































   Advancements in Agricultural Development 
  Volume 5, Issue 3, 2024 
  agdevresearch.org 

 

1. Rachel Hendrix, Assistant Professor of Agricultural and Extension Education, West Virginia University, 4424 Agricultural 
Sciences Building 1195 Evansdale Dr. Morgantown, WV 26506, rachel.hendrix@mail.wvu.edu,  

 https://orcid.org/0000-0002-1693-2019  
2. Travis Veach, Agricultural Educator at Washington High School, Washington High School 300 Patriot Drive, Charles Town, 

WV 25414, travis.veach@k12.wv.us  
3. Emily Perdue – Former Assistant Professor of Agricultural and Extension Education, West Virginia University,  

 https://orcid.org/0009-0003-8340-9118  
79 

 

West Virginia Agricultural Educators’ Usage of Internet-Based 
Instructional Technology 

 
R. Hendrix1, T. Veach2, E. Perdue3 

 
 

Article History 
Received: November 29, 2023 
Accepted: April 25, 2024 
Published: May 14, 2024 
 
 
Keywords 
diffusion of innovations; events of 
learning; broadband access; remote 
instruction; classroom technology 
  

Abstract 
Technology is vital to American education. Each year schools spend 
millions of dollars on various technologies intended for use in classrooms, 
but research shows over a third of this equipment goes unused. This 
study explores how West Virginia agricultural educators make decisions 
about adopting and integrating internet-based technology into their 
classrooms. Results showed educators were most likely to use learning 
management systems and search engines, and least likely to use 
websites, apps, games, and the online curriculum platform iCEV. 
Educators integrated technology into their classrooms primarily by using 
it to provide and review lesson content with classes. Less common uses 
included introducing, activating, and assessing learning. 

mailto:rachel.hendrix@mail.wvu.edu
https://orcid.org/0000-0002-1693-2019
mailto:travis.veach@k12.wv.us
https://orcid.org/0009-0003-8340-9118


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   80 
 

Introduction and Problem Statement 
 
Modern agricultural practices rely on technology to assist in the production food and fiber. 
Technological advances allow agriculturists to improve the output, profitability, efficiency, and 
safety of their operations while reducing environmental impact (United States Department of 
Agriculture National Institute of Food and Agriculture [USDA NIFA], 2023). If agricultural 
education programs are to prepare students for technology-based careers and educate the 
populace about agriculture in the 21st Century, we must examine how agricultural educators 
integrate technology into their classrooms.  

The most common type of technologies used in U.S. classrooms, and in agricultural education 
classrooms, are those available through the Internet (Tsai et al., 2011; Vega & Robb, 2019, 
Williams et al., 2014a). These technologies include video sharing websites, learning 
management systems (LMS), apps, games, and online educator resources (Vega & Robb, 2019). 
Use of such technology in the classroom supports student learning, creativity, and motivation 
while improving teachers’ abilities to differentiate course concepts and provide easy, more 
affordable access to course materials (Bekele, 2010; Williams et al., 2014a). Factors impacting 
agricultural educators’ technology use include cost, availability, complexity, learning time, 
implementation time, support, and positive modeling of the technology during the teacher 
education process (Al-Ruz & Khasawneh, 2011; Coley et al., 2014; Williams et al., 2014b).  

Reports show many successful educational technologies go completely unused due to lack of 
access, support, and teacher efficacy with the product (Crossley & McNamara, 2017). In some 
cases, this phenomenon extends to least one third of all educational technology products 
purchased by schools (Binkley, 2013; Glimpse K12, 2019; Vega & Robb, 2019; Yoder, 2023). 
Educators may also implement ineffective technologies – or use technologies ineffectively – 
due to inexperience, personal preference, outside influences, and educational mandates 
(Glimpse K12, 2019; Vega & Robb, 2019; Yoder, 2023). The Glimpse K12 Analysis of School 
Spending (2019) estimates that this non-use of technology costs schools over five billion dollars 
each year. 

Theoretical and Conceptual Framework 
 
Rogers’s Diffusion of Innovations 
Rogers’s theory of the Diffusion of Innovations (2003) forms the basis of this study. This theory 
examines how individuals within a social system evaluate an innovation’s utility and make 
decisions regarding the adoption or rejection of that innovation through trial and 
communication. Factors influencing an individual’s decision to adopt an innovation include the 
qualities of the innovation itself, communication methods, time, and social system 
characteristics (Rogers, 2003).  

Rogers (2003) divides the diffusion process into five stages: knowledge, persuasion, decision, 
implementation, and confirmation. First, an individual learns about the innovation and asks 
questions regarding its purpose, use, and ability to address needs. Next, that individual 

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   81 
 

experiments with and develops attitudes about the innovation before deciding on its suitability. 
If the innovation is adopted, it is then implemented into everyday life for a trial period. 
Following this trial period, the individual then decides if permanent adoption is warranted.  

After adoption, discontinuation or alteration can occur (Rogers, 2003). These processes result 
from dissatisfaction with or misuse of the original innovation. Discontinued innovations will die 
out as they pass through a social system and never reach sustained adoption. Altered 
innovations will remain in the system, although in a different form than originally intended. 
Successful reinvention of an innovation increases the likelihood of adoption and decreases the 
time necessary for the diffusion process to occur. The innovations most likely to be reinvented 
are those offering individuals more freedom of and possibilities for use (Rogers, 2003; Sahin, 
2006). Sahin (2006) notes technologies such as computers are particularly ripe for reinvention, 
as they allow “many possible opportunities and applications” (p. 4). 

Rogers (2003) described five characteristics which impact an individual’s decision to either 
adopt or reject an innovation: relative advantage, compatibility, complexity, trialability, and 
observability. Relative advantage refers to an innovation’s superiority over existing ideas, 
systems, or options. Compatibility describes an innovation’s fit within the needs, beliefs, and 
situations inherent to a social system. Complexity refers to the perceived level of difficulty 
associated with using an innovation as intended. Trialability is the degree to which an 
innovation may be experimented with or tested by potential adopters. Observability is 
concerned with the visibility and impact of outcomes which arise from an innovation. 
Innovations in possession of high levels of relative advantage, compatibility, trialability, and 
positive observability, alongside low levels of complexity, are more likely to be adopted.  

Gagné’s Events of Instruction 
The in-class usage methods for technology included in this study were derived from the work of 
Gagné et al. (1992), which described the purposeful development of quality educational lessons 
through a systematic process. This process was derived from a model of events that occur when 
adults are presented with learning outcomes and related stimuli and was designed to structure 
the learning process in the most effective manner based off that model (Gagné et al., 1992). 
Gagné et al. (1992) originally proposed nine distinct steps in their lesson design procedure, but 
some steps were combined for clarity and to reduce survey length. The sequence of these steps 
was kept intact to maintain fidelity to Gagné et al.’s (1992) original model. These changes were 
made with the guidance and approval of Agricultural and Extension Education faculty at West 
Virginia University. 

Purpose 
 
The purpose of this study was to explore West Virginia agricultural educators’ use of internet-
based technology in their classrooms and identify connections between technology use 
patterns and respective adoption characteristics. In doing so, agricultural educators and teacher 
educators can gain a more thorough understanding of how internet-based technology is 
currently used in the classroom, and how the differing attributes of such technology can create 

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   82 
 

more impactful learning opportunities for students when used in appropriate contexts. Specific 
objectives guiding this study included: 
1. Identify how many West Virginia agricultural educators have access to reliable internet 

service and technology in their classrooms. 
2. Identify the frequency with which West Virginia agricultural educators used specific 

internet-based technologies in the classroom in their lessons. 
3. Examine when and how agricultural educators in West Virginia integrate internet-based 

technologies into their lessons. 
 

Methods 
 
This descriptive study explored West Virginia agricultural educators’ internet-based technology 
habits and preferences. The population for this study included all agricultural educators 
employed in West Virginia (N = 103). The Tailored Design Method (Dillman et al., 2014) was 
used to guide instrument design and participant contact procedures. Participants were 
contacted by email and asked to complete an online survey instrument on technology usage in 
their classroom. Participants that did not respond after two weeks received a reminder email 
and a telephone call asking them to complete the survey or provide information orally. Those 
who did not respond after four weeks received a second similar reminder. At the close of the 
survey period, 32 agricultural educators provided usable data, offering a 31% response rate. 
Differences in early respondents and late respondents were not significant. 

The instrument was composed of four sections. The first section asked respondents if they used 
internet-based technologies in their classrooms, and if they had reliable access to internet and 
technology sources provided by their school. The second section queried if participants used 
selected internet-based technologies, and if so, how frequently this use occurred. Frequency 
responses were recorded on a four-point Likert-type scale ranging from “always = 4” to “rarely 
= 1.” The third section asked respondents to indicate when and how each technology was 
integrated into regular learning activities.  The fourth section collected respondents’ 
demographic information. Researchers used Cronbach’s alpha to measure the reliability of the 
statements included on the instrument. All statements demonstrated a Cronbach’s alpha of .70 
or above, which is acceptable in social science research (Nunnally, 1994). 

The types of internet-based technology included in the study were derived from Vega and Robb 
(2019), which included search engines, learning management systems (LMS), virtual field trips, 
video sharing platforms, and supplemental materials such as apps and games. The researchers 
chose to add the iCEV website to the survey because it is commonly used in West Virginia as a 
technological teaching aid. iCEV provides subscribing teachers with Career and Technical 
Education-specific resources including lesson plans, videos, activities, study materials, and 
assessments (iCEV, 2024). iCEV was founded in 1987 and is now used in over 2,000 classrooms 
worldwide (iCEV, 2022). 

To ensure validity, the survey was first examined by a panel of agricultural education teacher 
educators at West Virginia University, and pilot tested on Mississippi secondary agricultural 

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   83 
 

educators. Mississippi was chosen because it possessed levels of in-school technology and 
internet access similar to those in West Virginia. Data were analyzed for frequencies, means, 
and standard deviations using IBM® SPSS® 27.0 for Windows (2021).  

The primary limitation for this study involved the fact that participants were contacted only via 
email and not through other means. This contact method made it more likely that respondents 
would be more familiar with, and thus more likely to use, technology. Even though all 
agricultural educators in West Virginia are given email addresses by the West Virginia 
Department of Education, it is possible that some educators did not see the email, did not know 
how to complete an online survey, or did not feel comfortable doing so.  

A second limitation for this study involves technology access for teachers. Not all respondents 
said their schools offered reliable internet access. As participants were contacted over the 
Internet through official school email addresses, some agricultural educators in West Virginia 
may have been unable to access their email or the survey. Access to equipment is a reported 
issue regarding technology adoption in schools and is most likely to occur in Title I schools 
(Vega & Robb, 2019). These findings cannot be generalized to other agricultural education 
programs in other states and territories. 

Findings 
 
Thirty-two educators completed the study for a response rate of 31.06% (n = 32). Eighteen 
respondents identified themselves as male (56.30%) 13 as female (41.60%), and two did not 
provide their gender (3.10%). The average length of respondents’ teaching careers was 14.63 
years (SD = 10.20).  

Research Objective One 
Of the 32 respondents, 31 (96.88%) reported having reliable internet and technology access in 
their school building on a regular basis. All 32 respondents (100%) stated their students had 
access to such resources, either through personal or school-owned devices. This access made it 
possible for every responding educator to utilize at least one form of internet-based technology 
in their classrooms. Such findings agree with the idea that technology is important in 
agricultural education classrooms, and with Vega and Robb’s (2019) estimate of 95% of 
teachers using technology in some form.  They also agree with Tsai et al.’s (2011) finding that 
internet searches are one of the most common forms of technology use in classrooms. Smith et 
al. (2018) noted use of student-owned devices such as smartphones is becoming more common 
in schools which do not have the resources to provide reliable technology access for all. 

Research Objective Two  
This study explored how frequently respondents used each piece of internet-based technology 
in their everyday classroom instruction. Respondents indicated if they “always,” “often,” 
“occasionally,” or “rarely” used the technology. “Always” was defined as use of the technology 
every day, “often” described use a few times a week, “occasionally” referred to use a few times 
a month, and “rarely” referred to use only a few times a semester.  

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   84 
 

Results showed a clear hierarchy of internet-based technology use in West Virginia agricultural 
education classrooms. Technologies which displayed a variety of uses and allowed input from 
the teacher proved to be much more popular and frequently used than those which were not. 
Table 1 illustrates West Virginia agricultural educators’ technology preferences and use 
frequencies. 

Table 1 
 
Frequency of use of Internet-based technology  
 Always Often Occasionally Rarely 
Technology f % f % f % f % 
LMS 17 53.13 11 34.38 3 9.38 1 3.13 
Search Engines 10 31.25 18 56.25 3 9.38 1 3.13 
Virtual Field Trips 0 0.00 1 3.45 15 51.72 13 44.83 
Video Sharing Platforms 1 3.5 14 50.00 6 21.43 7 25.00 
Apps/Games 1 3.57 4 14.29 10 35.71 13 46.42 
iCEV 4 18.18 7 31.82 4 18.18 7 31.82 

 
Learning management systems demonstrated the greatest frequency of use and widest levels 
of adoption of all technologies. All 32 respondents (100%) used LMS as part of their classes, and 
over half (f = 17, 53.13%) used it every day. Eleven employed it “often” (34.38%), while three 
used it “occasionally” (9.38%), and one respondent “rarely” used it (3.13%).  

All respondents (n = 32, 100%) used search engines, although less frequently than they did LMS. 
Ten respondents “always” used search engines (31.25%), while 18 used them “often” (56.25). 
Three used them “occasionally,” (9.38%), and one used them “rarely” (3.13%). In a 10-year 
review of literature regarding educational technology integration, Tsai et al. (2011) found 
search engines to be the most commonly integrated piece of internet-based technology on a 
global scale. While this may be still the case, in many countries use of Learning Management 
Systems surged during the height of the COVID-19 pandemic, as there were few other safe 
options for educating students (Lee et al., 2022; Prat et al., 2021). If this study had been 
performed prior to the pandemic, it is likely that LMS use would be lower. 

Virtual field trips were seen as more of a niche product useful in certain educational situations. 
Twenty-nine respondents (90.63%) said they used virtual field trips at least once a semester, 
while three (9.37%) did not use virtual field trips at all. No respondent used them every day, 
although one (3.45%) did employ them “often.” Most respondents accessed virtual field trips 
on an occasional (n = 15, 51.72%) or rare (n = 13, 44.83%) basis, likely during specific lessons for 
which they either had a virtual field trip opportunity available or felt one to be advantageous to 
the learning process. 

Twenty-eight respondents (87.50%) used video sharing platforms in their classes. Over 70% of 
those who did used them either “often” (n = 14, 50.00%) or “occasionally” (n = 6, 21.43%), 
indicating that they, like virtual field trips, were helpful in specific circumstances only. One 

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   85 
 

respondent (3.50%) used them every day, and a quarter of users (n = 7, 25.00%) called upon 
them “rarely.” 

Apps and games were not frequently included as part of normal learning activities. Only 28 
respondents said they used them (87.50%) at all, and most of those did so rarely (n = 13, 
46.42%), or occasionally (n = 10, 35.71%). A few included them in lessons on a frequent basis (n 
= 4, 14.29%), and one “always” did so (n = 1, 3.57%). 

The final technology included in this study was iCEV. iCEV was polarizing to respondents, 
demonstrating the lowest number of total users (n = 22, 68.75%) and an interesting pattern of 
use. Half of those who implemented iCEV in their classrooms did so all (n = 4, 18.18%) or most 
(n = 7, 31.82%) of the time. The other half of iCEV users chose to include it in their lessons 
occasionally (n = 4, 18.18%) or rarely (n = 31.82%). Considering iCEV is a paid subscription 
service for pre-made lesson plans, activities, videos, and assessments, it is interesting to note 
that half of respondents did not use it much, despite making an investment to purchase it. This 
indicates iCEV may not be meeting teachers’ needs, or may be purchased at a district level, 
similar to LMS. 

Research Objective Three 
Research Objective Three examined when and how agricultural educators integrated internet-
based technologies into their lessons. Lesson segments were derived from the work of Gagné et 
al. (1992) and included lesson introductions, activating strategies, content provision, reviews, 
and assessments. Table 2 shows West Virginia agricultural educators’ usage of internet-based 
technology divided by lesson segment in further detail. 

Table 2 
 
Use of Internet-based technology in West Virginia agricultural education classrooms 
 Internet-Based Technology 
  

LMS 
Search 
Engine 

Video 
Sharing 
Website iCEV 

Apps 
and 

Games 

Virtual 
Field 
Trips Total 

Lesson 
Component 

Introduction 14 17 24 10 3 12 80 
Activating 

Strategy 
17 18 8 9 10 6 68 

Lesson 
Content 

25 25 21 18 5 12 106 

Review 22 16 20 12 15 7 92 
 Assessment 23 6 6 9 8 2 54 
Total  101 82 79 58 41 39 761 

 
Results indicated that teachers were most likely to use technology during the content provision 
portion of their lessons (f = 106), followed by review (f = 92), and introduction (f = 80) portions. 

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   86 
 

Teachers were least likely to use technology during the activating strategy (f = 68) and 
assessment (f = 54) segments of lessons.  

Learning management systems were the most frequently used technology during classroom 
lessons (f = 101), with most usage occurring during the content provision, assessment, and 
review segments. Search engines (f = 82), video websites (f = 79) also had high frequencies of 
use, especially during content provision, introductions, and reviews. iCEV (f = 58), apps and 
games (f = 41), and virtual field trips (f = 39) were the least commonly used of all technologies.  

These findings demonstrate agricultural educators in West Virginia have specific uses and 
preferences for technology in their classrooms. However, there are some instances where 
educators may not be using technology to its fullest potential. Apps and games were not often 
used in respondents’ classes, and when they were, it was often for review purposes. However, 
Ting (2010) found games could serve as a useful method for activating student interest in a 
topic before beginning actual instruction. Only ten respondents used apps or games in such a 
manner. Similarly, results showed respondents did not use technology as much for 
assessments, preferring more traditional formats instead. These results indicate a need for 
greater technological creativity to be modeled during the teacher education process. 

Conclusions, Discussion, and Recommendations 
 
Results of this study confirm the importance of internet-based technology in the agricultural 
education classroom. Most classrooms in West Virginia had reliable internet access and school-
owned technology, but in some cases students’ personal devices were required. The authors 
recommend identifying methods of technology implementation for agricultural education 
programs in such situations. They recommend performing such an analysis through survey 
methods that do not use the internet in order to catch programs which may have been left out 
of this study due to poor internet or technology availability. 

Most of the internet-based technologies included in the study showed sustained and wide 
adoption. These technologies are essential to online learning, open to reinvention, and in 
possession of key attributes that Rogers (2003) linked with successful adoption. This finding is 
supported by observing the ways in which participants used each technology in their 
classrooms, as the most frequently used were also those implemented during a variety of 
lesson plan components. Learning Management Systems and search engines demonstrated 
high levels of relative advantage, compatibility, trialability, and observability and low 
complexity. They require little effort or knowledge to use, are accessible on small screens and 
slower connections, are useful to teachers and students, and versatile in function. Their use is 
also widely supported throughout K-12 education (Tsai et al.; Vega & Robb, 2019), increasing 
the likelihood that teachers will receive positive affirmation from others about their use 
(Rogers, 2003). In some cases, use of these technologies may be mandated by district or state 
educational leaders, which Rogers (2003) terms an “authority innovation decision” (p. 348). 
This may have led to the high number of Learning Management System users involved in the 
study. Either way, it is essential for educators to use these technologies fluently. The 

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   87 
 

researchers recommend teacher educators teach and model essential LMS and search skills 
during the teacher education process, so teachers (and students in turn) can implement them 
to greater potential in the classroom. Research has shown that an educational technology 
course is not enough for students to master the material; teacher modelling and integration of 
technology into all courses is key (Zipke, 2018). They also recommend helping in-service 
agricultural educators master these technologies through demonstrations at professional 
development events and activities. 

Less frequently used technologies like virtual field trips, video websites, apps and games, and 
iCEV demonstrate less of Rogers’s (2003) characteristics and may be viewed as less useful than 
other options, incompatible with teachers’ expectations, inaccessible on student devices, too 
expensive, or too likely to produce ineffective learning outcomes. While results indicate they 
are useful in certain situations, their specificity and lack of user control may make them difficult 
to implement as widely throughout a lesson. The researchers recommend deeper examination 
into the use of these less-frequently employed technologies. Understanding what virtual field 
trips or videos are used and how games or apps are implemented into class could assist 
teachers with developing more successful, creative, and engaging technology-integrated 
lessons while preparing students for agricultural careers and educating them on modern 
agricultural practices.  

Current app-based agricultural technologies allow users to conduct business, keep records, 
monitor weather and climate information, operate irrigation systems, map fields, manage 
livestock, connect with experts, monitor soil health and fertility, access important information, 
and more (Farm Bureau, 2024; Hopkins, 2024). However, respondents in the study were either 
unaware of or unable to use these capabilities and heavily preferred to use apps for review 
instead of class content provision. Virtual field trips were more likely to be used for content, but 
still underutilized overall. Virtual field trips can allow students to gain insider views of 
agricultural operations that could not physically be visited due to logistic, funding, educational, 
or health and safety issues (Tuthill & Klemm, 2002). Updates with virtual reality programs could 
provide an in-depth, 3D experience integrating not just images, but sounds and narrations as 
well (Wells & Miller, 2020). With so few Americans involved in agriculture directly, viewing 
agricultural practices even remotely could provide valuable insight towards potential careers 
and general knowledge of food and fiber production. Teacher educators should introduce 
educators to these technologies early and require teacher candidates to practice using them 
creatively during lessons, and not just as tools for review.  

The researchers also recommend an investigation into teachers’ use of iCEV due to its 
interesting use patterns. Respondents were polarized regarding its implementation, and 
31.82% admitted to rarely using it, despite either their programs or districts paying for the 
service. Knowing who uses iCEV, how it is implemented, the suitability of iCEV lessons for 
curricular needs, and why it is purchased if not frequently used should be explored. iCEV offers 
both agricultural instruction through technology, and instruction in agricultural technologies, 
allowing it to serve as an effective option for educating about agricultural careers, at least for 
some. 

https://doi.org/10.37433/aad.v5i3.439


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   88 
 

The researchers noted that assessment was the lesson component least tied to technology use. 
Some respondents did use their LMS program or iCEV for assessment, but most seemed to 
prefer more traditional assessment means. The researchers recommend identifying teachers’ 
preferred assessment methods and reasonings behind those preferences. While technology 
may not be appropriate for all assessments in agricultural education, its use could help teachers 
manage submissions, provide more targeted feedback, and evaluate learning in multiple ways. 

Acknowledgments 
 
This work is/was supported by the USDA National Institute of Food and Agriculture, Hatch 
project S1701 and the West Virginia Agricultural and Forestry Experiment Station. 

Author Contributions: R. Hendrix – conceptualization, formal analysis, writing original draft, 
supervision; T. Veach – conceptualization, formal analysis, investigation, writing original draft; 
E. Perdue – Writing and editing, validation. 

References 
 
Al-Ruz, J. A., & Khasawneh, S. (2011). Jordanian pre-service teachers’ and technology 

integration: A human resource development approach. Educational Technology & 
Society, 14(4), 77-87. https://www.jstor.org/stable/10.2307/jeductechsoci.14.4.77 

Bekele, T. A. (2010). Motivation and satisfaction in internet-supported learning environments: A 
review. Educational Technology & Society, 13(2), 116-127. 
https://www.jstor.org/stable/jeductechsoci.13.2.116 

Binkley, C. (2023, October 9). Schools’ pandemic spending boosted tech companies. Did it help 
US students? AP News. https://apnews.com/article/edtech-school-software-app-
spending-pandemic-e2c803a30c5b6d34620956c228de7987 

Coley, M. D., Warner, W. J., Stair, K. S., Flowers, J. L., & Croom, D. B. (2015). Technology usage 
of Tennessee agriculture teachers. Journal of Agricultural Education, 56(3), 35-51. 
https://doi.org/10.5032/jae.2015.03035 

Crossley, S. A., & McNamara, D. S. (2017). Adaptive educational technologies for literacy 
instruction. Routledge. 

Dillman, D. A., Smythe, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode 
surveys: The tailored design method (4th ed.). Wiley. 

Farm Bureau Financial Services. (2024, April 8). Popular apps for farmers and ranchers. 
https://www.fbfs.com/learning-center/popular-apps-for-farmers-and-ranchers 

Gagné, R. M., Briggs, L. J., & Wager, W. W. (1992). Principles of instructional design (4th ed.). 
Harcourt Brace Jovanovich College Publishers.  

https://doi.org/10.37433/aad.v5i3.439
https://www.jstor.org/stable/10.2307/jeductechsoci.14.4.77
https://www.jstor.org/stable/jeductechsoci.13.2.116
https://apnews.com/article/edtech-school-software-app-spending-pandemic-e2c803a30c5b6d34620956c228de7987
https://apnews.com/article/edtech-school-software-app-spending-pandemic-e2c803a30c5b6d34620956c228de7987
https://doi.org/10.5032/jae.2015.03035
https://www.fbfs.com/learning-center/popular-apps-for-farmers-and-ranchers


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   89 
 

Glimpse K12. (2019, May 14). Glimpse K12 analysis of school spending shows that two-thirds of 
software license purchases go unused. https://www.glimpsek12.com/blog-
posts/glimpse-k12-analysis-of-school-spending-shows-that-two-thirds-of-software-
license-purchases-go-unused 

Hopkins, M. (2024). Best agriculture apps for 2024. CropLife. 
https://www.croplife.com/editorial/matt-hopkins/best-agriculture-apps/ 

IBM. (2021). SPSS for Windows [Compute software]. 

iCEV. (2024). [iCEV website homepage]. https://www.icevonline.com/ 

iCEV. (2022, October 12). iCEV acquires Applied Educational Systems (AES) [press release]. 
https://www.icevonline.com/pressroom/2022/icev-acquires-applied-educational-
systems 

Lee, K., Fanguy, M., Bligh, B., & Lu, X. S. (2022). Adoption of online teaching during the COVID-
19 pandemic: A systematic analysis of changes in university teaching activity. 
Educational Review, 74(3), 460-483. https://doi.org/10.1080/00131911.2021.1978401 

Nunnally, J. C., & Bernstein, I. H.(1994). Psychometric theory (3rd ed.), McGraw Hill. 

Prat, J., Llorens, A., Salvador, F., Alier, M., & Amo, D. (2021). A methodology to study the 
university’s online teaching activity from virtual platform indicators: The effect of the 
COVID-19 pandemic at Universitat Politècnica de Catalunya. Sustainability, 13(9). 
https://doi.org/10.3390/su13095177 

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. 

Sahin, I. (2006). Detailed review of Rogers’ diffusion of innovations theory and educational 
technology-related studies based on Rogers’ theory. The Turkish Online Journal of 
Educational Technology, 5(2), p. 1-10. https://files.eric.ed.gov/fulltext/ED501453.pdf 

Smith, H. E., Stair, K. S., Blackburn, J. J., & Easley, M. (2018). Is there an app for that?: Describing 
smartphone availability and educational technology adoption level of Louisiana school-
based agricultural educators. Journal of Agricultural Education, 59(1), 238-254. 
https://doi.org/10.5032/jae.2018.01238 

Ting, Y. L. (2010). Using mainstream game to teach technology through an interest framework. 
Educational Technology & Society, 13(2), 141-152. 
https://www.jstor.org/stable/jeductechsoci.13.2.141 

Tsai, C. C., Chuang, S. C., Liang, J. C., & Tsai, J. M. (2011). Self-efficacy in internet-based learning 
environments: A literature review. Educational Technology & Society, 14(4), 222-240. 
https://www.jstor.org/stable/jeductechsoci.14.4.222 

https://doi.org/10.37433/aad.v5i3.439
https://www.glimpsek12.com/blog-posts/glimpse-k12-analysis-of-school-spending-shows-that-two-thirds-of-software-license-purchases-go-unused
https://www.glimpsek12.com/blog-posts/glimpse-k12-analysis-of-school-spending-shows-that-two-thirds-of-software-license-purchases-go-unused
https://www.glimpsek12.com/blog-posts/glimpse-k12-analysis-of-school-spending-shows-that-two-thirds-of-software-license-purchases-go-unused
https://www.croplife.com/editorial/matt-hopkins/best-agriculture-apps/
https://www.icevonline.com/
https://www.icevonline.com/pressroom/2022/icev-acquires-applied-educational-systems
https://www.icevonline.com/pressroom/2022/icev-acquires-applied-educational-systems
https://doi.org/10.1080/00131911.2021.1978401
https://doi.org/10.3390/su13095177
https://files.eric.ed.gov/fulltext/ED501453.pdf
https://doi.org/10.5032/jae.2018.01238
https://www.jstor.org/stable/jeductechsoci.13.2.141
https://www.jstor.org/stable/jeductechsoci.14.4.222


Hendrix et al.  Advancements in Agricultural Development 
 

https://doi.org/10.37433/aad.v5i3.439   90 
 

Tuthill, G., & Klemm, E. B. (2002). Virtual field trips: Alternatives to actual field trips. 
International Journal of Instructional Media, 29(4), 453-468. 
https://wvu.idm.oclc.org/login?url=https://www.proquest.com/scholarly-
journals/virtual-field-trips-alternatives-actual/docview/204317859/se-
2?accountid=2837 

United States Department of Agriculture National Institute of Food and Agriculture. (2023). 
Agriculture technology. https://www.nifa.usda.gov/topics/agriculture-technology 

Vega, V., & Robb, M.B. (2019). The common sense census: Inside the 21st century classroom. 
Common Sense Media. 
https://www.commonsensemedia.org/sites/default/files/research/report/2019-
educator-census-inside-the-21st-century-classroom_1.pdf 

Wells, T., & Miller, G. (2020). The effect of virtual reality technology on welding skill 
performance. Journal of Agricultural Education, 61(1), 
https://doi.org/10.5032/jae.2020.01152  

Williams, M. R., Warner, W. J., Flowers, J. L., & Croom, D. B. (2014a). Accessibility and usage of 
technology by North Carolina agriculture teachers. Journal of Agricultural Education, 
55(4), 191-205. https://doi.org/10.5032/jae.2014.04191 

Williams, M. R., Warner, W. J., Flowers, J. L., & Croom, D. B. (2014b). Teaching with technology: 
North Carolina agriculture teachers’ knowledge acquisition, attitudes, and identified 
barriers. Journal of Agricultural Education, 55(5), 1-15. 
https://doi.org/10.5032/jae.2014.05001 

Yoder, S. (2023, October 16). School ed tech money mostly gets wasted. One state has a 
solution. The Hechinger Report. https://hechingerreport.org/school-ed-tech-money-
mostly-gets-wasted-one-state-has-a-solution/ 

Zipke, M. (2018). Preparing teachers to teach with technology: Examining the effectiveness of a 
course in educational technology. The New Educator, 14(4), 342-362. 
https://doi.org/10.1080/1547688X.2017.1401191  

 
 
 
© 2024 by authors. This article is an open access article distributed under the terms and conditions of 
the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). 
 

https://doi.org/10.37433/aad.v5i3.439
https://wvu.idm.oclc.org/login?url=https://www.proquest.com/scholarly-journals/virtual-field-trips-alternatives-actual/docview/204317859/se-2?accountid=2837
https://wvu.idm.oclc.org/login?url=https://www.proquest.com/scholarly-journals/virtual-field-trips-alternatives-actual/docview/204317859/se-2?accountid=2837
https://wvu.idm.oclc.org/login?url=https://www.proquest.com/scholarly-journals/virtual-field-trips-alternatives-actual/docview/204317859/se-2?accountid=2837
https://www.nifa.usda.gov/topics/agriculture-technology
https://www.commonsensemedia.org/sites/default/files/research/report/2019-educator-census-inside-the-21st-century-classroom_1.pdf
https://www.commonsensemedia.org/sites/default/files/research/report/2019-educator-census-inside-the-21st-century-classroom_1.pdf
https://doi.org/10.5032/jae.2020.01152
https://doi.org/10.5032/jae.2014.04191
https://doi.org/10.5032/jae.2014.05001
https://hechingerreport.org/school-ed-tech-money-mostly-gets-wasted-one-state-has-a-solution/
https://hechingerreport.org/school-ed-tech-money-mostly-gets-wasted-one-state-has-a-solution/
https://doi.org/10.1080/1547688X.2017.1401191

