TECHNOPHOBIA VERSUS ICT ACCEPTANCE AND … use of recent technologies in schools inspires the ......

BERA Conferences, 2012

George Kenyon Hall, University Hall Place

University of Manchester

1 Wednesday 5th September 2012

http://beraconference.co.uk/abstracts/

TECHNOPHOBIA VERSUS ICT ACCEPTANCE AND USE IN TEACHING AND

LEARNING AMONG ACADEMIC STAFF OF UNIVERSITIES IN NORTHERN

NIGERIA

Authors:

Suleiman Alhaji Ahmad1 (Ph.D.)

Manir Abdullahi Kamba2 (Ph.D.)

Muhammad Usman3 (Ph.D.)

College of Education PMB 44 Azare, Bauchi State Nigeria1

Bayero University Kano2

Abubakar Tafawa Balewa University Bauchi3

Corresponding email: [email protected]

Paper presented at the British Educational Research Association Annual Conference, University of

Manchester, 4-6 September 2012

Abstract

The paper x-rays the importance of information and communication technology (ICT)

as a tool for teaching, learning and research that is dramatically changing the

landscape of educational development since the last two decades. The incorporation

of ICT in educational sector is rendering plethora of opportunities for higher

institutions to integrate ICTs in teaching, learning and research. However, the

purview of literatures indicates that there exists a significant resistance to technology

(i.e. technophobia) among academic staff in tertiary institutions in Northern Nigeria.

This becomes a deterring factor for successful integration of ICTs in tertiary

institutions of Northern Nigeria and the country in general. The paper uses modified

Technology Acceptance Model (TAM) to ascertain the level of ICT acceptance and

utilisation in teaching and learning among academic staff in higher institutions in

northern Nigeria. Questionnaire was the only instrument used for collecting relevant

data for the study. Stratified random sampling was used and data was analysed using

SPSS. The findings of the study indicates a significant relationship between

availability, perceived usefulness, perceived ease of use, and intention to use,

whereas, ICT anxiety, mediated the relationship. The study concludes that

technophobia has been the major problem hindering academic staff to effectively use

ICT for teaching and learning process, thus, it is hoped that the study will open more

gaps for future researches that would enhance efforts in educational development,

thus, bridging the digital divide in the country.

Keywords: Technology Acceptance, Technophobia, Resistance to Technology, TAM, ICT,

Nigeria.

mailto:[email protected]






Introduction

The use of information and communication technologies (ICT) today has significant

impacts on our lives. In education sector many tertiary institutions realize the potentials of using

the technology in classrooms as an aspect of enhancing learning environment. The recent

technology infusion causes presentation of instruction and methods of communication in our

traditional university classrooms to have changed (Masrom, 2007). Information technology

widens opportunities for teachers to integrate the technological tools into the teaching-learning

process in order to improve the system. These advances create new opportunities for

collaboration, sharing, and interaction in learning (Suleiman 2011). The use of recent

technologies in schools inspires the educators to approach the teaching tasks with sense of

purpose which makes the learning process easy for students. The Internet, the multimedia

gadgets and other interactive programs on CD-ROMs assist students’ learning. The innovations

and recent advancements in ICT rapidly transform teachers and their work to the extent that

classrooms today must be technology-supported environment. Getting ready to adopt the use of

technology and understanding how the technology can support teaching-learning process should

form parts of the skills required in the teaching profession. There is the need for policies on

professional development designed to cover workshops and re-training of teachers to positively

influence them in adoption of the use of the computer technology in their work.

ICT is a gateway to the modern information, skills and orientation (ISO), which

distinguishes the world order. The adoption of ICT has set a landmark in educational sector in

the last two decades. The ICT adoption in educational system has become a background for

driving the potentials of new technological devices which revolutionize the educational system.

It is obvious that effectiveness of using ICT tools in education would be that factor which will

determine which countries would develop successfully in the future. However, Suleiman (2009)

asserts that the digital divide is today one of the wide-ranging encumbrance among people and

countries in this present digital era. It is the inequality of access to information technology. As

the people of more technically progressed societies become highly enriched by the knowledge

they tend to create, there is a cognizance that many more millions of people are not only offline

but also lack the freedoms associated with such prevailing civilization especially in Africa.

The convergence of a variety of technological, instructional, and pedagogical

developments altered teaching and learning process in recent times. Recent technology

challenges the educational structures which facilitate learning. Recent developments in the field

of computer technology and the diffusion of other technological devices such as multimedia

gadgets and other network resources pre-figure the development and implementation of

innovative teaching strategies. Many advocate educators of technology integration into teaching-

learning process believe that it will improve learning and better prepare learners for the 21st

century.

The introduction of ICT tools into the educational sector created new social stereotypes

and gender inequalities. Thus, old stereotypic gender differences in attitudes and achievements

that previously existed in mathematics and technological disciplines were extrapolated to the

area of ICT.






Statement of Problem

It is clear that technology is becoming an important part of education and teachers are

seen as a crucial link in developing ICT literate students. Teachers’ technology acceptance was

operationalized through Venkatesh, Davis and Moris (2007) the Technology Acceptance Model

2 (TAM2). The TAM2 combines measurement of social and cognitive influences on potential

computer users with users’ perceptions of the perceived usefulness and of their intentions to use

a computer system to understand the conditions for adopting computer system.

Academic staff perceptions of computer technology were areas needing investigation.

Another research gap, which requires attention, is that the academic staff are part of an

interactive social system; the educational system which, they are a part of shapes them as they

shape it as well (Bandura, 1997).

Academic staffs of universities are expected to prepare their syllabi and notes with a

word processor, to supplement their traditional lectures with PowerPoint presentations, or to

deliver their courses in state-of-the-art distance learning formats. Many have embraced emerging

technology, yet have resisted the changes to overcome other barriers. This resistance has

presented new challenges for university dons to promote their institutions as being well equipped

with cutting edge technology.

Information and communication technology (ICT) has reshaped the responsibilities of the

school teachers over the last decade by infusing ICT into teaching which emerged as an issue of

educational reform across countries. Teachers have been encouraged to use ICT to facilitate their

teaching tasks and create better learning environments. Kozma, (2003) states that a gap does

exists between ICT affordances and teachers’ intentions of use.

It is evident that there are no clear set of preconditions is dramatically leading teachers to

adopt ICT in teaching (Thomas, 2001). Many studies examined some factors such as anxiety,

attitude, and self-efficacy, but they did not pay attention to intention. Others focused attitude

which mediated by gender, and suggested for extension to include computer anxiety and

intention. The literature provided that further research is necessary to identify factors related to

instructors’ technology acceptance within educational environments. This study tries to fill these

gaps.

Objectives of the Study

This study, beside the broad objective which is to examine a wide range of both objective

and subjective factors that influence the academic staff’s attitude toward use of technology in

their assignments of teaching especially for class preparation. The study states the following

three specific objectives as they are translated into the stated research questions:

To investigate differences of attitude and acceptance of ICT technology among academic

staff in Northern Nigerian universities in terms of gender designation and institution.

To formulate a new fit model of Technology Acceptance Model in to Nigerian

educational system.

To examine relationship between availability, perceived usefulness, perceived ease of

use, and intention to use, whereas, ICT anxiety, mediated the relationship.






Research Hypotheses

Nine null hypotheses were developed based on the research objectives. These are adopted from

diffusion of innovations theory. The hypotheses are as follows:

H1o: There is no significant relationship between Usefulness and Anxiety

H2o: There is no significant relationship between Ease of Use and Anxiety

H3o: There is no significant relationship between Intention and Anxiety

H4o: There is no significant relationship between Availability and Anxiety

H5o: There is no significant relationship between Anxiety and Attitude

H6o: There is no significant relationship between Attitude and Acceptance

H7o: No significant difference in terms of Gender in the Anxiety and Attitude relationship

H8o: No significant difference in terms of Designation in the Anxiety and Attitude relationship

H9o: No significant difference in terms of Institution in the Anxiety and Attitude relationship

Figure: 1. The Proposed Research Model

Significance of the Study

The primary contribution of the study is that it allows a comparison of the relative

influence of these various factors (acceptance of technology, attitude towards use of technology

in teaching and availability, intention to use, perceived usefulness, perceived ease of use, and

technology anxiety). This will help policymakers and school administrators identify the relative

importance of various impediments to the academic staff’s use of ICT and educational

technology tools in general and in their particular university.

The significance of this study is to allow examine academic staff on the level attention

toward use of ICT and their adjustment with technology at their workplace. The conclusion

Anxiety

Usefulness

Intention

Ease of Use

Availability

Gender

Designation

Institution

Attitude Acceptance






drawn from this study will be crucial in choosing who are involved in or concerned about the

improvement of the development, effectiveness and adjustment to technology in their institution.

Besides, the findings from scope area Northern Nigerian universities will be useful and

interesting particularly to the educational researchers in terms of technology acceptance model.

This study examines the application of modified TAM in the Nigerian Educational system

because of the overwhelming amount of research on the TAM in other advance societies.

Limitations

Beside limitation in the scope area and limited unit of analysis i.e. academic staff, the

study provides useful insights into the relationship of various variables. However, the results

may be viewed in light of possible limitations. Since the study was conducted in Northern

Nigeria, the achieved results might not be generalized to other part of Nigeria which has

substantial differences in terms of cultural and educational background with the northern part.

Although the lecturers were arbitrary distributed across the universities, culture and environment

can affect the perception of the research instruments, the conceptual constructs and the

relationships of the variables. Therefore, generalizing findings from culture to culture should be

done with cautious. The present study is limited also because of the results that were completely

obtained from self-report data system. The results of this study are limited by the use

questionnaire as the only single method of data collection. Although there are more than one

hundred universities in Nigeria the study limits to only six sampled Universities in Northern

Nigerian (table ….) in order to have a manageable scope.

Methodological limitation can be seen in the TAM model. It is seen as a viable model in

identification of resistance to technology through focusing on behavioral constructs it is

considered to be the simplest, easiest, and most powerful measure of technology usage.

However, some critics believe that TAM is too simple and has a limited number of constructs to

describe behaviors.

Literature

The technology revolution is challenging and redirecting all forms of education,

including higher education. The incorporation of technology into the teaching–learning process

has become an important component throughout all areas of higher education.

Attitude is one of the determining factors in predicting people’s behavior it also

influences the positive or negative response to a specific object, situation, institution, or person

(Aiken, 2000). This has to be backed by perceived usefulness which is another major

determinant in the adoption of technology. Attitude therefore, plays an important role in

education. Computer attitude is a people’s thought that influences the use of computers. Over the

years researchers on technology acceptance have found close relationships between computer

attitudes and other variables (Teo, 2008). Computer anxiety has been referred to as aversion to

computer, fear or apprehension towards dealing with computers thus this can be an obstacle to

vital implementation and adoption ICT in universities in Nigeria.






The Technology Acceptance Model (TAM)

The original version of the Technology Acceptance Model was put forward by Davis et al

(1989). TAM adopts the well-established causal chain of beliefs, attitude, and intention,

behaviour that has been put forward by social psychologists (Ajzen, 1991), it later become the

Theory of Reasoned Action (TRA). Based on certain beliefs, a person forms an attitude about a

certain object, on the basis of which he or she forms an intention to behave with respect to that

object. The intention to behave is the sole determinant of actual behaviour.

The TAM has been empirically reviewed and modified in a variety of settings with

various levels of success. To obtain a better understanding of the acceptance information

technology by academic staff, stake holders should understand the effective elements on their

attitudes toward using information technology. Therefore, the study would facilitate a better

understanding about academic staff self-efficacy and the variables that appeared to influence

perceptions regarding attitude toward using information technology.

Venkatesh, Davis and Morris (2007) stated that TAM is considered to be well-established

and robust. The model consistently explained a substantial proportion of the variance in usage

intentions and behavior. Perceived usefulness and perceived ease of use we found to be

determinants in predicting intentions of actual computer use. The intention of use also shows that

it has a high ability to predict the use computer systems. Venkatesh, Davis and Morris (2007)

identified perceived ease of use as a key driver of user acceptance of computer technology with

additional key determinants of computer anxiety, and perceived enjoyment. Davis, (1993 p. 477)

stated that:

1. Actual use: is the individual’s behavior regarding the new system.

2. Perceived ease of use: is the degree to which the individual believes that using

the system would require little or no mental and physical effort.

3. Perceived usefulness: is the degree to which an individual believes the use of a

system could enhance job performance.

TAM theory symbolize that personal performance is determined by intention

synchronized with attitude and subjective norm. By using the theory of reasoned action as a

theoretical foundation, Davis (1989) created the TAM to focus on the domain of user acceptance

of technology by replacing the attitudinal components of the theory with perceived ease of use

and perceived usefulness.

Perceived ease of use

Perceived ease of use is theoretically based on the research of Bandura (1982) who

defined self-efficacy as “judgments of how well one can execute courses of action” (p. 122). In

other words, self-efficacy is the belief in one’s own ability to overcome the perceived difficulty

of a task. The self-efficacious persons see a link between their own efforts and a successful

outcome.






Perceived usefulness

Perceived usefulness is another major determinant in the adoption of technology. It is the

tendency of users to believe that the new technology will help them perform their job better

(Davis, 1989). Sun and Zhang (2006) found a correlation between performance and an undefined

construct similar to perceived usefulness. They also indicate the effects of perceived usefulness

as a statistically significant influence on attitude, behavioral intention and usage. They found that

perceived usefulness as a factor significant that influences user acceptance of technology. The

perception of usefulness is formed in interaction with other individuals and a system (Davis,

1989).

Intentions

Davis (1989) emphasized that within organizational settings, people form intentions

toward behaviors which they believe may increase their job performance. The concept of

continuance is critical because technology acceptance research often focuses on the initial

adoption of technology and overlooks or ignores long-term use and the integration of new

software into the daily activities of employees. Research must include more longitudinal studies

to ensure that new technologies actually have been accepted.

Computer anxiety

Computer anxiety is a psychological phenomenon that has been well-reported in the

literature. In many studies, computer anxiety has been variously referred to as aversion to

computer, fear or apprehension towards dealing with computers. In other words, it is possible for

people to be anxious about actively using a computer or watching others use a computer, or both.

Generally, computer anxiety refers to negative emotions in cognitive states evoked in actual or

imaginary interaction with computer-related technology. Students who experience a high level of

computer anxiety have been found to avoid computers or general areas where computers are

found; be extremely cautious with computers; possess negative feelings about computers, and

shorten the necessary use of computers (Bozionelos, 2001).

It is usually argued that, in a world where computer interactions are necessary,

particularly in the educational setting, computer anxiety may be a problem. Computer anxiety

refers to an unpleasant emotional state or negative feeling surrounding computers. Computer

anxiety is the result of negative past computer experience and an over exaggeration of the threat

posed by the computer interaction.

Venkatesh, Davis, and Morris (2007) have discussed that the TAM can help predict

acceptance, but does not always help us understand and explain acceptance beyond attributing

the system characteristics of ease of use and usefulness. Tung and Chang (2007) created an

extended TAM, which included computer self-efficacy, and computer anxiety to explain

adolescent technology acceptance. Computer anxiety had a negative impact on computer self-

efficacy and ultimate intent to use it.

Attitude toward ICT

The attitudes toward using the system are predicted from two factors which represent

user beliefs and attitude, perceived usefulness and perceived ease of use. As emerging

educational technology is a main driver in higher education a review of educational technology






trends and issues, as well as technology acceptance in education was conducted to discover what

is already known within these areas of research. The review revealed three main categories of

technology usage in educational environments: (a) instructional, (b) productivity, and (c)

administrative. Although instructional use of emerging educational technology is slowly

increasing, this revealed that several barriers to the effective use of emerging educational

technology in higher education still exist. The issues were related to all aspects of education,

including institutional, faculty, students and educational effectiveness. One major barrier is that

there is still no consensus as to the effectiveness of using emerging educational technology in

improving student outcomes, which is critical to instructor acceptance (Wenglinsky, 1998).

Acceptance

In technology acceptance research, it has consistently been found to have a significant

impact on technology acceptance. These constructs have been found to have both direct and

indirect influences on technology acceptance, and on each other. Because of these complex

relationships between the constructs, and because research results have been mixed, additional

research to clarify the relationships between the constructs has been recommended. The

investigation of these constructs provided the specific context for the research questions in the

current study.

ICT Use in Education in Nigeria

Information Communication Technology (ICT) is the processing and maintenance of

information, and the use of all forms of computer, communication, network and mobile

technologies to mediate information. Communication technologies include all media employed

in transmitting audio, video, data or multimedia such as cable, satellite, fibre optics, wireless

(radio, infra-red, Bluetooth, Wifi). Network technologies include personal area networks (PAN),

campus area network (CAN), intranets, extranets, LANs, WANs, MANs and the internet.

Computer technologies include all removable media such as optical discs, disks, flash memories,

video books, multimedia projectors, interactive electronic boards, and continuously emerging

state-of-the-art PCs. Mobile technologies comprises mobile phones, PDAs, palmtops, etc.

(Iloanusi, and Osuagwu 2010).

ICT Use in Education in Nigeria Computer applications in education are common to

reserve a classroom teaching and learning activity, which is universally agreed by education

practitioners. However, a reportedly obscure area in the computer-based instruction is how it can

systematically implement the different learning path for the diverse levels of students. The

advancement in computer technology has enticed various types of learning activities in the

classroom environment. For instance, students with computer simulation technologies could

learn complex science topics just as much enjoyable as they could have them literally

understood.

With the advent of Internet and mobile telecommunication in the world, much has

changed in the way we live, work and interacts with each other. In a traditional classroom

setting, teachers often ask students questions to determine the level of comprehension in the

class. In Nigeria, the story of ever evolving affairs has been the same. Many of the officials






wonder why they should spend money on communication rather than on social demands. While

many have been restrained by the above factors, the spirit of technophobia has kept some aback.

The feeling of dislike for technology, has led to lower patronage for technology devices

and services. And if not squarely addressed may limit the expected growth to an information

society. The universities teachers’ culture and collective practices each plays a crucial role in

enhanced technology-based teaching and learning. This is because ICT facilitates meaningful

learning and teaching only through transformed social practices (Hakkarainen et al., 2001). In

order to incorporate ICT with their teaching practices, the academic staff of the universities need

to change their everyday practices seeking and working with modern knowledge. It may span

through several years, but should not hamper the teachers’ effort to start using ICT intensively in

preparing and conducting their teaching activities (Hakkarainen et al., 2001). In the

transformation with ICT teachers’ work appears to becoming more and more knowledge

intensive in nature. As a consequence, teachers have to engage in lifelong learning and efforts of

keeping knowledge, expertise, and competence up-to-date throughout their life. Working within

a collaborative community is likely to provide overlapping zones of proximal development that

smooth professional development (Vygotsky, 1962). Educators’ taking active part in using ICT

are likely to belong to community of networked practices. It is asserted that teachers have the

reported the benefits of on-line networking as the ways to sharing knowledge, expressing and

receiving collegial and emotional support, and an opportunity to air frustration and to learn new

things.

The ICT in Nigeria experiences some evolutionary measures. Government had been

trying a lot to intensify ICT in Nigeria right from primary to tertiary education. This is through

various means in form of training, provision of facilities and sponsoring various projects and

researches. This trend suggests that the level of technophobia among Nigerian academic staff of

universities has been slowing drastically vis a vis the level of ICT usage which is growing

significantly. Government has been committing to many efforts through agencies such as

National Communication Commission (NCC) and Tertiary Education Trust Fund (TETFund) in

provision and enhancing ICT tools and services in tertiary institutions. The establishment of ICT

centres and Centres for Educational Technology (CET) had been done in most institutions.

Provision of e. libraries, and enhancing staff development on capacity building had been on the

epoch all over the tertiary institutions in the country for the last half decade.

There are a lot of development opportunities for teachers to equip themselves with ICT

skills especially on the web. The Teachers’ Registration Council (TRC) had been doing a lot in

campaigns to prepare teachers for ICT skills acquisition. Training on ICT is now a pre-requisite

for all academic staff in tertiary institutions in Nigeria. As this may have been the avenue to

enhancing the ICT in educational sector.

Technophobia

Technophobia can be seen as fear or dislike of an advanced complex device like

computers or the technology in general. It generally refers to the sense of an irrational fear, but

others contend fears are justified. It is the opposite of technophilia or techonphile the love for

technology.

The presence of computers in the classroom is seen as a means which students would

thrive in a modern learning environment They become motivating factors as they allow students’

access to several information and they promote a greater understanding by allowing the students






to learn in various ways unimagined previously (Rubin, Fernandes, Avgerinou & Moore 2010).

Computer and Internet in classroom has steadily become part of that educational landscape.

Growing use of computers in education has substantial benefits to their integration in the

curriculum. Olaniyi (2006); Okon, Chika and Emmanuel (2007) identified factors influencing

digital divide and negative attitude towards ICT in Nigeria as:

Expensive devices

Poor access

Poor skills to use

Inadequate financial capacity

Poor internet services and low teledensity

Poor of power supply

Poor level of awareness

Poor technical assistance and maintenance culture

In appropriate ICT policies

Poor implementation of the policies

Population explosion

Government negative attitude toward rural areas

Low government commitment to education

People attitude and fear towards technology

Methodology

The study is descriptive research and survey research technique. The researchers

collected data by distributing questionnaires to the sample of the accessible population.

The population comprised all the academic staff in the universities in Northern Nigeria.

(Table 1) This population was chosen for the fact that the university’s academic staff had been

involved in provision and using ICT tools in their service delivery in the country

Table: 1 List of Universities sampled

S/N Institutions Sampled Year

Established.

Statu

1 *Ahmadu Bello University, Zaria 1962 Federal

2 *Bayero University, Kano 1975 Federal

3 *University of Jos, Jos 1975 Federal

4 *University of Maiduguri, Maiduguri 1975 Federal

5 *Usman Danfodiyo University, Sokoto 1975 Federal

6 *Abubakar Tafawa Balewa University, Bauchi 1988 Federal

7 ABTI - America Yola 2003 Private

8 Bauchi State University Gadau 2010 State

Data were collected through the use of questionnaire which comprised two sections. The

first section deals with the demography information on the respondents, example: Gender,






Designation, and Institution. The second part assessed the availability of ICT facilities,

usefulness of ICT facilities, ease of use, intention to use, anxiety in using, attitude toward and

acceptance of ICT technology. This section comprised seven items structured on a Likert (1932)

five point scale ranging from strongly agree to strongly disagree. Four hundred copies of the

questionnaires were distributed to the respondents. The respondents were contacted physically

(in person) who were urged to complete the questionnaire. A total of 200 copies of the

instruments were required, the 200 copies were duly completed and returned thus, were the ones

used for the analysis.

For testing the instrument validity copies of the modified instrument were vetted for

content validation by two experts. Reliability was ascertained by piloting the instrument on 30

staff in Bayero University Kano. The overall Cronbach Alpha score of .809 was obtained for

internal consistency. The obtained data were analyzed using Amos SEM and SPSS version 18.0.

Table:2.Cronbach Alpha value on the main constructs

SN Construct Cronbach Alpha

1 Availability 1-5 -.13

2 Usefulness 1-5 .90

3 Ease of use 1-5 .78

4 Intention 1-5 .75

5 Anxiety 1-5 .83

6 Attitude toward technology 1-5 .71

7 Acceptance 1-5 .76

Result

The result of this research is presented here according to the first six hypotheses tested. They are

H1o: There is no significant relationship between Usefulness and Anxiety

H2o: There is no significant relationship between Ease of Use and Anxiety

H3o: There is no significant relationship between Intention and Anxiety

H4o: There is no significant relationship between Availability and Anxiety

H5o: There is no significant relationship between Anxiety and Attitude

H6o: There is no significant relationship between Attitude and Acceptance

The measurement model was tested and presented with composite reliability. Both convergent

and discrete validity were observed. The structural model was also used to test the formulated

hypothesis. It presented the standardized regression weight. Other items observed were the

estimates, CMIN, Regression Weights, Correlations, Goodness of Fit Index (GFI), Comparative

fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), p value and chi-square

values. It is as follows:






Table: 3: Model Fit Values

Chi-square = 1131.9 (= 548) p<.05

Chi Square = \cmin 2.066

df 548

GFI .763

AGFI .727

NNFI /TLI .761

CFI .780

RMSEA .073

CMIN 2.066

p-value p<.05

Model Supported

Figure1. Measurement Model on relationship between AVL, PUS, PEU, INT, AXY, ATT and

ACP






Table :4:

Covariances: (Group number 1 - Default model)

Estimate S.E. C.R. P Label

pu <--> pe .337 .071 4.719 *** par_35

pu <--> int .116 .037 3.153 .002 par_36

pu <--> av .003 .003 1.025 .305 par_37

pe <--> int .096 .034 2.804 .005 par_38

pe <--> av -.002 .002 -1.155 .248 par_39

int <--> av .000 .000 .385 .701 par_40

Table 5:

Regression Weights: (Group number 1 - Default model)

Estimate S.E. C.R. P value Label

ax <--- pu -.119 .122 -.976 .329 par_29

ax <--- pe .284 .142 2.003 .045 par_30

ax <--- int -1.056 .357 -2.962 .003 par_31

ax <--- av -1.947 6.099 -.319 .750 par_32

att <--- ax -.075 .055 -1.362 .173 par_33

ac <--- att .417 .102 4.099 *** par_34

PU5 <--- pu 1.000

PU4 <--- pu 1.037 .086 11.997 *** par_1

PU3 <--- pu 1.162 .093 12.450 *** par_2

PU2 <--- pu .917 .083 11.011 *** par_3

PU1 <--- pu .978 .092 10.664 *** par_4

EU5 <--- pe 1.000

EU4 <--- pe 1.005 .124 8.136 *** par_5

EU3 <--- pe .881 .131 6.751 *** par_6

EU2 <--- pe 1.087 .152 7.174 *** par_7

EU1 <--- pe .869 .138 6.295 *** par_8

INT5 <--- int 1.000

INT4 <--- int 1.714 .415 4.129 *** par_9

INT3 <--- int 2.725 .636 4.281 *** par_10

INT2 <--- int 2.780 .646 4.300 *** par_11

INT1 <--- int 1.643 .438 3.750 *** par_12

AVL5 <--- av 1.000

AVL4 <--- av -65.022 53.821 -1.208 .227 par_13

AVL3 <--- av 15.202 15.087 1.008 .314 par_14






Estimate S.E. C.R. P value Label

AVL2 <--- av 4.820 7.453 .647 .518 par_15

AVL1 <--- av 6.220 11.212 .555 .579 par_16

ANX1 <--- ax 1.000

ANX2 <--- ax .925 .104 8.889 *** par_17

ANX3 <--- ax 1.308 .121 10.844 *** par_18

ANX4 <--- ax 1.352 .123 10.979 *** par_19

ANX5 <--- ax .506 .096 5.297 *** par_20

ATT1 <--- att 1.000

ATT2 <--- att 1.119 .152 7.360 *** par_21

ATT3 <--- att 1.365 .155 8.823 *** par_22

ATT4 <--- att .715 .170 4.202 *** par_23

ATT5 <--- att .893 .149 5.978 *** par_24

ACPT1 <--- ac 1.000

ACPT2 <--- ac 1.661 .276 6.009 *** par_25

ACPT3 <--- ac 1.657 .294 5.633 *** par_26

ACPT4 <--- ac 1.558 .290 5.371 *** par_27

ACPT5 <--- ac 1.327 .276 4.806 *** par_28

Table:6:Correlations: (Group number 1 - Default model)

Estimate

PU <--> PE .509 Not Supported

PU <--> INT .409 Not Supported

PU <--> AV .228 Not Supported

PE <--> INT .367 Not Supported

PE <--> AV -.193 Supported

INT <--> AV .037 Not Supported

Table :7 CMIN

Model NPAR CMIN DF p. value CMIN/DF

Default model 82 1131.900 548 .000 2.066

Saturated model 630 .000 0

Independence model 35 3250.474 595 .000 5.463

Table:8: RMR, GFI

Model RMR GFI AGFI PGFI

Default model .119 .763 .727 .663

Saturated model .000 1.000

Independence model .260 .407 .372 .384






Table:9: Baseline Comparisons

Model NFI

Delta1

RFI

rho1

IFI

Delta2

TLI

rho2 CFI

Default model .652 .622 .784 .761 .780

Saturated model 1.000

1.000

1.000

Independence model .000 .000 .000 .000 .000

Table:10: FMIN

Model FMIN F0 LO 90 HI 90

Default model 5.688 2.934 2.469 3.438

Saturated model .000 .000 .000 .000

Independence model 16.334 13.344 12.464 14.261

Table: 11 : RMSEA

Model RMSEA LO 90 HI 90 PCLOSE

Default model .073 .067 .079 .000

Independence model .150 .145 .155 .000






Figure2. Structural Model on relationship between AVL, PUS, PEU, INT, AXY, ATT and ACP

This section presented the result according to the last three hypotheses formulated they

are:

H7o: No significant difference in terms of Gender in the Anxiety and Attitude relationship

H8o: No significant difference in terms of Designation in the Anxiety and Attitude relationship

H9o: No significant difference in terms of Institution in the Anxiety and Attitude relationship

The first part indicates the descriptive result of the demographic variables i.e. gender,

designation and institutions. Then follows the t- test result which indicates the differences on

anxiety and attitude in terms of gender later the ANOVA analysis indicates the result on the

differences on level of anxiety and attitude in terms of designation and institution among the

academic staff of universities in the Northern Nigeria..






Table: 12...Descriptive Statistics on Demographic variables

Var Mean SD

GENDER 1.3 .45

DESIGNATION 1.7 .72

INSTITUTION 4.5 2.3

AVAILABILITY 9.1 2.2

USEFULNESS 7.8 3.8

EASE OF USE 8.9 3.6

INTENTION 8.6 3.4

ANXIETY 11.4 4.7

ATTITUDE 8.3 3.1

ACCEPTANCE 8.4 3.2











Table 13: T-Test in terms of Anxiety between gender

Independent Samples Test

Levene's Test for

Equality of

Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean

Diff

Std.

Error

Diff

95% Confidence

Interval of the

Difference

Lower Upper

AXY Equal var.

assumed .349 .556 -.907 198 .366 -.661 .729 -2.101 .777

Equal var. not

assumed

-.896 108.6 .372 -.661 .738 -2.126 .802

Table 14: T-Test in terms of Attitude between gender

Independent Samples Test

Levene's Test for

Equality of

Variances t-test for Equality of Means

F Sig. t df

Sig. (2-

tailed)

Mean

Diff

Std.

Error

Diff

95% Confidence

Interval of the

Difference






Lower Upper

ATT Equal var.

assumed .016 .901 .832 198 .406 .409 .491 -.560 1.378

Equal var. not

assumed

.854 118.6 .395 .409 .478 -.539 1.357

Table: 15: ANOVA on Anxiety and Attidute in terms of Designation

ANOVA

Sum of Squares df Mean Square F Sig.

ATT Between Groups 120.637 7 17.234 1.745 .101

Within Groups 1895.905 192 9.875

Total 2016.542 199

AXY Between Groups 1653.160 7 236.166 16.228 .000

Within Groups 2794.180 192 14.553

Total 4447.340 199

Table 16: Difference in Bonferroni Tests on Attitude and Anxiety in terms of Institution

ATT UDUS ABU 1.83333 .90712 1.000 -1.0405 4.7072

AXY UNIJOS ABU 2.04333 .90712 .712 -.8305 4.9172

Table: 17 ANOVA on Anxiety and Attitude in terms of Designation

ANOVA


ATT Between Groups 11.829 2 5.915 .581 .560

Within Groups 2004.713 197 10.176

Total 2016.542 199


Within Groups 4355.688 197 22.110






ANOVA


ATT Between Groups 11.829 2 5.915 .581 .560

Within Groups 2004.713 197 10.176

Total 2016.542 199


Within Groups 4355.688 197 22.110

Total 4447.340 199

Table: 18: Differences in Bonferroni Tests on Attitude and Anxiety in terms of Designation

ATT PROFESSOR SENIOR .29386 .49279 1.000 -.8960 1.4838

AXY LECTURER 3-1 SENIOR 1.09614 .72638 .399 -.6578 2.8500

Table: 19: Regression on relationship between AVL, PUS, PEU, INT, AXY, ATT and ACP

Model Summary

Model R R Square

Adjusted

R Square

Std. Error

of the

Estimate

Change Statistics

R

Square

Change

F

Change df1 df2

Sig. F

Change

1 AVL .047a .002 -.003 3.24496 .002 .440 1 198 .508

2 PUS .231b .053 .044 3.16859 .051 10.659 1 197 .001

3 PEU .249c .062 .047 3.16262 .008 1.745 1 196 .188

4 INT .277d .077 .058 3.14543 .015 3.148 1 195 .078

5 AXY .280e .078 .055 3.15057 .002 .364 1 194 .547

6 ATT .470f .221 .196 2.90478 .142 35.220 1 193 .000






Discussion

The influence of this system and its effect on academic staffs’ ICT tools acceptance

cannot be overlooked. Therefore, university teacher’s acceptance and use becomes an area of

critical concern to the government as a measure of the successful of these efforts in encouraging

the use of ICT tools in education.

In this paper it indicates that the proposed model had been supported with enough evident

as fit model. The structural model output of Regression Weights, Correlations, Goodness of Fit

Index (GFI), Comparative fit Index (CFI), Root Mean Square Error of Approximation

(RMSEA), p value and chi-square values suggest that the causal effect do exist in the

relationship among the latent variables tested. . The entire exogenous (independent) variables

directly influence the endogenous (dependent) which is the acceptance. Thus, is translating the

high level of technophobia and moderate level of ICT tools usage among the academic staff. At

the same time, ICT tools acceptance has been an important research issue in information

systems. Among the various models appeared to evaluate and to predict acceptance, Technology

Acceptance Model (TAM) is the most widely referred. TAM was firstly introduced by Davis

(1989) where he proposed that perceived usefulness and perceived ease of use are the

fundamental determinants of user acceptance. Perceived usefulness being seen as the degree to






which a person believes that using a particular system would enhance his or her job performance;

perceived ease of use is seen as the degree to which a person believes that using a particular

system would be free of extensive effort. The two determinants were found highly correlated to

usage. This is consistent with logical relationships that when a person finds a system easy to use

and useful, he or she would be fear free and would have a higher motivation and intention to use

it especially in higher institutions of learning.

It is revealed in this study that among the personal ICT competencies that lecturers need

to develop, the highest scoring item is the development of the ability to use key ICT skills in

developing and presenting information. Freedman (1999) presents personal key ICT skills in four

main areas of knowledge namely: hardware, software, curriculum and general knowledge. These

key ICT skills are not limited to knowledge of technical skills such as key boarding and technical

use of some software packages. They include the ability to recognize when and how to apply

ICT to the solution of academic problems. Clarke and Englebright (2003:56) state that “the key

skill on ICT is based on user being able to find, explore, develop, and present information in the

form of text, images and numbers.” This is in line with the idea of many educational

technologists that emphasis should not be on mere knowledge of technical skills. However,

knowledge of ICT skills is the foundation for the development of ICT competencies.

Consequently, from knowledge of skills, the academic staff are expected to progress to that of

how, where, when and why each skill should be used.

Another finding of this study is that the academic staffs need to develop competencies not

only in selecting, developing, monitoring and evaluating ICT instruction but also in developing

and maintaining educational website. This is to make it possible for learners to interact with the

learning content anytime and anywhere. The need for the academic staff to develop

competencies in the instructional integration of ICT in their areas across the curriculum is to

ensure that ICT based education promotes the integration of diverse subject areas. This type of

ICT based education offers opportunities for spiritual, moral, social and cultural development of

pupils. It is quite interesting that all the respondents overwhelmingly agree that teachers need to

develop competencies in using ICT as an instructive tool in the class as well as in developing

learner’s ICT capability. Using ICT as a instructive tool implies using it to establish dynamic and

powerful instructional strategies and environment. Developing learner’s ICT capability is an

important aspect of instructional competencies and it requires that learners be helped to

understand the potentials of ICT and to have confidence and desire to use ICT. Educators with

instructional competencies are far more in demonstrating confidence in making meaningful use

of ICT than those who are not. Williams, Wilson, Richardson, Tuson, and Cole (1998:2) affirm

that such educators “have the capacity not only to enhance the richness of the learning

experience but also encourage the development of information literacy in their own students.”

Conclusion and Recommendations

In conclusion, the review of previous TAM research points out that there is a need to

focus on more diverse populations, various technology applications, and various settings

regarding new technology acceptance. This paper revised version of the Technology Acceptance

Model to understand academic staff usage behaviour of ICT tools. The result of the study

indicates a significant relationship between availability, perceived usefulness, ease of use, and

intention to use, while, anxiety and attitude mediated the relationship. The study concludes that






technophobia has been one of the major problem hindering academic staff to effectively use ICT

for teaching and learning process

It is obvious that in this era of ICT, Nigeria as a nation will find it very difficult to cross

the digital divide if concerted effort is not made to promote and continue to enhance ICT

education. One of the strategies to be adopted in this regard is the production of academic staffs

that have developed competencies for the instructional use of ICT. Academic staffs who do not

possess these competencies cannot impart same onto the learners. Nonetheless, to ensure the

development of academic staff ICT competencies the following recommendations are made:

1. More funds and allocation toward ICT in schools

2. ICT policy to make compulsory course for all lecturers

3. Lecturers should be helped empowered on competent in and receptive to ICT

4. ICT facilities be made available in all universities for easy access

5. The Federal Government should intensify the ICT development

6. ICT competencies set as a priority and targets be set for all long serving lecturers

7. Newly employed lecturer are expected to become ICT-literate as mandatory

8. It should ensure ICT integration into education across the curriculum in the country

9. NGO, Philanthropist individuals and Private companies needs to get involve in ICT

10. Future Research

This paper has contributed to the original TAM model by incorporating the conceptual

findings of previous TAM research, by successfully introducing the concept of availability,

anxiety and attitude. Thus, this work is subject to a number of limitations. We have investigated

only academic staff of universities in Northern Nigeria; this scope can be extended to cover other

categories of staff and to cover the whole country. There is obvious bias in the sample, because

we considered Kriejcy and Morgan’s (1970) sample size; this increases the possibilities of

measurement error. Finally, the constructs were restricted only to availability, usefulness, ease of

use, anxiety, attitude, intention and acceptance to use. The study also examines only gender,

designation, specialization and institution as demography variable. Researchers are therefore

encouraged to pursue on these limitations.

Acknowledgement: we are highly indebted to TEDfund Abuja Nigeria for their contribution and

sponsorship to this conference. Our sincere appreciations go to the respondents (some academic

staff of universities in Northern Nigeria).

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Apendix1

The scale on section B is as follows:

(1=strongly agree 2=Agree 3=No Decision 4=Disagree 5=Strongly Disagree)

Section A

Gender: Male Female

Designation Lecturer 3-1 Senior Reader/Professor

Specialization _________________________________________________________________

Institution _________________________________________________________________

Section B

SN Dimensions SA A ND D SD

Availability 1 2 3 4 5

1 There is a befitting ICT center in the University

2 Staff has adequate access to ICT centre

3 ICT facilities and Internet are available for utilization in the

University to every academic staff

4 I owned my personal computer

5 I owned other ICT tools such as iPad, Smart phones, PDA,

Projector

Usefulness

1 Using the ICT tools would enable me to accomplish tasks more

quickly

2 Using the ICT tools would improve my job performance

3 Using the ICT tools would improve my productivity

4 Using the ICT tools would enhance my effectiveness on the job

5 Using the ICT tools would make it easier to do things

Ease of use

1 Use ICT tools for teaching and learning

2 Use of different instructional software packages

3 Use of different operating systems (Windows and Androids)

4 Use of e-mail and other internet resources






5 Using ICT skills in presenting information (Teaching)

Intention

1 I intend continued use of the ICT tools in the future

2 I believe it is worthwhile to use the ICT tools

3 I will use the ICT tools in the next few months

4 It is necessary to use the ICT tools in the future

5 I intend to collaborate with others to use ICT tools

Anxiety

1 I am afraid of using ICT technology

2 Using ICT tools is difficult to non technologist

3 I hate anything technology in my service

4 I don’t want to use ICT technology

5 ICT tools are very expensive

Attitude toward technology

1 I like using ICT tools

2 I want to participate in online discussion

3 I enjoy using ICT tools

4 I encourage others to use ICT tools

5 I can support any ICT incline activity

Acceptance

1 Integrate ICT in other discipline across the curriculum

2 Identifying and using available hardware

3 Solve common ICT problems relating to instruction

4 Prepare ICT-based learning materials

5 Use ICT for teaching and learning

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