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Towards the Adoption of a Sentence Computation Collaborative
Mobile App for Eective Correctional/Oender Management
Chukwunonso Henry Nwokoye∗
ABM College, Canada
chinonsonwokoye@gmail.com
Chukwuemeka N. Etodike
Madonna University
nelsonetodike@gmail.com
Evelyn Nwafor
Nnamdi Azikiwe University, Nigeria
evelynuchechukwu@gmail.com
Ikenna Ihemelu
Nnamdi Azikiwe University, Nigeria
ikennaihemelu@gmail.com
ABSTRACT
Recently, correctional facilities meant for oender reformation have
been left out of technological advances pertaining to mobile appli-
cation development and human computer interaction. Designed
to basically aid oender management, the sentence computation
application (ScApp) is essentially a mobile collaborative platform
for sentence calculation, oender information collection and stor-
age, processing, searching, and notication. Therefore, the study is
aimed at evaluating the behavioral aspects of correctional sta’s
adoption of ScApp using the unied theory of acceptance and use
of technology (UTAUT). The study comprised 69 participants who
are ocers of the Nigerian Correctional Service, selected through
a multi-stage sampling technique. Based on ve-point rated re-
sponses of correctional ocers, the internal consistency of the
ScApp was assessed using Cronbach’s Alpha reliability analysis
after deriving the zero-order inter-item correlation. The results
showed that the independent contributions of anxiety, facilitat-
ing conditions, and attitude towards technology are predictors of
participants’ behavioural intentions to use the ScApp.
CCS CONCEPTS
•Human-centered computing;•Human computer interac-
tion (HCI);•HCI theory, concepts and models;
KEYWORDS
Technology acceptance, Mobile applications, UTAUT model, Smart-
phone, Correctional management, oenders
ACM Reference Format:
Chukwunonso Henry Nwokoye, Chukwuemeka N. Etodike, Evelyn Nwafor,
and Ikenna Ihemelu. 2023. Towards the Adoption of a Sentence Computation
Collaborative Mobile App for Eective Correctional/Oender Management.
In 4th African Human Computer Interaction Conference (AfriCHI 2023), No-
vember 27–December 01, 2023, East London, South Africa. ACM, New York,
NY, USA, 7 pages. https://doi.org/10.1145/3628096.3629042
∗Corresponding author.
Permission to make digital or hard copies of all or part of this work for personal or
classroom use is granted without fee provided that copies are not made or distributed
for prot or commercial advantage and that copies bear this notice and the full citation
on the rst page. Copyrights for components of this work owned by others than the
author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or
republish, to post on servers or to redistribute to lists, requires prior specic permission
and/or a fee. Request permissions from permissions@acm.org.
AfriCHI 2023, November 27–December 01, 2023, East London, South Africa
©2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.
ACM ISBN 979-8-4007-0887-9/23/11. . . $15.00
https://doi.org/10.1145/3628096.3629042
1 INTRODUCTION
Sophisticated advancements in Information and Communication
Technologies (ICT), particularly for smart mobile devices and appli-
cations, have had far-reaching and mind-boggling inuence on our
daily lives [
1
,
2
]. Instances of ICT exist as cloud computing, Internet
of Things, big data, as well as mobile telephony and communica-
tions [
3
]. The smartphones are now widely utilized in a variety of
settings, including workplace, education, amusement, communi-
cation, nursing and healthcare [
2
,
4
,
5
]. The rapid expansion and
pervasiveness of ICT juxtaposes with the relatively sluggish sci-
entic evaluation of its product oerings, since ICT studies can
scarcely keep up with digital industry and consumer expectations
[
2
,
6
]. This is especially noticeable in the creation of mobile applica-
tions (apps) for diverse areas. Downloads of these mobile apps have
been rising rapidly across the globe [
7
]. Mobile communication plat-
forms are transportable and pervasive technology, and consumers
have a deep personal contact with the gadgets involved [
8
]. Such
mobile services are linked with other variety of applications rang-
ing from internet infrastructure to software and the communication
apparatus. Beside mobility, versatility, convenience, and eective-
ness are some of the characteristics that help address related daily
issues or fulll the desires of their customers [
8
]. Other notable
services available today include information access and transaction
authorization ticket booking, order monitoring, online banking,
and record authentication), mobile payment [
8
] and promotion of
physical activity [9].
This submission template allows authors to submit their papers
for review to an ACM Conference or Journal without any output
design specications incorporated at this point in the process. Al-
though the literature is cluttered with the intense research eorts
for mobile application development, few have been seen to aect
oenders and correctional facilities. Notwithstanding the enormous
importance that correctional facilities represent in every society,
little or no research has been conducted on how correction ocers
and oenders might benet from technological advancements [
10
].
There exists a desktop application for correctional management in
several countries, Nigeria inclusive [
11
]. Despite the reformative
agenda of the Federal Government of Nigeria on Criminal Justice
Administration [
12
], it was discovered that sentence computation
has remained problematic, most times leading to miscarriage of
justice with some inmates serving wrong sentences as a result of
human error and inecient conventional computational methods.
Given this problem, a mobile application for sentence computa-
tion (ScApp) [
13
] was designed to reduce and mitigate human and
AfriCHI 2023, November 27–December 01, 2023, East London, South Africa Henry Nwokoye et al.
Figure 1: ScApp for NCS [13]
bureaucratic factors which usually trail sentence computation in
correctional facilities throughout Nigeria (Figure 1). ScApp is a
computing mobile collaboration platform comprising of interactive
tools for assisting the operations of jail ocials and the friends and
families of prisoners.
In the words of Nwokoye, et al. [
13
], "the software eliminates
the need for manual calculations and book-based documentation,
the overloaded responsibility of both the records and welfare o-
cers, the lack of third-party audit/check for calculated discharge
dates, no knowledge of entry patterns of convicted prisoners in
the prisons, and the breakdown of communication in the prison
community. The advantages of the online platform include an auto-
mated method of auditing and reviewing the computed dates, timely
information about convicts and their punishments, and improved
decision making by prison administration at all levels (state, zones,
and national). Furthermore, the program will give an automatic
method of alerting and notifying the inmate’s friends and relatives
of the day and hour of release".
On the other hand, human behavior and intentions to use infor-
mation technology have been a hot research topic in the eld of
information systems ever since the mid-20th century, and a number
of information technology acceptance models have been developed
[
14
,
15
]. The most widely used information technology acceptance
models are the Technology Acceptance Model (TAM) and the Uni-
ed Theory of Acceptance and Use of Technology (UTAUT) [
14
,
16
].
In light of the above, the focus of this paper is to evaluate the behav-
ioral aspects of the ScApp mobile application aecting correctional
sta’s adoption for computation of inmate sentences by making
use of a renowned technology adoption model (TAM), i.e., the uni-
ed theory of acceptance and use of technology (UTAUT). The
remainder of the paper is structured as follows: The second section
is the review of pertinent literature and hypothesis development.
The third section contains the research methodology for the study.
The fourth section discusses the major ndings and results of the
UTAUT analysis. Finally, the fth section contains discussion, con-
clusion, and future directions.
2 RELATED WORKS
Prominent amongst them is the UTAUT, which was developed and
veried by combining components from 8 important theories rel-
evant to the issue and comparing them empirically [
15
]. In fact,
UTAUT is the result of the integration of various ideas and mod-
els including Theory of Reasoned Action, Technology Acceptance
Model, the Motivational Model, Theory of Planned Behavior, the
Decomposed Theory of Planned Behavior, the Model of PC Utiliza-
tion, Innovation Diusion Theory, and Social Cognitive Theory [
17
].
According to the ndings, the new model served as an essential
management tool for assessing and developing strategies for im-
plementing emerging innovations and technologies [
8
]. Electronic
and mobile instances of banking [
18
,
19
], technology for academia
[
20
], books [
21
], restaurant [
17
], payment for telecom service [
8
],
governance [
22
], document workow [
23
], business-related social
media [
1
], tour mapping [
24
], travel [
25
], and health [
2
,
4
,
26
] are
some of the technological areas that have been deployed in adop-
tion scenarios utilizing the UTAUT paradigm. This is owing to the
UTAUT’s robustness, completeness, statistical validity dependabil-
ity, and correctness in predicting technology adoption in many
disciplines and in varied technology settings [
27
]. UTAUT analyzes
the impact of four elements on users’ behavioral intentions: per-
formance expectation (PE), eort expectancy (EE), social inuence
(SI), and facilitating circumstances (FC) [
15
] Reviewing UTAUT
literature, and buttressing its essentiality, researchers suggest that
this concept was hugely noteworthy since it endured painstaking
empirical validation and prompted additional theoretical research
in technology adoption and application [4, 15, 28].
Therefore, it is universally acknowledged as a helpful paradigm
for studying ICT adoption across contexts. Consequently, it is hy-
pothesized that this model may indeed be utilized to comprehend
behavioral intention towards the use of ScApp by correctional of-
cials in NCS. The study argues that facilitating conditions (FC),
attitude towards technology (AT), anxiety (AX) may have signif-
icant eect on the behavioural intention (BI) to use the ScApp
technology.
2.1 Hypothesis Development
In the light of denitions of the UTAUT constructs [
15
,
17
], we
present the hypotheses of the study. Performance expectancy (PE)
is the extent to which utilizing a technology will help customers
while doing particular tasks. Eort Expectancy (EE) is described
as the degree of ease with which a particular information technol-
ogy may be used. Attitude towards using technology (AT) refers
to an individual’s disposition towards accepting, using, and recom-
mending technology. Social Inuence (SI) is the extent to which a
consumer believes that relevant individuals feel he or she should
utilize a particular information technology. Facilitating conditions
(FC) are based on the idea that technological assistance in terms
of operational requirements and supportive infrastructure will be
accessible to accomplish an ICT-required activity. Self-ecacy (SE)
is described as a person’s perceived competence to use certain new
technologies [
3
]. Anxiety (Ax) is the degree of uneasiness and men-
tal tension caused by utilizing technology [
29
]. Table 1 contains
the details of the constructs, items, and observed variables in the
study. The hypotheses of the study are as follows:
Towards the Adoption of a Sentence Computation Collaborative Mobile App for Eective
Correctional/Oender Management AfriCHI 2023, November 27–December 01, 2023, East London, South Africa
Table 1: The details of the constructs, items, and observed variables in the study
Construct Items Observed variables
Performance Expectancy PE1 ScApp is benecial to overall sentence computation
PE2 ScApp will allow eective management of sentence data
PE3 ScApp will increase sentence documentation eciency
PE4 ScApp reduces data errors inherent in manual computation
PE5 ScApp ensures more accuracy and trust of stakeholders
Eort Expectancy EE1 Use of ScApp is simple and understandable
EE2 ScApp is easy and user friendly
EE3 It is easy to gain mastery of the ScApp with a short time
EE4 Operating ScApp has simple procedures
EE5 ScApp saves me time to attend to other responsibilities
Attitude towards using Technology AT1 ScApp is a brilliant idea
AT2 The features of ScApp such as notication make its use interesting
AT3 Using ScApp interactive mechanisms is fun
AT4 ScApp helps me to work better
Social Inuence SI1 My colleagues at work think using ScApp is a great idea
SI2 My superiors are suggestive of the use of ScApp
SI3 Inmates feel that the use of ScApp saves them from errors
SI4 Inmates’ next of kin feel ScApp is transparent and thus suggest its use
Behavioral Intention to use Technology
BI1 I intend to use ScApp in the future
BI2 I will like to use ScApp when it is available
BI3 I plan to maximize the features of ScApp for greater eciency in my work
Facilitating Conditions FC1 I use smart phone
FC2 There is organizational internet services for work
FC3 I can navigate with ease through such applications
FC4 ScApp is compatible with smart phones
FC5 There is steady power supply in my organization
FC6 I can access help easily within the organization if I have diculty with ScApp
Self-Ecacy SE1 I can use ScApp even without assistance
SE2 With ScApp I can complete computation and send notication
SE3 If I need assistance for something unusual in ScApp, I will denitely ask
SE4 With user guide, my learning experience of ScApp is facilitated
SE5 I trust myself to be able to navigate dicult functions associated with
Anxiety AX1 I am nervous about making mistakes while using ScApp
AX2 ScApp feels awkward and I may never get used to it
AX3 I am afraid of making mistakes in ScApp may aect my job
AX4 I am scared because I may lose information using ScApp
Hypothesis 1 (H1). Performance expectancy positively predicts
the intention to use ScApp.
Hypothesis 2 (H2). Eort expectancy positively predicts the in-
tention to use ScApp.
Hypothesis 3 (H3). The attitude towards using technology posi-
tively predicts the intention to use ScApp.
Hypothesis 4 (H4). Social Inuence positively predicts the inten-
tion to use ScApp.
Hypothesis 5 (H5). Intention to use positively aects the individ-
ual use of ScApp.
Hypothesis 6 (H6). Facilitating Conditions positively predicts
the intention to use ScApp.
Hypothesis 7 (H7). Self-Ecacy positively predicts the intention
to use ScApp.
Hypothesis 8 (H8). Anxiety negatively predicts the intention to
use ScApp.
3 METHODS
Participants: The inclusion criteria for the study comprised 69 par-
ticipants who were ocers of the NCS, Anambra state command,
Nigeria, for not less than 2 years. This period allows for orientation
and deployment of ocers to units and departments. Note that
orientation is mostly in-service training conducted at training col-
leges, where the manual ways of sentence computation are taught.
Considering the nature of the population, a multi-stage sampling
technique was employed in selecting the participants. Purposive
sampling was used in selecting the command. Cluster sampling was
used in selecting the participants’ units and departments, whereas
simple randomization was utilized to select the nal participants
AfriCHI 2023, November 27–December 01, 2023, East London, South Africa Henry Nwokoye et al.
Table 2: Zero Order Inter-Item Correlation Matrix
PE EE AT SI FC SE AX BI
Performance Expectancy (PE) 1
Eort Expectancy (EE) .485** 1
Attitude to Technology (AT) .488** .850** 1
Social Inuence (SI) .390* .817** .811** 1
Facilitating Condition (FC) .408* .667** .664* .605** 1
Self-ecacy (SE) .445** .624** . 507** .539** .339* 1
Anxiety (AX) - .480** -.779** -.771** -.712** -.745** -.565** 1
Behavioural Intention (BI) .530** .789** 797** .654** .819** .500** -.824** 1
*Signicant at p < 0.05, **signicant at p < 0.01, n=69
Table 3: Internal Consistency of ScApp
Constructs A X SD N
Performance Expectancy (PE) .74 9.89 5.2 69
Eort Expectancy (EE) .87 9.33 4.3 69
Attitude towards Technology (AT) .95 8.02 4.5 69
Social Inuence (SI) .71 7.39 3.5 69
Facilitating Condition (FC) .91 11.40 5.4 69
Self-ecacy (SE) .70 9.78 4.6 69
Anxiety (AX) .95 8.18 4.6 69
Behavioural Intention (BI) .89 6.42 4.1 69
for the user study. The participants were mostly chosen from the
Records and the Welfare units. Table 2 holds the zero-order inter-
item correlation. The zero-correlation matrix in Table 2 is indicative
that the seven constructs correlated with ocers’ behavioural in-
tention to use ScApp. However, the matrix is indicative that there
is an elevated correlation between facilitating conditions, attitude
towards the use of technology, and ocer anxiety as per the use of
technology. The elevation will require further analysis in order to
establish them as predictor factors of behavioural intention to use
ScApp.
Measurement: The items that make up the ScApp questionnaire
were developed by the authors following an elaborate review of
literature on user-related challenges and problems attendant to the
introduction of IT applications (e.g., ScApp) aimed at modifying
work methods and processes for performing job tasks. Based on
ve-point rated responses of designated users (correctional ocers),
the internal consistency of the ScApp was assessed (Table 3). The
pilot study reported the following internal consistency. Internal
consistency was assessed using Cronbach’s Alpha reliability analy-
sis (Table 2) to analyze the items that make up each construct in
the subscales. Sample items for each of the constructs include: "Sen-
tence compute will allow eective management of sentence data"
(PE), "Use of ScApp is simple and understandable" (EE), "Sentence
compute helps me to work better" (AT), "My colleagues at work
think using ScApp is a great idea" (SI), "I would like to use ScApp
when it is available" (BI), "ScApp is compatible with smart phones"
(FC), "I trust myself to be able to navigate dicult functions associ-
ated with sentence compute" (SE), and "I am nervous about making
mistakes while using ScApp" (AX).
Procedure: Consent approval was obtained from NCS before engag-
ing the participants in the user studies. Participants were exposed to
a prototype application which was installed on the authors’ mobile
phones and were asked to respond to the user problems which may
be associated with the application if it is deployed at their place
of work as a new method of documenting and executing sentence
computation in the NCS. From literature, user-associated problems
and challenges which could hamper behavioural intention to use
technology were grouped into 7 constructs corresponding to 8 sub-
scales in the questionnaire, namely: performance expectancy (PE),
eort expectancy (EE), attitude to technology (AT), social inuence
(SI), facilitating conditions (FC), self-ecacy (SE), anxiety (AX), and
behavioural intention to use technology (BI). Participants’ personal
information and demographics were also recorded.
4 RESULTS
In order to ascertain whether behavioural intention to use this
technology (ScApp) was inuenced by the proposed UTAUT con-
structs, a test for predictability was performed using a stepwise
regression model (Table 4). The stepwise regression model enabled
determination of how the user’s behavioural constructs could im-
pact the behavioural intention to use technology and the weight
of predictability would help ascertain which factors would impact
the behavioural intention to use technology the most, thus, en-
abling technology redesigns and enhancements. Regression analy-
sis performed revealed the following R2 (Adjusted) and beta weight
coecients.
a. Predictors: (Constant), Anxiety
Towards the Adoption of a Sentence Computation Collaborative Mobile App for Eective
Correctional/Oender Management AfriCHI 2023, November 27–December 01, 2023, East London, South Africa
Table 4: Model summary indicating a.R2 predictive contribution of user factors on behavioural intention to use technology
R R2Adjusted R Std Error
Square Estimate R Square
Change
F Change df1 df2 Sig. F Change
Model 1 .824a.679 .674 1.31417 .679 141.415 1 67 .000
Model 2 .880b.774 .767 1.11100 .095 27.746 1 66 .000
Model 3 .901c.811 .803 1.02219 .038 12.966 1 65 .001
Figure 2: Conceptual model Key: FC
=
Facilitating Condi-
tions, AT
=
Attitude towards Technology, AX
=
Anxiety, BI
=
Behavioural Intention to Use Technology: a
=
relationship
of FC+AT, b
=
relationship of FC+AX, c
=
relationship of AT+
AX
b. Predictors: (Constant), Anxiety, Facilitating Conditions
c.
Predictors: (Constant), Anxiety, Facilitating Conditions, At-
titude Towards Use of Technology
d.
Dependent variable: Behavioural intention to use technology
Given the extant support in literature as regards the psycholog-
ical underpinning of technology acceptance, adoption and usage,
the organizational climate of the NCS and the background of the
NSC ocers at the Anambra Command, the authors proposed that
FC, AT, and AX will most predict ocers’ acceptance, adoption,
and use of ScApp as an eective means of sentence computation in
the Command. The model is depicted in Figure 2 below.
The model conceptualized that FC (.40), AT (.31) and AX (-.29)
predicted BI. More so, AX was inuenced by FC and AT as in b &
c respectively, while AT was equally inuenced by FC as depicted
in a. The conceptual model showed a signicant correlation (a, b,
c) among factors. AT, FC positively and signicantly predicted BI,
whereas AX negatively and signicantly predicted BI, and thus, AT,
FC, and AX =BI.
The preliminary results of the user studies (for predictor contri-
butions) as indicated by adjusted R2 produced 3 models (a, b, c) as
predictors of behavioural intention to use technology with anxiety
(AX) contributing 67.4% (a.R2
=
.674) explanation of user factors
which predict behavioural intention to use technology. When facili-
tating conditions (FC) were added to the previous yielding model 2,
predictability as shown by a.R2 increased to 0.767, an indication that
facilitating conditions (FC) contributed 9.5% of the independent ex-
planation to the user factors. Furthermore, in model 3, participants’
attitude towards technology (AT) also proved to be an important
user factor for ScApp as it contributed 3.8% explanation to the user
factors at a.R2
=
0.803. The a.R2 change was equally conrmed at p
< .05 respectively for the 3 model contributions. Although PE, EE,
SE and SI correlated positively with BI, they were excluded from
the accepted model (model 3) as the correlation did not have pre-
dictive impact on behavioural intention to use technology. Given
these outputs, and to accept the model factors as predictors, beta
weight coecient analysis was further performed and the result
are reported in Table 5 below.
Testing the 3 models for signicant predictive eects on be-
havioural intention to use technology, beta weight coecient anal-
ysis revealed that the user factors (anxiety, facilitating conditions
and attitude towards technology) as conrmed in model 3 of the
model summary (Table 3) signicantly predicted behavioural in-
tention to use technology (ScApp) at
𝛽
(3, 66)
=
-.29, .40 and .31, p
< .05 respectively as reported in the joint model 3. While anxiety
yielded negative (inverse) predictive eects on behavioural inten-
tion to use technology (ScApp), facilitating conditions and attitude
towards technology produced positive (proportional) predictive
eects on behavioural intention to use technology (ScApp). The
result thus conrmed the independent contributions of anxiety,
facilitating conditions and attitude towards technology as predict-
ing user factors of participants’ behavioral intentions to use the
ScApp. The ndings imply that while increase in ocers’ anxiety
predicts low behavioral intention to use ScApp, with improving
facilitating conditions and ocers’ positive attitudinal change to-
wards technology, predict high behavioral intentions to use ScApp
among the ocers. Therefore, the developers have a challenge to
align the application along organizational supporting conditions
and to carry out orientation into adoption of the technology as the
eective means of sentence compute task execution and general
organizational eciency and eectiveness.
Manual sentence computation has inherent problems and chal-
lenges, which may lead to actual miscarriage of justice for correc-
tion/oender management. Eciency in data storage, processing,
searching, and notication represent sets of actions which the pro-
posed ScApp hopes to optimize for greater eectiveness. However,
it is not without user challenges. The associated user challenges
were tested using the UTAUT model to predict ocers’ behavioural
intention to use ScApp. Although internal consistency was ascer-
tained across the 7 component factors evaluated as critical factors
that could aect technology use, the model prediction conrmed
that anxiety, facilitating conditions, and attitude towards use of
technology mostly accounted for user factors with the greatest
AfriCHI 2023, November 27–December 01, 2023, East London, South Africa Henry Nwokoye et al.
Table 5: Beta Weight Coecient Analysis
Model Unstandardized
Coecients
Unstandardized
Coecients
Standardized
Coecients
t Sig.
B Std. Error Beta
1 (Constant) 15.251 .471 - 32.355 .000
Anxiety -.615 .052 -.824 -11.892 .000
(Constant) 7.176 1.584 - 4.530 .000
2 Anxiety -.358 .066 -.480 -5.469 .000
Facilitating Conditions .596 .113 .462 5.267 .000
(Constant) 4.111 1.688 - 2.436 .000
Anxiety -.214 .072 -.287 -2.957 .000
3 Facilitating Conditions .514 .106 .399 4.829 .000
Attitude Towards Use
of Technology
.265 .074 .312 3.601 .001
impact on behavioural intention to use ScApp among correction
ocers.
Patil et al [
30
] identied anxiety, among others, as the lead-
ing user factor aecting consumer adoption of mobile payments
in India, which emphasized the impact of anxiety in predicting
behavioural intention to adopt technology. Also, buttressing the
importance of minimizing anxiety in user designs, Gunasinghe
and Nanayakkara [
31
] identied anxiety as a leading tech-factor
in non-user adoption intentions. Though their nding was limited
to virtual learning environments, it could be extrapolated along
most UTAUT designs, which seek to model technologies which
provoke less anxiety. The importance of reducing anxiety associ-
ated with tech use can best be understood through motivational
paradigms which propel innovation diusion, a view shared by
many researchers [
17
] has roots in social cognitive theory. Practi-
cally, anxiety is real in actual tech use due to diverse factors not
unconnected to the user’s personal characteristics and background.
For example, Park et al [
32
] found that anxiety has negative impacts
on user behavior in mobile payment services for retailers, which is
related to individual user factors.
Findings also identied facilitating conditions as proximal factors
to behavioral intention to use ScApp among correctional ocers.
Conditions which increase the likelihood of technological accep-
tance and adoption may be user- based and institutionally based
[
33
]. User based may be dependent on whether the user meets the
required enablement to initiate tech use, whereas institutionally
based conditions account for climatic conditions upon which the
technology is deplored, e.g., institutional electricity supply, person-
nel factors, etc. Peñarroja et al [
34
] ascertained the impacts of facil-
itating conditions for virtual community practice which exposed
virtual community. Many research ndings [
33
,
35
,
36
] contend
that personal and organizational based facilitation trails eventual
tech adoption. These statistical ndings are in part supportive of
challenges which could adversely aect the use of ScApp among
correction ocers as regards its deployment on android phones
and personal computers, and the institutional required supply of
electricity and internet services which could facilitate its adoption.
Furthermore, being positive about technology use as an attitude
towards the use of technology was found to impact correction of-
cers’ behavioural intention to use ScApp. For instance, several
authors [
37
–
39
] found that without a positive attitude from tech
users, technology acceptance may remain elusive. Human attitudes
have an overwhelming stake in behavioural intention, behavior
initiation and behavioural modication. Thus, with the presence
of other user factors, attitude is like an ignition which acts upon
other user factors. Positive attitudes towards technology tend to
encourage and motivate behavioral intentions to use technology,
whereas negative attitudes kill trust. Therefore, the model of the
current study predicting anxiety, facilitating conditions and atti-
tudes towards the use of technology appears to be consistent with
literature.
5 CONCLUSION AND FUTURE DIRECTIONS
Following user challenges which trailed the introduction and use of
new applications especially those of them that alter job processes,
job outcomes and signicantly aect the way tasks are performed,
the current user study was aimed at testing the associated user
behavioural factors therein and the probable use of ScApp. The
user challenges may exist while introducing automated application
(ScApp) for eective management of prison sentence computation
in Nigeria correction facilities. ScApp is essentially a computational
application for information and data storage; processing, searching
and notication as regards inmates’ correction decisions. It is a devi-
ation from the conventional manual records, programmed to curtail
data loss, sentence ambiguity, inecient and inherent human fac-
tors therein in the recording processes of inmates’ correctional de-
cisions. In order to enhance the ease of use and impediments in the
user experience, the study evaluated ocers’ (i.e., users of ScApp)
behavioral factors in line with UTAUT recommended concerns for
technology acceptance. Model analysis identied signicant user
factors among the UTAUT constructs which most predicted the
behavioral intentions to use ScApp among correction ocers. By
identifying user challenges, subsequent application upgrade would
be able to alleviate them, thus increasing the adoption of the newer
methods of accomplishing correctional objectives using ScApp.
Towards the Adoption of a Sentence Computation Collaborative Mobile App for Eective
Correctional/Oender Management AfriCHI 2023, November 27–December 01, 2023, East London, South Africa
In future, the extensions of the UTAUT, which is UTAUT 2
as well as other technology acceptance models in the context of
correctional/oender management using the ScApp.
ACKNOWLEDGMENTS
We thank the anonymous reviewers in their keen eorts directed at
ensuring scrutiny, encouraging cohesion and insisting on the inclu-
sion of essential topic-specic literature. Also, we greatly appreciate
the sta of Nigerian Correctional Service.
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