Expanding the Technology Acceptance Model to Predict ICT Utilization in Agricultural Extension in Isabela, Philippines

International Journal of Rural Development, Environment and Health Research
[Vol-8, Issue-2, Apr-Jun, 2024]
Issue DOI: https://dx.doi.org/10.22161/ijreh.8.2
Article DOI: https://dx.doi.org/10.22161/ijreh.8.2.12
ISSN: 2456-8678 ©2023 IJREH Journal
Int. Ru. Dev. Env. He. Re. 2024 111
Vol-8, Issue-2; Online Available at: https://www.aipublications.com/ijreh/
Expanding the Technology Acceptance Model to Predict
ICT Utilization in Agricultural Extension in Isabela,
Philippines
Vladimir B. Caliguiran1
, Rosalinda S. Guingab2
1Agricultural Training Institute- Regional Training Center 02, Isabela, Philippines
Email: vbcaliguiran@gmail.com
2Department of Communication, College of Development Communication and Arts and Sciences, Isabela State University, Isabela,
Philippines
Email: rosalinda.s.guingab@isu.edu.ph
Received: 06 May 2024; Received in revised form: 08 Jun 2024; Accepted: 18 Jun 2024; Available online: 30 Jun 2024
©2024 The Author(s). Published by AI Publications. This is an open access article under the CC BY license
(https://creativecommons.org/licenses/by/4.0/)
Abstract— With the advent of information and communications technology, the diffusion of modern
farming technologies and information could be enhanced. The Technology Acceptance Model (TAM)
developed by Davis is one of the widely used models to utilization of information systems such as ICT
tools and resources for agriculture. In addition to the original model that measures the influence of
Perceived Usefulness and Perceived Ease of Use towards the use of technology; intrinsic factors, extrinsic
factors, and socio-demographic characteristics were added to test its relationship with other TAM
components. Data collected through survey among agricultural extension workers (AEWs) and analyzed
through descriptive and inferential statistics. Results showed that most AEWs have access to ICTs. AEWs
frequently use the Rice Crop Manager, Binhing Palay App, and MOET App. The utilization of apps is
seasonal or as need arises. The result shows the extent of utilization of the Binhing Palay App is
significantly influenced by accessibility (0.38) and user interface (0.34) and the Leaf Color Computing App
has significant relationship with accessibility (0.34). In terms of Institutional Support, the fund allocation
for the office internet recorded a significant influence on the use of majority of the ICT tools. The
education degree or course graduated by the AEWs has significant influence with the Perceived
Usefulness of the ICTs with p-value of 0.0075.
Keywords— Agricultural extension, Electronic extension, ICT for agriculture, Information and
Communications Technology, Technology Acceptance Model
I. INTRODUCTION
Information and communications technology (ICT) “has
great potential to accelerate human progress (United
Nations, 2015).” ICT has the capability to accelerate,
scale-out and -up, or enhance the rate of diffusion of a
very wide range of modern technologies, applications,
and platforms. It can assist low-income nations to make
significant development milestones while fostering
economic growth. More importantly, ICTs can
significantly lower the costs of service delivery (Sachs &
Modi, 2015).
According to the International Food Policy Research
Institute (IFPRI), “agricultural extension (also known as
agricultural advisory services) plays a crucial role in

Caliguiran and Guingab Expanding the Technology Acceptance Model to Predict ICT Utilization in Agricultural
Extension in Isabela, Philippines
promoting productivity, increasing food security,
improving rural livelihoods, and promoting agriculture
as a pro-poor economic growth (IFPRI, 2022).”
Agricultural extension has been one of the priority
programs of the government to bring rural
development. The Food and Agriculture Organization of
the United Nations defined extension as “systems that
should facilitate the access of farmers, their
organizations and other market actors to knowledge,
information and technologies; facilitate their interaction
with partners in research, education, agribusiness, and
other relevant institutions; and assist them to develop
their own technical, organizational and management
skills and practices” (Christoplos, 2010). Agricultural
extension is also described as the provision of
knowledge and information to rural people to boost
their productivity and sustainability of their production
systems and improve their livelihoods and quality of life
as a whole (Natural Resources Institute, 2014). In the
Philippines, the extension services is defined in the
Agriculture and Fisheries Modernization Act (AFMA) of
1997 as “the provision of training, information, and
support services by the government and non-
government organizations to the agriculture and
fisheries sectors to improve the technical, business and
social capabilities of farmers and fisherfolk” (Official
Gazette, 2022). Under AFMA, extension services shall
cover major services such as (1) training services, (2)
farm or business advisory services; (3) demonstration
services; and information and communication support
services through tri-media.
The Local Government Code of 1991 devolved the
agricultural extension services and other delivery of
basic services to local communities to the Local
Government Unit. In June 2021, Executive Order No. 138
mandates the national government to fully devolve the
functions of the executive branch to local governments
as specified in the Local Government Code of 1991 by
2024.
However, issues arising from the devolution were
enumerated (Ani & Correa, 2016), some of it are as
follows: (1) Lack of funding support. The shortage of
funds limits the mobility of the agricultural extension
workers. (2) Human resources development issues.
Extension workers have become “jack of all trades,
master of none” since they have to address all
agricultural related issues in their respective localities.
Because funds are limited, extension workers were
transformed from commodity or subject matter
specialists into generalists.
In the Philippines, ICT is being utilized to advance
agricultural extension and communication programs
(Obed, 2019). The Department of Agriculture (DA) has
been developing ICT tools that provide users access to
information channels and decision support tools across
the value chain.
The Agricultural Training Institute (ATI) of the
Department of Agriculture is mandated to conduct
training of all agricultural extension worker and other
agri-fishery clients. The ATI offers (1) technical courses
which covers production and postharvest technologies,
and farming systems; and (2) social technologies that
deals with extension delivery system, communication
skills, and facilitation and presentation skills. In 2007,
the DA through Administrative Order No. 03.s2007
designated ATI as the lead agency for the provision of e-
Extension Services.
Furthermore, different attached agencies of the DA
have also their own Extension Support, Education, and
Training Services (ESETS) unit. For example, the
Philippine Rice Research Institute is one of the
pioneering institutions to use and develop ICT tools for
rice extension services. It is important for agricultural
extension workers to have access information on rice
production. Local R&D can improve extension services
by developing knowledge management system through
ICT. Among the strategies include exploring the use of
internet, regular updating of rice technology websites,
and provision of technical assistance through call and
text centers (Bordey, 2010).
Among these ICT tools include the PhilRice Text Center
(PTC), a SMS-based service provides rice information
such as varietal characteristics, pests and diseases
management, nutrient management, rice machines, and
seeds availability at PhilRice stations. The Pinoy Rice
Knowledge Bank (pinoyrice.com) is a one-stop
information shop that makes rice knowledge available
and accessible in different formats. Moreover, the
agency also developed an android-based smartphone
application that features a catalogue of all released rice
varieties in the Philippines. The Binhing Palay (BP) App
can be used by AEWs in providing seed quality and
varietal information to farmers. Meanwhile, eDamuhan,
is an app that recognizes weed images through artificial
intelligence. It provides weed management information
and can work offline.

In 2008, the International Rice Research Institute
(IRRI), University of the Philippines Los Banos and the
Department of Agriculture developed the Nutrient
Manager for Rice (NMR) using the site-specific nutrient
management (SSNM) principle. It was designed and
deployed from 2008 to 2013 with AEWs as intended
users. The NMR is a useful tool for AEWs in providing
fertilizer recommendations to farmers after answering
series of questions about their field and farming
practices. The first version of the NMR was distributed
through CDs and can be operated with MS Access.
Later, it became web-based wherein interviews were
sent to a cloud-based calculator utilizing SSNM-based
algorithms (IRRI, 2021).
In 2013, the NMR evolved in the now Rice Crop
Manager (RCM) which provides not only fertilizer
recommendation but it also includes crop management
recommendations. In 2018, it evolved into RCM Advisory
Services (RCMAS) which include other functions such as
farmer and field registration. Today, the RCMAS is now
fully managed by the Department of Agriculture
through the Philippine Rice Research Institute since it
was transferred by IRRI on July 16, 2022.
The RCM has now an Android app version and can
generate recommendation even without internet
connection. The ATI together with the DA Regional Field
Offices are conducting series of trainings for AEWs and
other para-extension workers.
The use of ICT is now a popular extension modality in
different countries. In Uganda, they utilized radio,
mobile SMS messages, and village-based video
screenings to enhance the knowledge of farmers on the
management of fall armyworm (FAW) (Tambo, et al.,
2019). On an impact assessment conducted, the result
showed that ICT-based extension campaign significantly
increased the knowledge of farmers on FAW and
triggered the adoption of agricultural technologies and
practices for the management of the pest. The study
also revealed that the used of complementary ICT
channels that repeat and reinforce messages are
effective in translating awareness and knowledge into
behavioural change. In Mali, public extension workers
acknowledge that their current ration to farmers limits
dissemination of extension services to farmers. Hence,
they are also utilizing ICT based extension. However, in
a study conducted, one of the challenges in the
adoption of ICT base extension among public extension
workers is age. Informants said that younger officers
tend to adopt more quickly the older ones. In addition, a
good government policy will positively affect the
adoption of ICT (Kante, 2021). The use of ICT among the
agricultural extension officers in Lesotho significantly
improved their access to information. Moreover, the
awareness of extension officers on ICT had a significant
positive on their use of ICT tools. Meaning, if the
extension officers are aware of the importance of ICT
tools, the more they will use of it in their professional
work (Akintunde & Oladele, 2019). On the other hand,
the study found that some of the constraints to the use
of ICT include: perceived high cost, failure of service,
inability to maintain ICT, absence of skilled operators,
shortage of electricity, fake and substandard products,
insufficient service providers in the country, illiteracy,
poor basic infrastructure, and non-availability of
technical personnel. In Ethiopia, non-governmental
organizations provided agricultural extension and
advisory services to farmers (Benson, 2022). These
include the provision of technology and inputs, training
on how to use ICT in agriculture and mass education.
The study of Benson (2022) found out that ICT, through
mobile phones, helps small-scale farmers to market
their produce and enhance their livelihoods. They also
used ICT in promoting farming information and
knowledge. However, Mahon et al. (2019) as mentioned
by Benson (2022), said that the lack of access to ICT
infrastructure hindered the national and regional
sharing and exchange of knowledge and information
generated by research centers.
Undeniably, the information and communication
technology revolution provide new options for
accessing information by providing it directly to farmers
and extension workers. ICTs offer more opportunities to
reach more people and to carry out various extension
functions more effectively and efficiently.
The Philippine Department of Agriculture has been
aggressive in promoting the utilization of its ICT tools
among Agricultural Extension Worker (AEWs), farmers,
intermediaries and other stakeholders. However, there
have not been a single study looking into the extent of
the utilization of these ICT tools among AEWs. Just like
any other app, these ICT tools have features that may
either encourage or discourage their use by AEWs.
The Technology Acceptance Model (TAM), developed
by Davis (1989) to explain and predict computer
technology adoption is one of the widely used models in
studies on information technologies utilization

(Alambeigi & Ahangary, 2015). The TAM model uses two
variables as fundamental determinants of user
acceptance: perceived usefulness; and perceived ease
of use (Davis, 1989). Perceived Usefulness (PU) is
defined as “the degree to which a person believes that
using a particular system would enhance his or her job
performance,” while Perceived Ease of Use (PEOU)
refers to “the degree to which person believes that
using particular system would be free of effort (Davis,
1989).
Through the years, the TAM expanded to include other
variables that could directly affect or mediate utilization
of ICT. These include the TAM 2 work by Venkatesh and
Davis which include social factors and results-oriented
aspects in the framework. While TAM 3 was proposed
by Venkatesh and Bala wherein self-efficacy, external
control, anxiety, playfulness, perceived enjoyment, and
usability are determinants of PEOU (Castiblanco
Jimenez et al, 2021).
Succeeding researchers have proposed several different
extensions based on the research objectives, context,
and the nature of technology (Castiblanco Jimenez et al,
2021).
In this context, an expanded Technology Acceptance
Model was developed and validated to predict the
extent of utilization of ICT tools in agricultural extension
in the Province of Isabela.
The expanded TAM considered the Institutional Support
by the Department of Agriculture and Local
Government Unit, the ICT tools’ Content Quality, and
User Characteristics as predictor of PU and PEOU.
Jimenez et al. (2020) identified content quality as one
of the common external variables for TAM under
Technology acceptance when the technology is a
platform or system. Based on the literature search of
Castiblanco Jimenez et al (2020), Content Quality (CQ)
was defined as the extent to which the information fits
user needs in terms of information organization,
relevance and actuality, availability of support materials,
and accuracy of the terminology. This definition was
adopted in this study.
II. METHODOLOGY
Descriptive causal research design was employed in this
study. Quantitative data collection techniques,
specifically survey, was used to elicit information for this
study. The respondents of the study were Agricultural
Extension Workers (AEW) in Isabela. Both the regular
and non-permanent AEWs working for at least one year
at the Municipal/City Agriculture Office were included in
the study. In selecting the respondents, only the AEWs
residing in accessible municipalities of Districts 1 and 3
were considered. These are districts that are adjacent to
the Training Centers of the Agricultural Training
Institute. Based on accessibility, therefore, the
municipalities of Cabagan, Delfin Albano and Tumauini,
in District 1 and municipalities of Cabatuan, San Mateo
and Ramon in District 3 of Isabela, Philippines were
purposely chosen as sites for the study.
A survey questionnaire was used to collect the needed
data for this study. It consists of two parts, the first part
is designed to collect the AEWs characteristics while the
second part explored the other intrinsic ICT traits,
extrinsic factors, and extent of utilization of ICT tools
among the respondents. The instrument partly adopted
the TAM questionnaire by Davis and format as studied
by Lewis (2019). The TAM has 12 items, six assessing
perceived usefulness (PU) and six assessing perceived
ease of use (PEOU). Meanwhile, three items assessing
the content quality were derived from the study of
Castiblanco Jimenez et al. (2021). And the questions for
accessibility were derived from the study of Barroga
(2019). On the other hand, questions referring to user
interface were derived from the research of Choi et al
(2017). Moreover, the study used the perceived
constraints in utilization of ICT for agricultural extension
by Kale et al. (2017). Self-administered survey
questionnaires were sent in person or through email to
all the respondents. Their consent to participate were
solicited through an Informed Consent Form indicating
their voluntary participation.
Data were analyzed through descriptive and inferential
statistics. Encoding, cleaning, and sorting of data were
done through MS Excel. These were processed in SPSS
statistical software. Pearson correlation, p-test, and t-
test were used to examine the predictive value of each
independent variable on the dependent variable.
III. RESULTS AND DISCUSSIONS
Socio-demographic characteristics of AEWs
A new generation of Agricultural Extension workers are
now in the frontline service. Table 1 shows that majority
of AEWS are young, with nearly 60% aged 30 or younger.
This indicates a youthful workforce, which could imply a
high level of energy and potential for growth, and are

more receptive to innovations and technological
advancements.
In terms of sex, there is a higher proportion of female
AEWs compared to male, making up almost 61% of the
workforce. The dominance of female AEW, in terms of
number, is more evident in District 3 with 66% while in
District 1 is almost equal at 53%.
Majority of the AEWs are young and new in the service.
A significant majority of AEWs have relatively short
tenure (1-5 years), which correlates with the younger
age distribution. The average years in service is 5.15
years while 23% of them are in the service for only 1 year.
Nonetheless, majority or 52.2% are on permanent or
regular job tenure status, 8.7% are contractual or casual
and the rest 39.1% are job orders or under contract of
service which has not employee-employer relationship.
According to Briones et al. (2023), the type of
appointment of the AEWs have an effect on the quality
of the extension services provided to farmers. For their
highest educational attainment, only one from the
respondents has a Doctoral Degree and only two have
masters’ degree.
Each AEW has multiple commodity assignments.
Majority or 58.7% of the respondents are assigned on
rice, reflecting its importance as staple crop. Livestock
(32.6%) and corn (28.3%) are also significant areas of
focus. The diversity in commodity assignments shows a
broad range of expertise among AEWs, but the
concentration on rice suggests it is a key priority of the
government and it shows in the production
performance of the Isabela province being one of the
top rice producing provinces in the country.
Table 1. Socio-demographic Characteristics of AEWs
Variable Frequen
cy
Percentag
e(%)
Age Young (≤30) 27 58.70
Average (31-
59)
19 41.30
Old (≥60) 0 0
Sex Male 18 39
Female 28 61
Highest
Educatio
Vocational/
Diploma
1 2.2
nal
Attainm
ent
College
Graduate
42 91.3
Masteral
Graduate
2 4.3
Doctoral
Graduate
1 2.2
Course Agribusiness 2 4.35
Agricultural
engineering
3
6.52
Agricultural
technology
8
17.39
Agriculture 23 50
Animal
Husbandry
1
2.17
Business
administration
2
4.35
Forestry 1 2.17
Information
technology
3
6.52
Nursing 1 2.17
Veterinary
medicine
1
2.17
Fisheries 1 2.17
Job
Tenure
Job Order/
Contract of
Service
18 39.1
Contractual/
Casual
4 8.7
Regular/
Permanent
24 52.2
Years in
Service
1-5 32 73
6-10 8 18
11-15 2 5
16-20 2 5
Commod
ity
Assignm
ent*
Rice 27 58.7
Corn 13 28.3
Livestock 15 32.6
High Value
Crops
10 21.7

Rural Based
Organizations
7 15.2
Crop
Insurance
1 2.2
Fisheries 6 13.1
Agricultural
Engineering/
Machines
2 4.4
*Multiple responses
Information needs of farmers
On the other hand, one of the main tasks of agricultural
extension workers is to provide technical assistance or
farm business advisory services. They provide
information need by the farmers to improve their
management practices, processing techniques,
marketing, or even their resources. Table 3 shows the
information AEWs provide to farmers. Moreover, the
Municipal Agriculture Office is among the source of
information of farmers specifically on agriculture,
livestock, and fishery. As mentioned in a Baseline Study
conducted by the Department of Agriculture, the top
source of information of farmers is training/ coaching/
and mentoring (Briones, Galang, & Latigar, 2023).
The most frequently asked information by farmers is on
variety and seed selection with 63% followed by planting
with 45.7%, pest management with 43.5% and nutrient
management as shown in Table 2. On the other hand, it
can be observed in Table 3 that information on variety
and seed selection is also the primary topic being
provided by the AEWs to the farmers. It is worth to
point out that, the information need by the farmers are
being provided by the AEWs. This suggests that AEWs
must have up-to-date knowledge on these topics or
have an access to sources of information such as ICT
tools.
ICT tools that the AEWs have access for agricultural
extension
The almost all or 93.5% of the AEW respondents have
access to ICT tools developed by the Department of
Agriculture, which is crucial for disseminating updated
agricultural information.
Most of the AEWs own smartphones (89.1%), which
supports the use of mobile apps and internet resources
in their work. However, fewer AEWs own laptops
(41.3%) or desktops (37.0%), which might limit their
ability. Nevertheless, the Local Government Units
(LGUs) provide significant ICT resources, especially
laptops (73.9%) and desktops (82.6%). This support
enhances AEWs' capacity to access and disseminate
information effectively.
A mix of internet connection types is used in offices,
with fiber broadband (41.3%) being the most common,
indicating good infrastructure for reliable internet
access. Most AEWs have internet access in the field,
primarily through prepaid mobile data (82.6%), which
supports on-the-go information access and
communication.
Table 2. Information usually asked by farmers from AEWs
Variable Frequency Percentage
(%)
Credit 18 39.1
Crop Insurance 10 87
Variety and Seed
Selection
29 63
Land Preparation 18 39.1
Planting 21 45.7
Seedlings Management 18 39.1
Nutrient Management 19 41.3
Water Management 17 37
Pest Management 20 43.5
Harvest Management 13 28.3
Postharvest
Management
12 26.1
Processing and Value
adding
10 21.7
Marketing 13 28.3
Training 17 37.0

The high percentage of smartphone ownership (89.1%),
internet connectivity in the field (89.1%), and access to
DA-developed ICT tools (93.5%) could equip the AEWs to
provide timely and relevant information to farmers. This
infrastructure supports the effective dissemination of
agricultural information, aligning well with the high
demand for specific types of information from farmers.
Table 4. ICT Ownership and Access
Variable Frequenc
y
Percentag
e (%)
Accessing
DA-
Developed
ICT tools
for
Informatio
n Sharing
Yes 43 93.5
No 3 6.5
ICTs
Personally
Owned by
AEW
Keypad/
Feature Phone
4 8.7
Smartphone 41 89.1
Tablet 3 6.5
Laptop 19 41.3
Desktop 17 37.0
ICTs
owned by
LGU for
Agricultura
l Extension
Keypad/
Feature Phone
2 4.3
Smartphone 23 50
Tablet 2 4.3
Laptop 34 73.9
Desktop 38 82.6
Radio 1 2.2
Television 3 6.5
Internet
Connection
at their
Office
Prepaid Mobile
Data
- Personal
Expense
- LGU
Provided
14
9
30.4
19.6
Postpaid
Mobile Data
2 4.3
Wireless
Broadband
11 23.9
Fiber
Broadband
19 41.3
Internet
Connection
in the Field
Yes
- Prepaid
- Postpaid
41
38
3
89.1
82.6
6.5
None 5 10.9
In terms of awareness of the AEWs on the ICT tools
developed and being promoted by the Department of
Agriculture, a large majority or 91.3 percent are aware of
these technologies. The Rice Crop Manager is the most
popular app with 76.1% of the respondents followed by
Binhing Palay App with 71.7%. Since its launching in 2018,
there is a massive campaign on the utilization of Rice
Crop Manager Advisory Services which started as
Nutrient Manager for Rice. Several Trainings on the Use
and Operation of the RCMAS were conducted by the
Agricultural Training Institute, Department of
Agriculture, Philippine Rice Research Institute and the
International Rice Research Institute.
Table 3. Information provided by AEWs to farmers
(%)
Credit 17 37
Crop Insurance 10 87
Variety and Seed Selection 33 71.7
Planting 22 47.8
Nutrient Management 23 50
Water Management 22 47.8
Pest Management 22 47.8
Harvest Management 19 41.3
Postharvest Management 17 37
adding
12 26
Marketing 13 30.4
Training 13 30.4

Table 5. AEW Awareness on the ICT Tools Developed and
being Promoted by DA for Agricultural Extension
(%)
Awareness
on existing
ICT tools
developed
by DA
Yes 42 91.3
Binhing Palay
App
33 71.7
Rice Crop
Manager
35 76.1
Leaf Color
Computing App
20 43.5
MOET App 19 41.3
e-Damuhan 15 32.6
Rice Doctor 10 21.7
AgriDoc App 8 17.4
Rice Knowledge
Bank
7 15.2
Pinoy Rice
Knowledge
Bank
10 21.7
e-Extension/
eLearning for
AgriFishery
13 28.3
PhilRice Text
Center
12 26.1
Farmers’
Contact Center
8 17.4
No 4 8.7
ICT tools developed by DA that are being used by the
AEWs
The top three ICT tools or applications that are being
utilized by the AEWs are Rice Crop Manager (76.1%),
Binhing Palay App (56.5%), and MOET App (34.8%).
Respondents have noted that both the RCM and
Binhing Palay app are being utilized during the seed
distribution every cropping season. “Farmers are usually
asking the maturity of the variety, how much it can
yield, and other information about the seeds
(Respondent A, 40 years old).” Hence, they are using
the Binhing Palay App to look for the information about
rice varieties. On the other hand, the provision of
nutrient and crop management recommendation
through the Rice Crop Manager has been a practice of
most local government units. “We use them seasonally,
but during seed distribution we use it every day
(Respondent A, 40 years old).” According to the AEWs,
rice seed distribution occurs on May to June for the Wet
Cropping season and November to December for the
Dry Cropping season.
It is also important to note the findings of Briones et al.
in 2023 that the RCM received a large funding from the
National Rice Program which provides incentives to
AEWs who generated the number of target RCM
recommendations.
Table 6. ICT Tools that are being used by AEWs in
agricultural extension
Variable Frequency Percentage (%)
Binhing Palay App 26 56.5
Rice Crop Manager 35 76.1
Leaf Color
Computing App
14 30.4
MOET App 16 34.8
e-Damuhan 15 32.6
Rice Doctor 10 21.7
AgriDoc App 3 6.5
Rice Knowledge
Bank
5 10.9
Pinoy Rice
Knowledge Bank
7 15.2
e-Extension/
eLearning for
AgriFishery
9 19.6
PhilRice Text
Center
10 21.7
Farmers’ Contact
Center
7 15.2
With the access to ICT tools, the agricultural extension
workers usually search information on crop production
from the different apps and websites. The top
information they are searching is on Variety and Seed
Selection (73.9%), Pest Management (63.0%), Water
Management (56.5%), and Seedlings Management
(54.3%). Meanwhile, they are also looking for topics such
as Crop Insurance (43.5%), Land Preparation (45.7%),
Planting (50.0%), and Nutrient Management (52.2%). It

can be observed that the topics searched by the AEWs
are closely related to the functionalities and information
being offered by the ICT tools.
Table 7. Information Usually Search by AEWs in the ICT
Tools
Credit 12 26.1
Crop Insurance 20 43.5
Variety and Seed
Selection
34 73.9
Planting 23 50
Nutrient Management 24 52.2
Water Management 26 56.5
Pest Management 29 63
Harvest Management 17 37
Postharvest
Management
18 39.1
adding
12 26.1
Marketing 15 32.6
Training 14 30.4
Livestock 14 30.4
Table 7. Information Usually Search by AEWs in the ICT
Tools
Organic Agriculture 12 26.1
Price Information 6 13
Weather Forecast 12 26.1
Extent of utilization of ICT tools among AEWs in
the delivery of agricultural extension services
There is a variability in usage patterns of the
different ICT tools, with some being used more
consistently than the others. The Binhing Palay App
and Rice Crop Manager, are used more frequently, with
a higher proportion of AEWs using them on a daily or
weekly basis. On the other hand, ICT tools such as Rice
Doctor and AgriDoc App, are used less frequently, with
usage typically occurring once in 2 months or even less
frequently. Some of the respondents who answered
“others” specified that the utilization of the RCM and
Binhing Palay App is seasonal. As mentioned earlier,
during seed distribution prior to the planting season,
these two apps are used almost every day. Meanwhile,
the Rice Doctor which provides information on Pest
Management is used only during insect pests’
infestations.
Table 8. Utilization of ICT Tools Developed by DA for Agricultural Extension for the past 6 months
ICT Tools Everyday 1x a week
1-2 times a
month
Once in 2
months
Once in 6
months
Others
f % f % f % f % f % f %
Binhing Palay App 1 2.2 2 4.3 5 10.9 6 13.0 8 17.4 5 10.9
Rice Crop Manager 1 2.2 1 2.2 11 23.9 7 15.2 12 26.1 3 6.5
Leaf Color Computing
App
- - - - 3 6.5 4 8.7 7 15.2 5 10.9
MOET App - - 3 6.5 5 10.9 7 15.2 4 8.7 - -
e-Damuhan 1 2.2 2 4.3 2 4.3 3 6.5 4 8.7 4 8.7
Rice Doctor 1 2.2 1 2.2 1 2.2 1 2.2 - - 5 10.9
AgriDoc App - - - - 1 2.2 - - - - 5 10.9
Rice Knowledge Bank - - - - 2 4.3 - - 1 2.2 5 10.9
Pinoy Rice
Knowledge Bank
- - - - 2 4.3 - - 1 2.2 5 10.9

e-Extension/
eLearning for
AgriFishery
- - - - 3 6.5 - - 1 2.2 5 10.9
PhilRice Text Center - - - - 2 4.3 1 2.2 3 6.5 5 10.9
Farmers’ Contact
Center
- - - - 1 2.2 1 2.2 2 4.3 4 8.7
Perception of AEWs on ICT traits
According to Davis, the user’s beliefs can
influence the attitude of the users which will affect the
intention to use or not the ICT tools (Castiblanco
Jimenez, Cepeda Garcia, Violante, & Vrezzetti, 2020).
Using a Likert Scale of 1-5 with where 1= Extremely
Disagree, 2= Slightly Disagree, 3= Neither Agree nor
Disagree, 4= Slightly Agree, 5- Extremely Agree, the
respondents assessed their perception on different
beliefs used in the TAM. Based on the result on Table 8,
respondents generally agree on these beliefs. In terms
of Perceived Usefulness, a mean of 4.50 was obtained
wherein the highest score was recorded on the
statement “Using ICT tools improves my job
performance as an AEW”. Meanwhile, on the Perceived
Ease of Use there is an average of 4.25 which positively
indicates that the ICT tools are user-friendly and easy to
navigate. For the Content Quality, the respondents
agreed that information presented in the ICT tools are
relevant, accurate and in appropriate format with a
score of 4.24. On the other hand, the Accessibility
recorded the lowest mean with 3.89 of which some of
the respondents have disagreement on their
willingness to pay or buy ICT tools for the performance
of their job. Nonetheless, on average a score of 3.59
which places between Neither Disagree nor Agree and
Slightly Agree was obtained. Lastly, the respondents
agreed that the user interface is also an important
traits of ICT tools to be considered with a score of 4.09.
Table 9. Perception on ICT Traits towards utilization
Variables Mean
Standard
error
Perceived Usefulness 4.50 0.10
1. Using ICT Tools in
my job enables me
to accomplish tasks
more quickly than
other products in
its class.
4.37 0.09
2. Using ICT tools
improves my job
performance as an
AEW.
4.59 0.09
3. Using ICT tools in
my job increases
my productivity as
an AEW.
4.48 0.10
4. Using this product
enhances my
effectiveness on
the delivery of
agricultural
extension.
4.52 0.10
5. Using the ICT tools
makes it easier to
provide agricultural
extension.
4.48 0.10
6. I have found the
ICT tools useful in
my job as an
agricultural
extension worker.
4.57 0.10
Perceived Ease of
Use
4.25 0.11
7. Learning to operate
the ICT tools was
easy for me.
4.22 0.10
8. I found it easy to
get the ICT tools to
do what I want it to
do.
4.09 0.11
9. My interaction with
the ICT tools has
been clear and
understandable.
4.39 0.10
10. I found the ICT
tools to be flexible
4.22 0.12

to interact with.
11. It was easy for me
to become skillful
at using the ICT
tools.
4.33 0.10
12. I found the ICT
tools easy to use.
4.26 0.12
Content Quality 4.24 0.12
13. The ICT tools
provide up-to-date
information and
content that is
relevant to my
needs and interests
as AEW.
4.07 0.14
14. I think that the
information I will
get from the ICT
tools are valuable in
the performance of
my job as an AEW.
4.39 0.09
15. The ICT tools
present the
information in an
appropriate format.
4.26 0.12
Accessibility 3.89 0.12
16. I am willing to
pay/buy ICT tools
for the delivery of
agricultural
extension.
3.59 0.14
17. I consider the
internet
connectivity
requirement of an
ICT tool before
using it.
4.20 0.11
User-interface 4.09 0.12
18. The interface is fun
to use.
4.02 0.11
19. The interface is 4.17 0.12
easy to learn.
20. The interface is
pleasant.
4.07 0.12
21. The interface is
simple.
4.11 0.13
22. I can input data
accurately using
the interface.
4.07 0.12
23. I can input data
quickly using the
interface.
4.13 0.12
Aside from the intrinsic and extrinsic factors that may
affect the utilization of ICT tools, this study also
explored the relationship of the socio-demographic
characteristics of the respondents and their perception
on the ICT Traits. Results showed that there are two
socio-demographic variables that have significant
relationship with the perception of AEWs on some ICT
Traits.
The education degree or course graduated by the
AEWs has significant influence with the Perceived
Usefulness of the ICTs with p-value of 0.0075. The
AEWs working in different Local Government Units
varies on the courses they finished which include
Agriculture, BS in Agricultural Engineering, Fisheries,
Forestry, Veterinary Medicine, Information Technology,
and Business Administration. However, as Ani and
Correa (2016) found “Extension workers have become
“jack of all trades, master of none” since they have to
address all agricultural related issues in their respective
localities”. The nature of their work providing farm
business advisory outside of their specialization could
influence their perception on how useful the ICT tools
in the performance of their job.
Meanwhile, the educational attainment of the AEWs
significantly influences the Perceived Ease of Use with
p-value of 0.0451. With their exposure on and use of
ICT tools during their university years, it provides them
prior knowledge on computer system which influences
their perception on ease of use.

Table 10. Relationship of Socio-demographic characteristics and user’s beliefs towards ICT
ICT Traits
p-value
Age Sex Years in
Services
Educational
Attainment
Course Job
Tenure
Perceived
Usefulness
0.3892 0.6729 0.8184 0.1141 0.0075* 0.1064
Perceived Ease
of Use
0.4376 0.2718 0.786 0.0451* 0.1043 0.4154
Content Quality 0.5617 0.3216 0.4771 0.2869 0.1305 0.2352
Accessibility 0.705 0.8332 0.5359 0.1075 0.4498 0.1744
User Interface 0.8948 0.6952 0.6553 0.0548 0.7491 0.6527
*significant at 0.05 level
Institutional support
The Department of Agriculture and the Local
Government Unit are providing support for the
utilization of ICT tools in different municipalities. These
include provision of financial resources, provision of ICT
equipment and capability building activities. The
Department of Agriculture through the Agricultural
Training Institute (DA-ATI) conducted trainings on the
operation and maintenance on the Rice Crop Manager
and included modules on ICT Tools for Agriculture in
different Training Modules (ATI-RTC 02, 2023). In
addition, the DA-ATI also provided ICT tools such as
laptops, wifi modem, tablet, and GPS device to some
Farmers Information and Technology Services (FITS)
Centers maintained by the Office of the Municipal
Agriculturist for different Local Government Units.
Furthermore, the result of the study shows that 76.1%
of the respondents said that the LGUs allow them to
attend training programs. Moreover, 60.9 of the
AEWs said that their LGUs allocate fund for office
internet. The LGUs are also maintaining their FITS
Centers said by the majority (52.2%) of the
respondents.
Influence of ICT Traits on the Extent of Utilization of
ICT Tools
Based on the result on Table 8, the
respondents agreed that their perceptions on the
usefulness, ease of use, content quality, accessibility
and user interface of the ICT tools greatly influence
their attitude towards the tools which eventually affect
their intention to use. However, the extent of the
utilization could be different. Among the ICT traits, only
the accessibility and user interface showed significant
relationship with the utilization of ICT tools. The result
on Table 11 shows the extent of utilization of the
Binhing Palay App is significantly influenced by
accessibility (0.38) and user interface (0.34) and while
the Leaf Color Computing App has significant
relationship with accessibility (0.34).
Table 11. Institutional Support of LGUs on ICT
Variable Frequ
ency
(n=46)
Percentage
(%)
Allocate funds for office
internet connection
28 60.9
Provides/procure ICT gadget
for extension service
9 19.6
Provides training program
on ICT/ digital literacy
21 45.7
Allows staff to attend
training program on ICT/
digital literacy
35 76.1
Provides communication
allowance of staff
6 13.0
Maintains an ICT lounge 2 4.3
Maintains the LGU FITS
Center
24 52.2
Documented support on ICT
(Memorandum, resolution,
development plan, etc)
5 10.9

Furthermore, in terms of Institutional
Support, the fund allocation for the office internet
recorded a significant influence on the use of
majority of the ICT tools as reported on Table 12. In
addition, the maintenance of the FITS Center and
documented support such as memorandum of
agreements, resolutions, and development plans
have also a significant influence on the extent of
utilization of the ICT tools (Table 13).
Table 12. Influence of ICT Traits on the Extent of Utilization of ICT
ICT Trait
Correlation (pearson r)
Binhin
g
Palay
App
Rice
Crop
Manag
er
Leaf
Color
Computi
ng App
MOE
T
App
e-
Damuh
an App
Rice
Doct
or
AgriDo
c App
Rice
Knowled
ge Bank
Pinoy
Rice
Knowled
ge Bank
e-
Extension
/
eLearning
for
Agri/Fishe
ry
PhilRic
e Text
Center
Farmer
s'
Contac
t
Center
usefulnes
s
0.28 -0.23 0.21 -0.09 0.06 0.04 -0.02 0.05 -0.05 0.10 0.05 -0.02
ease of
use
0.27 -0.10 0.25 -0.07 0.26 0.12 0.08 0.14 0.06 0.23 0.04 0.11
content
quality
0.24 -0.12 0.20 -0.05 0.24 0.17 0.10 0.18 0.10 0.24 0.09 0.13
accessibili
ty
0.38* -0.02 0.34* 0.04 0.11 0.12 0.05 0.13 0.06 0.24 0.05 0.12
user
interface
0.34* -0.02 0.29 0.03 0.23 0.07 0.01 0.09 0.02 0.16 -0.02 0.06
Table 13. Influence of Institutional Support on the Extent of Utilization of ICT Tools
Institution
al Support
t-test
Binhi
ng
Pala
y
App
Rice
Crop
Mana
ger
Leaf
Color
Compu
ting
App
MOE
T
App
e-
Damu
han
App
Rice
Doct
or
AgriD
oc
App
Rice
Knowle
dge
Bank
Pinoy
Rice
Knowle
dge
Bank
e-
Extensi
on/
eLearni
ng for
Agri/Fis
hery
PhilR
ice
Text
Cent
er
Farm
ers'
Conta
ct
Cente
r
Allocate
funds for
office
internet
0.47
62
0.601
5
0.0048
*
0.026
0*
0.0367
*
0.05
16
0.04
04*
0.0155* 0.0155* 0.0350* 0.119
2
0.014
3*
Provides
ICT gadget
0.501
3
0.387
5
0.4077 0.973
5
0.5205 0.43
79
0.287
4
0.2061 0.2061 0.5455 0.38
8
0.469
Provides
training
program
on ICT
0.70
54
0.301 0.334 0.261 0.385
4
0.58
06
0.655
5
0.5394 0.5394 0.2025 0.90
73
0.289
4
Allows
staff to
0.85 0.620 0.7307 0.38 0.2175 0.34 0.203 0.0833 0.3836 0.1116 0.777 0.477

attend
training
on ICT
5 3 87 68 3 9 6
Provides
communic
ation
allowance
0.56
48
0.454 0.8966 0.414
2
0.154 0.86
44
0.703
1
0.4383 0.4383 0.9564 0.125
3
0.889
1
Maintains
ICT lounge
0.751
6
0.680
9
0.5438 0.517
4
0.3198 0.119
6
0.08
5
0.1358 0.1358 0.1524 0.245
8
0.1314
Maintains
LGU FITS
center
0.14
9
0.575
4
0.1862 0.003
3*
0.082
5
0.29
12
0.133
5
0.2156 0.0472* 0.3169 0.33
87
0.1211
Document
ed
support
on ICT
0.93
81
0.4118 0.6729 0.021
8*
0.3192 0.06
55
0.036
1*
0.079 0.079 0.1538 0.203
8
0.125
Challenges and constraints on the use of ICT tools
The study also explored the possible conditions that
may constrain the Agricultural Extension Workers on
their utilization of the ICT Tools. The respondents
provided their insights using a Likert Scale of 1-5
where 1= Extremely Disagree, 2= Slightly Disagree, 3=
Neither Agree nor Disagree, 4= Slightly Agree, 5-
Extremely Agree. Based on the result of their scores
on Table 10, the respondents may agree and disagree
that the conditions such as Time management
problems in learning to use ICT (3.0), Lack of fund for
ICT (3.35), Poor ICT based infrastructure facilities in
our office (3.24), Lack of technical support from our
organization (3.11), and Slow functioning of internet/
server break down may restrict their use of ICT tools
(3.33). On the other hand, they disagree that the
conditions such as lack of expertise to use ICT (2.87),
lack of motivation towards ICT (2.85), use of ICT cause
health problems like eye pain, body pain etc (2.65),
lack of confidence to use ICT (2.54), lack of training
facilities to learn ICT (2.89), and lack of useful
software/ app (2.89) restrict them to use ICT tools.
Table 14. Challenges and constraints on the use of
ICT tools among the AEWs in the delivery of
extension services
Constraints Mean
Lack of expertise to use ICT 2.87
Time management
problems in learning to use
ICT
3.00
Lack of learner motivation
towards using ICT
2.85
Use of ICT cause health
problems like eye pain,
body pain etc.
2.65
Lack of confidence to use
ICT
2.54
Lack of training facilities to
learn ICT
2.89
Lack of fund for ICT 3.35
Poor ICT based
infrastructure facilities in
our office
3.24
Lack of technical support
from agency
3.11
Slow functioning of
internet/ server break
down
3.33
Lack of useful software/ 2.89

app
Power supply interruption 2.43
No network coverage for
mobile
3.17
High threat of virus 2.72
IV. CONCLUSION
With the advent of information and communications
technology, the diffusion of modern farming
technologies and information could be enhanced. At
present, there are several ICT tools and resources that
were developed and promoted to advance agricultural
extension.
The Technology Acceptance Model (TAM) by
developed by Davis in 1989 to explain and predict
computer technology adoption. It is one of the widely
used models to study utilization of information systems
such as ICT tools and resources for agriculture.
Based on the results of the study, most of the
agricultural extension workers have access to ICTs such
as smartphones, desktop computers, and internet. The
Local Government Units through the Municipal
Agriculture Offices provide ICT tools such as laptops
and desktops for the delivery of agriculture and fishery
extension services. The AEWs are also using their
personal smartphones and internet connectivity when
accessing ICT apps in the field.
Among the many ICT tools, AEWs frequently use the
Rice Crop Manager, Binhing Palay App, and MOET App.
The respondents noted that the utilization of apps is
seasonal or as the need arises. For example, the
Binhing Palay App and the Rice Crop Manager are
being used during the on-set of the cropping season
since farmers will seek information on recommended
variety and nutrient management.
The study explored different factors that could affect
the extent of utilization of ICT tools on rice among the
agricultural extension workers in Isabela. Among the
areas considered include intrinsic factors such as
usefulness, ease of use, content quality, accessibility,
user-interface, and extrinsic factor specifically
institutional support.
The results of the study showed that among the
intrinsic factors, the accessibility and user interface
have significant influence on the extent of ICT
utilization specifically on the Binhing Palay App and
Leaf Color Computing App.
Meanwhile, on institutional support the allocation of
funds for office internet, maintenance of LGU FITS
Centers, and documented support on ICT have
significant influence on the utilization of the ICT tools.
Hence it is recommended for the Local Government
Units to allot regular budget for ICT to improve
internet connection and upgrade equipment for
efficient extension delivery. Moreover, given that the
AEWs have different specializations, the LGUs are
encouraged continuously to invest on ICT resources
since most of the AEWs share information from the ICT
tools to the farmers
On the other hand, factors that could limit the use of
ICT tools among AEWs include lack of fund for CIT,
poor ICT infrastructure facilities, lack of technical
support and slow function of internet or server
breakdown.
ACKNOWLEDGEMENTS
The researchers acknowledge the assistance extended
by the participating Municipal Agriculture Offices, the
Department of Communication, College of
Development Communication and Arts and Sciences of
Isabela Sate University Cabagan Campus, and the
Agricultural Training Institute- Regional Training Center
02.
REFERENCES
[1] Adriano, F. (2020, September 10). Revitalizing our
agriculture research and extension system. Retrieved
January 28, 2022, from The Manila Time:
https://www.manilatimes.net/2020/09/10/business/colum
nists-business/revitalizing-our-agriculture-research-and-
extension-system/766617
[2] Akintunde, M., & Oladele, O. (2019). Effect of
Information Communication Technologies on
Information Access in Lesotho Extension System. Merit
Research Journal of Agricultural Science and Soil
Sciences, 008-014. doi:10.5281/zenodo.2551618
[3] Alambeigi, A., & Ahangari, I. (2015). Technology
Acceptance model (TAM) as a Predictor Model for
Explaining Agricultural Experts Behavior in Acceptance
of ICt. International Journal of Agricultural Management
and Development, 235-247.
[4] Albert, J. R., Quimba, F. M., Tabuga, A. D., Mirandilla-
Santos, M. G., Rosellon, M. A., Vizmanos, J. F., . . .
Muñoz, M. S. (2021). Expanded Data Analyis and Policy

Research for National ICT Household Survey 2019.
Quezon City: Philippine Institute for Development
Studies.
[5] Ani, P., & Correa, A. (2016, July 9). Agricultural Extension
Policies in the Philippines: Towards Enhancing the
Delivery of Technological Services. Retrieved January 28,
2022, from Food and Fertilizer Technology Center for the
Asian and Pacific Region Agricultural Policy Platform:
https://ap.fftc.org.tw/article/1092
[6] ATI-RTC 02. (2023). Annual Report 2022. San Mateo,
Isabela, Philippines: Agricultural Training Institute-
Regional Training Center 02.
[7] Barroga, R. F. (2019). The Role of Information and
Communications Technology in Agricultural
Development in the Philippines. Perth WA, Australia: The
University of Western Australia.
[8] Benson, T. (2022). ICT Supported, Agricultural Extension
and Advisory Services in Ethiopia. International Journal
of Academic Pedagogical Research, 123-127.
[9] Bordey, F. (2010). The Impacts of Research on Philippine
Rice Production. Urbana, Illinois: University of Illinois at
Urbana-Champaign.
[10] Briones, R. M., Galang, I. M., & Latigar, J. S. (2023).
Transforming Philippine Agri-Food Systems with Digital
Technology: Extent, Prospects, and Inclusiveness.
Quezon City: Philippines Institute for devleopment
Studies.
[11] Castiblanco Jimenez, I., Cepeda García, L., Marcolin, F.,
Violante, M., & Vezzetti, E. (2021). Validation of a TAM
Extension in Agriculture: Exploring the Determinants of
Acceptance of an e-Learning Platform. Appied Sciences.
doi:https://doi.org/10.3390/app11104672
[12] Castiblanco Jimenez, I., Cepeda Garcia, L., Violante, M.
M., & Vrezzetti, E. (2020). Commonly Used Externl TAM
Variablesin e-Learning, griculture and Virtual Reality
Appliccation. Future Internet.
doi:https://doi.org/10.3390/
[13] Choi, W., & Tulu, B. (2017). Effective Use of User
Interface and User Experience in an mHealth
Application. 50th Hawaii Internationl Conference on
System Sciences, (pp. 3803-3812).
[14] Christoplos, I. (2010). Mobilizing the potential of rural
and agricultural extension. Rome: Food and Agriculture
Organization of the United Nations.
[15] Davis, F. D. (1989). Perceived Usefulness, Perceived Ease
of Use, and User Acceptance of Information Technology.
MIS Quarterly, 319-340.
doi:https://doi.org/10.2307/249008
[16] Dijk, V., & Jan, A. (2005). The deepening Divide:
Inequality in the Information Society. Thousands Oaks
CA London: Sage Publications.
[17] Gapasin, D. P. (2006). Rural Growth and Development
Revisited Study: Agricultural Research, Development
and Extension. Manila: The Worldbank Group East Asia
and the Pacific Region.
[18] Gefen, D., & Straub, D. W. (2000). The Relative
Importance of Perceived Ease of Use in IS. Journal of the
Association for Information Systems.
doi:10.17705/1jais.00008
[19] IFPRI. (2022, April 30). Agricultural Extension. Retrieved
April 30, 2020, from IFPRI website:
https://www.ifpri.org/topic/agricultural-extension
[20] IRRI. (2021). Rice Crop Manager Harnessing Digital
Agriculture: Lessons from the Philippines. Los Baños,
Laguna: International Rice Research Institute.
[21] Kabir, K. H., Hassan, f., Mukta, M. Z., Roy, D. D.,
Leggette, H., & Ullah, S. A. (2022). Application of the
technology acceptance model to assess the use and
preference of ICTs among field-level Extension Officers
in Bangladesh. Science Direct.
[22] Kale, R. B., Meena, M., & Singh, S. (2017). Constraints and
Suggestions Perceived by KVK Scientists in Utilization of
ICT for Agricultural Extension. Journal of Community
Mobilization and Sustainable Development, 12(1), 21-24.
[23] Kante, M. (2021). An ICT-Based Extension Services'
Adoption Model for Public Extension Officers: A Case in
Mali. Journal of Information Systems and Technology
Management – Jistem USP.
[24] Kim, J., Torneo, A., & Yang, S. (2019). Philippine
Readiness for the 4th Industrial Revolution: A Case
Study. Retrieved January 28, 2022, from AsiapPacific
Social Science Review: http://www.apssr.com/wp-
content/uploads/2019/03/RA-9-R.pdf
[25] Lewis, J. R. (2019). Comparison of four TAM Item
Formats: Effect of Repsonse Option Labels and Orders.
Journal of Usability Studies, 14(4), 224-236.
[26] Manalo, J., Balmeo, K., Berto, J., & Saludez, F. (2016).
Youth and Agriculture: The Infomediary Campaign in the
Philippines. Science City of Munoz, Nueva Ecija: DA-
PhilRice and DA-Bureau of Agricultural Research.
[27] Natural Resources Institute. (2014). Agricultural
Extension, Advisory Services and Inovation. London:
University of Greenwhich.
[28] Obed, R. A. (2019). Use of Information and
Communication Technologies among Farmers and
Extension Workers and Its Relevance to the Agricultural
Devleopment in the Province of northern Samar.
International Journal of Economics and Management
Studies, 6(4), 85-91.
[29] Official Gazette. (2022, July 27). Official Gazette.
Retrieved from Official Gazette Website:
https://www.officialgazette.gov.ph/1997/12/22/republic-
act-no-8435-s-1997/
[30] Padin, M. (2015, August 26). ‘Enrollment in agriculture
courses continues to decline’. Retrieved January 28,
2022, from Business Mirror:
https://businessmirror.com.ph/2015/08/26/enrollment-in-
agriculture-courses-continues-to-decline/

[31] Palis, F. G. (2020). Aging Filipino Rice Farmers and their
Aspiations for their Children. Philippine Journal of
Science, 11.
[32] PhilRice. (2021, June). Digital Agriculture- How Can We
Make It Work? Rice Science for Decision-makers. Science
City of Muñoz, Nueva Ecija, Philippines: Philippine Rice
Research Institute.
[33] Sachs, J. D., & Modi, V. (2015). - ICT and SDGs: How
Information and Communications Technology Can
Accelerate Action on the Sustainable Development
Goals. New York: Earth Insittute at the Columbia
University, Ericsson, International Telecommunications
Union, GSMA.
[34] Sivakumar, P. S., Bibudha, P., Raghu, N. D., &
Mathevanpillai, A. (2014). Determinants of computer
utilization by extension personnel: A structural
equations approach. The Journal of Agricultural
Education and Extension , 191-212.
[35] Soomro, K. A., Kale, U., Curtis, R., Akcaoglu, M., &
Bernstein, M. (2020). Digital divide among higher
education faculty. International Journal of Educational
Technology in Higher Education.
[36] Tabuga, A. D., & Cabaero, C. C. (2021). Filipinos' Access
and Exposure to ICT: A General OVerview based on the
National ICT Household Survey. Quezon City: Philippine
Institute for Development Studies.
[37] Tambo, J. A., Aliamo, C., Davis, T., Mugambi, I., ROmney,
D., Onyango, D. O., . . . Byantwale, S. K. (2019). The
impact of ICT-enabled extension campaign on famrers'
knowledge and management of fall armyworm in
Uganda. PLOS One, 1-21.
doi:https://doi.org/10.1371/journal.pone.0220844
[38] United Nations. (2015). Resolution adopted by the
General Assembly on 25 September 2015. New York,
USA: United Nations.

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Expanding the Technology Acceptance Model to Predict ICT Utilization in Agricultural Extension in Isabela, Philippines