Evaluation of Policies on Ban of Mobile Phone Usage by SHS Students on Campuses using an Analytical...

AFRICA DEVELOPMENT AND RESOURCES RESEARCH INSTITUTE (ADRRI) JOURNAL

ADRRI JOURNAL (www.adrri.org)

pISSN: 2343-6662 ISSN-L: 2343-6662 VOL. 10, No.10(2), July, 2014

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Evaluation of Policies on Ban of Mobile Phone Usage by SHS Students on Campuses using

an Analytical Hierarchy Process (AHP).

Frank Opoku1, Dawuni Mohammed2, Abdul-Aziz Ibn Musah3 and Abdulai Abdul-Hanan4

1Department of Information Systems and Decision Sciences, KNUST School of Business, Kwame

Nkrumah University of Science & Technology, Ghana. 2,3,4Department of Statistics, Mathematics and Science, Tamale Polytechnic, Tamale-Ghana.

2Correpondence: [email protected]

Received: 21st June, 2014 Revised: 25th July, 2014 Published Online: 30th July, 2014

URL: http://www.journals.adrri.org/

[Cite as: Opoku, F., Mohammed, D., Musah, A.A.I. and Abdul-Hanan, A. (2014). Evaluation of Policies on Ban of

Mobile Phone Usage by SHS Students on Campuses using an Analytical Hierarchy Process (AHP). Africa

Development and Resources Research Institute Journal, Ghana: Vol. 10, No. 10(2).]

Abstract The study seeks to evaluation of policies on ban of mobile phone usage by SHS students on campuses; an

analytical hierarchy process (AHP). The possible policy directions opened to school authorities in

achieving student discipline on mobile phone usage on campuses, alternative policies to the enforced

policy, reasons for noncompliance of students to the ban on mobile phone usage on campuses and an

alternative policy that will be benefit both school authorities and students are looked at. Questionnaires

were used to collect primary data from respondents, mainly educational experts (administrators), parents

and students of seven senior high schools in Ashanti Region and the results analysed using Expert’s

Choice for Windows 2007 and Excel. 36% of SHS students have stopped using their phones while on

campuses of which 16% stopped because of the ban. Allow students to carry specified cell phones on

campus and taught how to use them responsibly at specific time and places is beneficial to all players.

The effort of educational authority should be focused towards making cell phone usage on campuses

more friendly in a more responsible way rather than the current no cell at all policy which by all standard

unsustainable. Authorities must also realize that day in day out cell phones are becoming powerful than




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most of the personal computers stocked in our various learning institutions across the country and when

implemented effectively can help school authorities serve costs such as inventory, maintenance and

purchase.

Keywords: evaluation, policies, mobile phone, Senior High School (SHS) students, analytical hierarchy

process (AHP)

INTRODUCTION

A number of questions have arisen following the student unrest which took place at the Ghana

SHS (GHANASCO) in Tamale, Aduman SHS in Ashanti Region and the Navrongo SHS

(NAVASCO) in Navrongo in early 2010 all in relation to ban on mobile phone usage. A

publication captioned, ‚GES ban of mobile phones in SHS is unnecessary‛ (Modern

Ghana.com), June 2, 2010. , Radio and television discussions on the above problem show the

level of public interest in the matter at the time.

The importance of mobile phones cannot be overemphasized. Phones are use as calculators,

flash lights, web browsers, multimedia devices, cameras, television, radio, recorders, storage

devices, calendars, diaries, alarm clocks, date keepers, timers, broadcast devices, outside

broadcast tool or news gathering tool, crime monitors, aid to parents to keep touch with kids

and many more. Notwithstanding, these positives can easily be eroded by the negatives;

promotion of pornographic materials, increase of incidence of theft among students,

impersonation, over spending of time on phones rather on their books and many more if care is

not taken especially with the age bracket, 14 to 20 years pupils by (Mullen, 2006 cited in Clarene and William, 2007) .

Opinions are sharply divided on whether to ban the usage of mobile phone in the SHS or not,

even within school administrators, parents, and teachers. While many sees mobile phone as a

modern tool needed to develop students skills other think they are just to guided by the adults

such as their teachers and family to used the device in a more responsible manner of which they

will use anyway now or in the future.

In order to arrive at an optimal policy alternative so as to reduce the adverse effect of mobile

phone usage by SHS students, the study seek to adopt a scientific approach, analytic hierarchy

process (AHP) by Saaty (1980) to decomposes the decisional process in a hierarchy of criteria,

sub-criteria, attributes and alternatives through a set of weights that reflect the relative

importance of these alternatives. Lack of certainty of the effect of mobile phone usage on

students in SHS and lack of consensus among experts and stakeholders makes the use of AHP

more profound. AHP has become a significant methodology due to its capability for facilitating




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multi-criteria decision-making Ramanathan (2001). According to (Alphonce, 1997; Tiwary et al.,

1999; Duke et al. 2002; Ferrari, 2003), AHP has been widely applied to numerous complex

environmental and economic problems. Opinion of experts with an in-depth understanding of

the educational policies and their effects on students conduct is required. These experts do not

have to agree on the relative importance of the criteria or the rankings of the alternatives, but

each expert enters his judgments and makes a distinct, identifiable contribution to the issue.

In today’s democratic environment, management of organizations are increasingly in favour of

consensus based decisions rather than imposition of ideas on employee to promote high

productivity. Hahn (2002) stressed the need for a structured approach to decision making which

allows trade-offs after all perspectives are considered. Multi-criterion methods such as scoring

models, preference based methods; outranking methods, goal programming, and analytical

hierarchy process are effective in this scenario.

It is more practical to try to contain this inconsistency within reasonable limits, rather than to

eliminate it completely for a truer representation of the actual decision. A decision model which

is not overtly complex and uses simple human judgment to make the decisions is thus needed.

AHP is such a tool which breaks down a problem into smaller parts which can be easily

handled by a human mind.

Gray (1999) observes that, when scales for decision making are not consistent (units differing)

making decisions based on multi-criteria becomes complex and risky. However, Saaty (1999)

suggests that the use of a model that is not overtly complex, legitimately aggregates across

scales and addresses consistency in judgments from multiple participants. Common to most of

the multi-criterion methods require participants of high deductive capacity, and a human mind

would find it challenging to take into consideration the different trade-offs between the various

criterions under different circumstances. This consistency is difficult to maintain in the real

world.

The AHP process has been used for strategic evaluation of emerging technologies May et al.

(2006) and selection of R & D projects Duke and Aull-hyde (2002). In both evaluation and

selection there is considerable uncertainty about the future, and little statistical data is available.

The ultimate goal is to meet the strategic objective of the company. It can be said that these cases

are similar to the problem at hand: evaluate policies to eliminate the negative impact of mobile

phone usage on SHS students.

May et al (2003) demonstrate the application of AHP incorporating stakeholder preferences in

the complex task of forest planning. Bevilacqua M. and Petroni, (2002) described applying the

AHP to select the best maintenance strategy. Chan and Chan (2004) detailed the development of

a material handling equipment selection system involving AHP. AHP has also been used in

combination with other tools. . Chan and Chan further suggested that a decision support tool




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that includes a data structure to monitor the effectiveness of a decision, through the use of AHP,

cost-benefit analysis, and statistical analyses. Davis and Hersh (1998) used AHP in design

improvement by integrating it with Failure Mode Effect Analysis (FMEA). Lee et al. (2006) used

AHP in combination with fuzzy set theory for enterprise waste evaluation problem. Due to its

relative simplicity, AHP has been used in numerous applications with consistent results.

METHODOLOGY

This study adopted survey as its strategy. Questionnaires were administered to experts (SHS

administrators, formal administrators and lecturers) from randomly selected SHS, some parents

and students within K.M.A to score the relative importance of predetermined factors over the

aother. Secondary data was also collected mostly from the internet to facilitate the analysis of

the results using Excel for Windows program called Expert Choice for Windows. The study

focused on the Kumasi Metropolitan Assemble (K.M.A.) of the Ashanti Region. The region has

102 Senior High Schools (SHSs) and Secondary Technical Schools of which about 26 are private.

This study also adopted both qualitative and quantitative methods like stated in chapter one.

The nature of the problem is such that the necessary information needed were basically

opinions and views of experts and stakeholders. These views and opinions are then quantified

using a scale describing the relative importance of one factor over the other. This makes it

necessary to adopt both qualitative and quantitative methods to be able to answer the set

objectives. The results are presented quantitatively.

Simple random sampling technique was used to select seven (7) SHSs within K.M.A. 5 out of

about 22 public SHSs and 2 out of about 11 private SHSs. In each school, the

Headmaster/Headmistress, Assistant Headmaster/Headmistress Academic and

Domestic/Senior Housemaster/Housemistress were interviewed. Ten (10) students, five boys

and five girls who have at least used a cell/mobile phone in school before were interviewed in

each school. Two parents from each of the seven schools selected schools were also surveyed.

Were we did not get the two parents on campus to interview a contact number was solicited

from school’s administration.

Data was analysed by AHP using Microsoft Excel for Windows and Expert Choice for

Windows. AHP is a multi-criteria decision method that uses hierarchical structures to solve

complicated, unstructured decision problems, especially in situations where there are important

qualitative aspects that must be considered in conjunction with various measurable quantitative

factors.

AHP Axioms

AHP is founded on the following set of axioms for deriving a scale from fundamental

measurements and for hierarchical composition Saaty (1986).




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Axiom 1: Reciprocal

If element A is x times as important than element B, then element B is 1/x times as important

than elements A.

Axiom 2: Homogeneity

Only comparable elements are compared. Homogeneity is essential for comparing similar

things, as errors in judgment become large when comparing widely disparate elements.

Axiom 3: Independence

The relative importance of elements at any level does not depend on what elements are

included at a lower level.

Axiom 4: Expectation

The hierarchy must be complete and include all the criteria and alternatives in the subject being

studied. No criteria and alternatives are left out and no extra criteria and alternatives are

included.

AHP Procedure

Pairwise comparisons among n elements in each level lead to an approximation of each

iij

j

wa

w , 0ija , 1iia and ji <<<<<<<<<<<..<<<<<<.. (3.1)

Following Saaty (1980, 2000), the priorities of the elements can be estimated by finding the

principal eigenvector w of the matrix A (comparison matrix). The estimated weight vector w is

found by solving the following eigenvector problem:

maxAw w <<<<<<<<<<<<<<<<<<<<<<<<<<<. (3.2)

where the matrix A consists ofija ’s, and max is the principal eigenvalue of A. lambda ( ) is the

average of the consistency vector. When the vector w is normalized, it becomes the vector of

priorities of elements of one level with respect to the upper level. In cases where the pairwise

comparison matrix satisfies transitivity for all pairwise comparisons it is said to be consistent

and it verifies the following relation: If there is consistency between the pair of elements, then

ij ik kja a a and 1

ij

ji

aa

for all i j and k…<<<<<<<<<<<<<< (3.3)

The result is that max n and we have Aw nw , where n is the number of elements in each

row. Table 3.1 reports the pairwise comparison scale used in the AHP developed by Saaty

(1977). It allows converting the qualitative judgments into numerical values, also with

intangible attributes.




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Table 3.1 The AHAP pairwise comparison scale

Numerical

values

Verbal scale Explanation

1 Equally important for both elements Two elements contribute

equally

3 Moderate importance of one element over

another

Experience and judgment

favour

one element over another

5 Strong importance of one element over another An element is strongly

favoured

7 Very strong importance of one element over

another

An element is very strongly

dominant

9 Extreme importance of one element over

another

An element is favoured by at

least

an order of magnitude

2,4,6,8 Intermediate values Used to compromise between

two judgments

Source: Saaty (1977, 1980).

Saaty (1980) has shown that to maintain reasonable consistency when deriving priorities from

paired comparisons, the number of factors being considered must be less or equal to nine. AHP

allows inconsistency, but provides a measure of the inconsistency in each set of judgments. The

consistency of the judgmental matrix can be determined by a measure called the consistency

ratio (CR), defined as:

CICR

RI <<<<<<<<<<<<<<<<<<<<<<<<<<<<< (3.4)

where CI is called the consistency index and RI is the Random Index. Furthermore, Saaty (1980,

2000) provided average consistencies (RI values) of randomly generated matrices Table 3.3. CI

for a matrix of order n is defined as:

max

1

nCI

n

<<<<<<<<<<<<<<<<<<<<<<<<<<<. (3.5)

In general, a consistency ratio of 0.1 or less is considered acceptable this threshold is 0.08 for

matrices of size four and 0.05 for matrices of size three. If the value is higher, the judgments

may not be reliable and should be elicited again.




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Table 3.3. The average consistencies of random matrices (RI values)

Size (n) 1 2 3 4 5 6 7 8 9 10

RI 0.00 0.00 0.58 0.89 1.11 1.25 1.35 1.40 1.45 1.59

Source: Saaty (1980, 2008)

Once the local priorities of elements of different levels are available, in order to obtain final

priorities of the alternativesia , the priorities are aggregated as follows:

i k k iikS a w s a <<<<<.<<<<<<<<<<<<<<<<<<<. (3.6).

Assessment of alternative policies on Cell phone ban by SHS students on campuses

In order to evaluate alternative policies on cell phone ban by SHS students on campuses to

minimize the adverse impacts of cell phone on their lives, we have investigated the opinions of

twenty one educational experts, twenty eight parents and fourteen students by means of a

survey questionnaire. Experts do not necessarily have to agree on the relative importance of the

criteria of the rankings of the alternatives. Each expert entered his judgement and gave a

distinct, identifiable contribution to the issue.

For the case study, a four-level analytic hierarchy process has been applied, as shown in Figure

3.1. The first level is composed of the final goal one wishes to attain in carrying out the project:

minimization of the adverse impact of cell phone usage on SHS students in Ashanti region. The

second and third levels represent the criteria and sub-criteria on the basis of which the policy

options are to be evaluated:

C1 – Promotion of exam malpractice

C2 – Cyber bullying of fellow students

C3 – Allocations of too much time to calls specially deep into night to the neglect of

their books

C4 – Breakdown of good moral standing (misapplication of the device like viewing and

taking of pornographic materials)

Management of Ghana Education Service (GES) is aware that despite all these potential adverse

impact of cell phone usage, the device very important functions and uses and if care is not taken

these students would be denied off the benefits. Four important uses were broadly identified as

why students in SHS might need cell phones on campuses:

SubC1 – As aid for students to keep in touch with parents and relations

SubC2 – As aid during emergencies (example financial needs, health needs, etc.)

SubC3 – As a device for learning (example as device for internet accessibility, storage

device, picture taking etc.)




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SubC4 – As a device for developing the technology capabilities of students

The third level presents the policy options, which are:

A1 – Outright ban of all personal cell phones own by students on campuses and install

phone boots in dormitories and campuses

A2 – Allow students to carry specified cell phones on campus and taught how to use

them responsibly at specific time and places

A3 – Allow students to carry models of their choice and taught how to use them

responsibly to facilitate their learning at restricted places and time

A4 – Allow students to carry models of their choice and taught how to be responsibly to

facilitate their learning

Figure 3.1 Analytic Hierarchy Process of Policy directions which will reduce the adverse

impacts of cell phone usage by SHS students on campuses

Source: Adopted from Saaty’s cited in Qureshi & Harrison

RESULTS

Demography of student respondents

Of the 70 students’ respondents, 74.3% are within (18 – 20) years, 21.4% are within (15 – 17)

years and the rest of the 4.3% are within (21 – 23) years.

Goal (Policy direction which will reduce the adverse

impacts of cell phone usage by SHS students on campuses)

C1 C4 C3 C2

SUBC2

A1

SUBC1 SUBC3 SUBC4

A2 A3

A4

Goal

Criteria

Sub-criteria

Options




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Of the 70 students’ respondents, 84.4% of the students said their cell phones were important to

them academically and 15.6% said their cell phones were not important (not use for academic

purpose) to them academically.

What students use their cell phones to do?

Again, 70 out 70 respondents use their cell phones for both ‘voice calls’ and ‘text messaging’

each. 52 out of 70 use their cell phones for ‘internet browsing’. 39 out of the 70 use their cell

phones for ‘radio/audio recording’ and 28 out of 70 use their devices to take ‘pictures and

capture video’.

Awareness and effects of cell phone usage.

Of the 70 respondets 33 think cell phone usage has some negative effects on their lives and 53%

do not think cell phone usage has any negative effects on their lives.

Of the 33 respondents who think cell phone usage has some negative effects on their lives, 24

mentioned ‘less sleep due to calls made deep into the night’ 20 mentioned ‘extra financial

burden’18 mentioned addiction to ‘watching of pornographic pictures and videos’, 9 mentioned

‘health consequences (itching of ears, impaired hearing)’ 3 mentioned ‘encouragement of theft

among students’

22 of the 33 respondents have ‘made calls deep into night’ before, 20 out of the 33 have suffered

‘extra financial burden’, 15 out of the 33 have ‘watch pornographies’ with their cell phones

before, and 5 said they have experienced ‘health problems’.

Parents

Of the 35 parents 31.4% strongly agreed with the ministry’s directive on the ban, 37.2% agreed,

20% disagreed and 11.4% strongly disagreed with the directive.

Experts Views (Educational administrators)

Of the 19 school management respondents, 42% described the rational of the ban as very

important, 37% described it as important, and 11% each described it as normal and

unimportant.

On the issue of compliance, all of the 19 respondents said the ban has not been complied with

by students.

Reasons for noncompliance

At their age students always want to be in touch with parents and family members

while in school (unedited). Many others fall under this category.

Students use their phones to engage in examination malpractices (unedited). Many other

responses fall under this category.

School authorities are not committed enough to enforcing the ban by turning blind eyes

to culprits(unedited)




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Students always protect each other by failing to expose culprits (unedited)

Unavailable of suitable alternative communication modes on various campuses and

dormitories (unedited)

Students are generally recalcitrance always want to go in the opposite direction to the

pursuit of administration (unedited)

It is their era. There is little we can do about it we rather have to concentrate on

educating them on how to be more responsible with the devices (unedited)

Some of these students are adults and they know what they are about. We all know how

difficult it is to stay without your cell phone once one begin using one (unedited)

Students claim they need them for emergency situations. Many responses fall under this

category

Some parents want to keep in touch with their wards all the time while they are in

school

Students need cell phones for unknown ill-motives

The cost of using these installed phone boots is higher than using one cell phone

(unedited)

Sometimes teacher – student relationships makes it difficult to enforce the ban. Many

other responses fall within this category

Some teachers do not share the opinion of the ministry view

The device aid students in their academic work

They use the phone to entertain themselves rather than learning

From the above information, it follows that the reasons for non compliance to the ban varied.

While some are attributable to students own agendas, parents and teachers interest also

accounts for the non compliance. Others are seen as good reasons while others are seen as ill

motives.

When respondents were asked if they are in fully support of the current ‚no cell phone at all‛

policy subscribed to by GES, 11out of 19 said ‘no’ they do not and 8 out of 19 said ‘yes’ they are

in fully support to the ban.

Policy alternatives opened to school authorities on mobile phone usage on campuses.

Of the experts and school administrators sampled, the various policy directions opened to

management for the enforcement sanity on cell phone usage by SHS students on campuses are:

1. Outright ban of all personal cell phones own by students on campuses and install phone

boots in dormitories and campuses (Alternative A).

2. Allow students to carry models of their choice and taught how to use it responsibly to

facilitate their learning at restricted places and time (Alternative B).




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3. Allow students to carry specified cell phones on campus and taught how to use them

responsibly at specific time and places (Alternative C) and.

4. Allow students to carry models of their choice and taught how to be responsibly to

facilitate their learning (Alternative D).

Relative weights of the alternative policies

Total weighted evaluations are shown on Table 4.2. The policy option A3 receives the highest

importance (more than 50%); A4 is the second-best option (19%), slightly more important than

A1 (16%) and A2 (13%).

Table 4.2 Factor Weights for alternatives

Policy Alternative Total Weighted evaluations

Alternative A1 0.1617




Source: Survey, 2012

From the above results, there is an indication that the highest importance is to the alternative A3

‚Allow students to carry specified cell phones on campus and taught how to use them

responsibly at specific time and places‛ (51.7%); the other two criteria ‚Outright ban of all

personal cell phones own by students on campuses and install phone boots in dormitories and

campuses‛ and ‚Allow students to carry models of their choice and taught how to be

responsible with the device to facilitate their learning‛ have almost equal priority (about 20%)

and the final alternative ‚Allow students to carry models of their choice and taught how to use

it responsibly to facilitate their learning at restricted places and time‛ has priority choice off

about (10%).

Sensitivity analysis to test under which conditions the ranking of alternatives may change. The

method has involved specifying a certain number of experiments, which set different possible

combinations of the criteria’ weights (Harrison et al., 1993). In particular, the weight of any

criteria i,iw , has been supposed to evolve according to the stochastic differential equation:

ii i idw w dt w dz

This equation implies that iw are changing according to a process of geometric Brownian motion

(GBM). The term dt is the mean or expected percentage change in iw for the increment dt , and

μ is called the mean drift rate. The term dz introduces a random component to the drift,

because dz= t dt , where t is a normally distributed random variable with 0 mean and




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standard deviation of 1. A discrete approximation of the equation shown above is given by the

stochastic difference equation:

, 1 , , 11i t i t i t tdw w w

Where 1t the standard normal variants and the implied increment are is 1dt . Given the base

weights vector of the criteria in table 3 and the values for μ and σ, selected from the standard

normal distribution defined for the 95% confidence interval, we have generated sample paths of

100 random numbers for any criteria.

The sensitivity results indicated that all possible combinations of increasing and decreasing,

reported in Table 4.3, which reports the mean percentage change in each alternative and the

standard deviation across the 100 random samples, suggests that the results are relatively

robust to different combinations of the weights’ values. In fact, the mean percentage change is

very low, as well as the standard deviation tend to be quite small. Moreover, analysing the

sample probability of the ranking of alternatives, we have found that A3 is always the best

option, and the change in the ranking of alternatives is due mainly to the fact that A1 becomes

slightly more important than both A4 (30% of cases) and A2 (10% of cases).

Table 4.3 Sensitivity analysis of policy options

Mean % Standard deviation

A1 4.065 0.012

A2 4.124 0.006

A3 4.006 0.034

A4 4.232 0.009

Source: statistics computed from survey, 2012

Dantzig (1963) the benefit of doing a sensitivity analysis is too paramount to be ignored in

applications of the weighted sum model (WSM), the weighted product model (WPM), and the

analytic hierarchy process (AHP) to real-life problems. As stated it: "Sensitivity analysis is a

fundamental concept in the effective use and implementation of quantitative decision models,

whose purpose is to assess the stability of an optimal solution under changes in the

parameters."

DISCUSSIONS OF RESULTS

Students who are the subject of discussion think cell phones are of important to their education.

Uses of the handsets included; making voice calls, sending and receiving of text messages,

browsing of the internet, data storage and as an audio/radio. It is important to mention that the

students themselves admitted the devices are abused sometimes. The vices they mentioned

included; financial burden on the addictions to watching of pornographies, health problems

and increase of phone theft cases among students.

Majority of parents support the band but up to 31% of the parents are still willing to buy cell

phones to students. This means some children still has the support of their parents on using cell




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phones on campuses. Against the ban policy is bound not to succeed because the implemented

of the policy are not in full support of the ban policy. The 58% school administrators who do not

fully support the current cell phone usage by students cannot be seen to be effectively enforcing

the ban. Some parents want their wards to own their personal cell phones in SHS and will

therefore provide for their wards with cell phones.

Whatever the reasons are, all these players must buy into the decision of dealing with the

problem of ownership of cell phones students in secondary schools.

School administrators’ reasons for the non compliance are follows:

The assertion by school administrators that students will always want to contact parents and

family members while in school indicates they do acknowledge the need for them owing cell

phones.

Again, they believe that students always want to use their phones to engage in examination

malpractices should not be too much a reason for the ban. Instead proactive measures should be

employed to counter any attempt to cheat in examination. To hit the nail on the head some

school administrators accepted that they themselves are not committed enough to enforcing the

ban by turning blind eyes to culprits.

Unavailability of suitable alternative communication modes on various campuses and

dormitories are also the reason for the noncompliance of the current no cell phone at all policy

been articulated by GES. Students are generally recalcitrance and will always want to go in the

opposite direction to the pursuit of administration.

The ranking of the policy options with respect to the ultimate goal of evaluating the ban of cell

phone usage on SHS campuses by students indicate that the most important policy alternative

to the current policy is A3. That is ‚Allow students to carry specified cell phones on campus

and taught how to use them responsibly at specific time and places‛ (51.7%); the fourth

alternative, A4‚Allow students to carry models of their choice and taught how to be responsible

with the device to facilitate their learning‛ (18.7%) is also ranked better than the current

‚Outright ban of all personal cell phones own by students on campuses and install phone boots

in dormitories and campuses‛ (16.2%) and the final alternative ‚Allow students to carry models

of their choice and taught how to use it responsibly to facilitate their learning at restricted

places and time‛ (13.4%) is ranked less important to the current policy.

Sensitivity analysis indicated that the results are consistent. It implies that the results are stable

over a certain range of variation of the weights values assigned to the various criteria. It also

means that respondents were consistent in expressing the views. The mean percentage change

in each alternative and the standard deviation across the 100 random samples, suggests that the

results are relatively robust to different combinations of the weights’ values. In fact, the mean

percentage change is very low, as well as the standard deviation tend to be quite small.




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Moreover, analysing the sample probability of the ranking of alternatives, we have found that

A3 is always the best option, and the change in the ranking of alternatives is due mainly to the

fact that A1 becomes slightly more important than both A4 (30% of cases) and A2 (10% of

cases).

CONCLUSIONS

The reasons for students noncompliance with cell phone ban in various SHS campuses are:

students seeing the device to be useful for their academic career, parents not been generally

supportive of the directive and SHS adminsitrators not in total agreement with the current ‚no

cell phone at all‛ policy.

The various policy directions opened to school authorities are: Outright ban of all personal cell

phones own by students on campuses and install phone boots in dormitories and campuses,

allow students to carry specified models of cell phones on campus and taught how to use them

responsibly at specific time and places, allow students to carry models of their choice and

taught how to use it responsibly to facilitate their learning at restricted places and time and

allow students to carry models of their choice and taught how to be responsibly to facilitate

their learning.

Amongst the alternative policies, allow students to carry specified cell phones on campus and

taught how to use them responsibly at specific time and places has been assessed as the best

option to pursue to reduce the adverse impacts of cell phone usage on students of SHS.

Authorities of GES must come to the realization that the issue of technological development of

the nation has reach a stage where both adults and children are finding it even more difficult to

do without it. The effort should therefore be gear towards making cell phone usage on

campuses more friendly in a responsible way rather than the current no cell at all policy which

by all standard unsustainable.

Authorities must also realize that day in day out cell phones are becoming powerful than most

of the personal computers stocked in our various learning institutions across the country. There

are cell phones with higher processors and speed than our PCs. Ensuring that students use

these devices in the best possible ways would help the institutions in a number of ways. First

cost of acquiring and maintenance of these devices would be saved. Cost of providing the

infrastructure for housing of these PCs would also be saved. Information would have been

closer to the students using their cells than PCs which are likely to be locked up somewhere

after a certain period of the day.

ACKNOWLEDGMENT

Our first appreciation goes to Dr. Bashiru Imoro Ibn Saeed, Statistics Department, Kumasi

Polytechnic for his constructive criticisms, suggestions and advice that led to the completion of

this paper.




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We also appreciate the contributions of all staff of the Statistics, Mathematics and Science

department of Tamale Polytechnic.

REFERENCE

Alphonce C.B., 1997. Application of the analytic hierarchy process in agriculture in developing

countries. Agricultural Systems 53, 97-112.

Bevilacqua M. and Petroni, A., (2002) Traditional Purchasing to Supplier Management: A

Fuzzy Logic-Based Approach to Supplier Selection, International Journal of Logistics:

Research and Applications, 5 (3), pp. 28-46.

Chan, F.T.S & Chan, H.K., (2004) Development of the Supplier Selection Model- A Case Study

in the Advanced Technology Industry, Journal of Engineering Manufacture, 218, pp.

1807-1823.

Clarene J. and William A. K (2007), National Forum of Educational Administration and

Supervisions Journals Volume 25, Number 4, 2007.

Dantzig, G.B. (1963). Linear programming and extensions. Princeton, NJ: Princeton University

Press.

Davis, P. J. and Hersh, R., (1998). Descartes Dream, Harcourt Brace and Jovanovich, New York.

Duke J. M., Aull-hyde R., 2002. Identifying public preferences for land preservation using the

analytic hierarchy process. Ecological Economics 42, 131-145.

Ferrari P., 2003. A method for choosing from among alternative transportation projects,

European Journal of Operational Research 150, 194-203.

Gray, M. L. (1999). To: All search committees From: A stymied job seeker Re: How about some

respect? Chronicle of Higher Education 45(43), B9.

Hahn, E. D. (2002). Better decisions come from a results-based approach. Marketing News,

36(19), 24.

Lee A.H.I., Kang, H.Y., Wang W.P., (2006) Analysis of Priority Mix Planning for Semiconductor.

May A.D., Jopson A.F., Matthews B., 2003. Research challenges in urban transport policy.

Transport Policy 10, 157-164.

May A.D., Kelly C., Sheperd S., 2006. The principles of integration in urban transport strategies.

Transport Policy 13, 319-327.

Ramanathan R., 2001. A note on the use of the analytic hierarchy process for environmental

impact assessment. Journal of Environmental Management 63, 27-35.

Saaty T. L., 1980. The analytic hierarchy process: planning, priority setting and resource

allocation. McGraw-Hill, New York.

Saaty, Thomas L. (1999). Decision making for leaders: The analytic hierarchy process for

decisions in a complex world. 3rd. Pittsburg: RWS Publications. ISBN 0-9620317-8-X. 315

p.




16

Saaty, T. L., Vargas, L. G. And Whitaker, R., (2008). Addressing Criticisms of the Analytic

Hierarchy Process, (in publication).

Tiwari D.N., Loof R., Paudyal G.N., 1999. Environmental-economic decision-making in lowland

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