contextual nature of the Nigerian software industry.

Although they have attempted to show how they

adhere to best software engineering practice,

irregularities are often normalised. This include

designer/developers neglecting potential user’s

requirement – we ‘put ourselves in the shoes of the

use’ (Dev4), ‘thinking for them’ (Dev3), ‘implement

something close to what we think is generic’(Dev2) –

assuming that designerly way of knowing (Cross,

2001) is the same as a userly way of knowing. There

is also the alarming issue of how educational

managers providing system requirements, engage in

evaluating and validating educational tools, thereby

considering themselves de factor users. Although

they are potential users (their use of the technology is

mainly to manage the administrative and educational

processes of higher institutions) they do not engage

with the educational tools to carry out some

teaching/learning activities. One might expect that a

set of actual users’ (or potential users) will be

involved in articulating their needs, and some

developed educational theory or framework inform

the design processes of a particular tool. However,

what the data suggests is that no pedagogical

requirement nor actual user requirements inform the

design strategies used to develop and deploy tools. It

seems more likely that tools are developed and

implemented with the simple expectation that the

users will find them useful and relevant to their

processes, and which therefore from our analysis,

might have led to the low acceptance rate.

However, from the analysis of developers/

designers, one can appreciate what their perspective

might suggest to the predictability and articulation of

end user’s attitude and behavioural intention towards

the use of eLearning systems. It is therefore important

to point out that although the literature might have

neglected the perspective of designers/developers, as

our analysis has shown, they hold significant

implications to the acceptability or rejection of

educational tools, in both private and public

universities. Their practices can either promote or

impede the processes of teaching and the learning

outcome, and thus ought to form part of any model

that examines the acceptance or rejection of

educational technologies.

4.3 Identifiers of Acceptance and Use

In this section, we focus primarily on factors that

might have promoted or discouraged the acceptance

of the adopted tools by lecturers and students. The

analysis attempts to show the different and conflicting

factors that have fostered/hindered the acceptance

and use of eLearning systems as part of educational

processes and activities. It also identifies factors that

can bring about continual use or shape future use.

Lecturers’ Perspectives. For lecturers, the most

prominent factors that have led to acceptance are

individual curiosity, pedagogical necessity, social

accessibility, availability of technology, and

institutional promotional strategies and policy

directions. This is also driven by the assumption that

necessary infrastructure and technical training is

readily available, while also having sustainable

enforcement mechanisms in place. These factors

appear more strongly from the narratives of the

members of the private university. In public

universities, however, it is mainly due to personal

drive, social influences, and an awareness of the

relevance of the adopted technologies. Equally

relevant are the factors that might have warranted the

lack of acceptance by other lecturers. These factors

include people’s general orientation towards

technology, lack of proper promotional strategy and

enforcement policies, inadequate training and

support, lack of awareness of the importance of

available tools, and the dynamics of people’s attitude

and behaviour towards change. These issues are

institutional, whereas other national factors like

limited necessary infrastructure and connectivity

might have had hindered the acceptance of

educational tools in most higher institutions. In a

lecturers’ words: “the issue of using electronic

mediated means to reach out to students from the part

of the lecturers is because some people are

conservative and not ready to change. They still feel

that the only way students can learn is when they see

your standing in front of them. But some of use that

has undergone some training have come to learn that

students learn better when the enabling environment

is provided” (Lect 11). Such an account suggests a

profoundly rooted mentality towards conventional

approaches to education, and which the blended

approach supports.

Students’ Perspectives. For students, the analysis

attempt to identify specific characteristics of the

educational technologies that encouraged use. We

also identify other factors, either technology-related

or context related that might have discouraged use. In

the private university, students are more appreciative

of the technologies diffused into their everyday

practice, either through the use of education

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technologies or through the use of innovative support

systems. This is not to suggest that students of most

public universities are dissatisfied with the

technologies adopted in their institutions – but to

highlight how the issue of the higher number of

students and limited resources have led to negative

behavioural attitude towards educational

technologies. In both universities, students expressed

their attitudes towards the tools adopted by

suggesting that they are ‘easy in all aspect,

interesting, user-friendly (student made an emphasis),

straightforward, responsive, interactive, convenient

and available’. These terminologies were used to

show their perceived experience of use, providing

insights into the characteristics of technology that

warranted such behavioural attitudes. However,

another group emphasised that “the technology does

not really aid or have a significant impact on

performance; it is just a way of disseminating

learning materials and information” (Fgroup 2). Also,

one of the important factors that might have fostered

acceptance is that students are compelled to use the

educational tools deployed in their various

institutions, regardless of their perception or attitude

towards what was deployed. This makes prediction

relatively tricky, as they are in no position to decide

whether to use or not, use is a necessity placed on

them by their lecturers. Comparatively, this shows a

clear correlation to TAM’s perceived usefulness and

ease of use, but more importantly, how their lecturers

and other institutional instruments and power’s drive

their intention and attitude towards use.

Lecturers and Students as End-user’s. From the

analysis of end user’s – both students and lecturers –

one can infer two key indicators that shape current

and future use: the institutional driver’s that promote

acceptance by lecturers and the technologies

characteristics that provide predictable insights into

the compelling factors that drive continual use. The

factor that standouts among all students are the ‘user-

friendliness’ and ‘integrativeness’ of the tool with

existing systems in place. In addition, to bring about

more acceptance and actual use, there is a general

agreement towards universal access (providing

institutional loan schemes), promotion and awareness

creation (through seminars, workshops, training,

incentives), and the development of sustainable

policies and context-specific actions plans towards

changes management. This could bring about

reorienting the perception and attitude of the

academic community towards the blended approach,

which will, therefore, shape present and future use.

However, the analysis has also point to the fact that

the adoption and acceptance of educational tools by

end users is not entirely based on relative attitude,

perception or behavioural intentions of adopter, but

also supported by salient arguments concerning

institutional powers towards the subjective

governance of adopters. The form of governmentality

would be in how lecturers are under the disciplinary

gaze of university managers, whereas students are

constantly under the control of lecturer’s, thereby

presenting end user’s as subjects that power is

exercised upon. As the adoption of educational

technologies are prescribed and enforced on end

user’s, the subjectivity of the subjects of postcolonial

education are limited in their ethical form of self-

reasoning, self-formation, and self-governance.

5 DISCUSSION AND

CONCLUSION

This position paper advances our understanding of

how particular models and frameworks might inform

the process and practice of adopting and using

educational technologies in Nigerian higher

education through a blended approach. It suggests

that the integration of the components of the diffusion

of innovation and technology acceptance model

provide a better appreciation of the factors that might

champion or discourage the adoption and acceptance

of a blended approach to teaching/learning. From the

analysis of those that decide on what to blend and how

to blend, those that design and develop the tools used

to support the blended approach, and those that get to

use the tools in their processes and activities, our

interpretive analysis has advanced a range of context-

specific factors. First, the analysis emphasises prior

findings concerning the relevance of the components

of both models (Lee et al., 2011; Persico et al., 2014;

Tshabalala et al., 2014; Al-Rahmi et al., 2019) by

identifying and outlining factors that motivate,

promote, popularise, and hinder the blended

approaches to education, and then emphasising how

the characteristic of both approaches provide insight

into the possible acceptance or rejection of

innovation. These findings are consistent with prior

results from a range of studies that emphasise the

implication of factors like; perceived ease of use,

user-friendliness and technological integrativeness

(Rahmi et al., 2018; Yakubu and Dasuki, 2019); the

social availability-accessibility and innovativeness of

technology (Okocha et al., 2017); the implications of

subjective and social influences towards minimal

uncertainty (Tarhini et al., 2017; Papadakin, 2018);

Analysing the Integration of Models of Technology Diffusion and Acceptance in Nigerian Higher Education

185

and the pedagogical relevance and associated

importance of adoption, acceptance and use

(Olatubosun et al., 2015; Nicholas-Omoregbe et al.,

2017; Okocha, 2019). Some of the determining

factors identified can be considered specific to the

institution investigated, however, they might be

generalizable to similar educational context.

Secondly, our analysis indicates how institutional

mechanisms and strategies, like effective change

management planning, timely staff training and

support programmes, wider awareness creation

strategies, and promotional incentivisation of use, can

lead to an increase in adoption and acceptance rates.

Our account points to significant and often taken for

granted, factors that determine the extent to which

technological tools can be integrated into

conventional practices of higher education in

developing countries. Such factors provide the basis

for developing future actions plans and design

implementation strategies that could support and

promote future blending across different (Nigerian)

universities. The factors are not merely technological,

nor exclusively related to the characteristic of the

adopter, but more to the broader cultural sociality of

the context of deployment. This suggests the limits of

the determining components of both models by

bringing forth other relevant factors that might inform

the deeper analysis of technology in Nigerian higher

education.

Thirdly, the analysis points to how specific

design-based identifiers could influence/discourage

the attitude and behavioural intention of adopters.

From the discussion of effective and ineffective

design strategies, it can be inferred that the design

approach adopted shapes how the tool gets developed

and evaluated and thereby influences current and

future acceptance or rejection. We suggest that the

major contribution of our analysis is to point to how

differences in an organisational context, pedagogical

culture, and individual users’ positionality can

identify the factors that promote or discourage

acceptance and use.

To conclude, the analysis informs our

understanding of the dichotomy between

theory/theoretical construct and the practical

application and relevance of stereotypical models and

frameworks that impact the acceptability and

rejection of any technological innovation. In practice,

the range of factors identified from educational

managers, designers-developers, and ends users

provide a means of outlining how the plurality of

pedagogical, organisational, socio-cultural, and

technological identifiers are interpreted and

translated into design. We have also shown how

design related identifiers might influence or impede

the acceptability and usability of educational tools,

raising important question regarding the politics of

‘design’ as exemplified in HCI. The insights that

came from the analysis of a range of stakeholders; and

the implications of the mundane practices of thinking,

reasoning, deciding, designing, and deploying

technological innovation, suggest some of the power

relations involved in deploying technology in

education, in Nigeria (and elsewhere). This further

indicates the power dynamics of dominant paradigms

in educational research, where technology is often

considered neutral and beneficial to the renaissance

of education in developing countries. A critical and

subtle analysis of the underlying premise surrounding

such an assumption might provide insights into how

ethnocentric ideologies and prescriptive models

shape the adoption of technological innovation in

Nigerian higher education. This, therefore,

necessitates the consideration of indigenous and

localised alternatives that are not generalizable and

prescriptive, but rather generative and emerging.

Through a Freirean and Foucauldian concepts about

‘problematisation’, ‘governmentality’, and ‘ethical

subjectivity’ (Deacon, 2006; Bacchi, 2012), future

work would attempt to show how dominant

paradigms in educational research and HCI might

have produced a fateful misunderstanding and

misrepresentation of the factors that drive and

popularise the adoption and acceptance of

educational technologies in developing countries.

ACKNOWLEDGEMENTS

The authors would like to thank our imaginary co-

author – Mark Rouncefield – for critical insights and

comments on earlier draft. This paper is part of a

project funded by the Petroleum Technology

Development Fund (PTDF), Nigeria.

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