TECHNOLOGY ACCEPTANCE MODEL AND THE INFLUENCE OF TWITTER ON K-12 EDUCATORS
A Dissertation Presented to The Faculty of the College of Graduate Studies Lamar University
In Partial Fulfillment of the Requirements for the Degree Doctor of Education in Educational Leadership by Elizabeth Meredith June 2018
TECHNOLOGY ACCEPTANCE MODEL AND THE INFLUENCE OF TWITTER ON K-12 EDUCATORS ELIZABETH MEREDITH Approved: _________________________________ Kaye Shelton Dissertation Chair _________________________________ Neil Faulk Dissertation Co-Chair ________________________________ Diane Mason Committee Member ________________________________ Michael Mills Committee Member
_________________________________ Brett Welch Director, Doctoral Program _________________________________ Diane Mason Acting Chair, Department of Educational Leadership ________________________________ Robert J. Spina Dean, College of Education and Human Development ________________________________ William E. Harn Dean, College of Graduate Studies
© 2018 by Elizabeth Meredith No part of this work may be reproduced without permission except as indicated by the “Fair Use” clause of the copyright law. Passages, images, or ideas taken from this work must be properly credited in any written or published materials.
ABSTRACT TECHNOLOGY ACCEPTANCE MODEL AND THE INFLUENCE OF TWITTER ON K-12 EDUCATORS by Elizabeth Meredith The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. Specifically, this study looked at the results of the Technology Acceptance Model questionnaire regarding the perceived ease of use, perceived usefulness, and behavioral intent to use educational technology by both educators who use Twitter and those who do not. An electronic TAM questionnaire, developed by Venkatesh and Bala (2008) was used with a distributed nonrandom representative population of K-12 teachers from a variety of disciplines, grade levels, and with varying years of experience within the United States. The teachers providing the information required for the study were a mix of users and non-users of Twitter. This study utilized independent t-tests and Pearson product-moment correlation coefficient tests. Findings of this study suggest that using Twitter for educational purposes impacts how useful and easy to use technology is perceived by teachers. In general, teachers who use Twitter had higher mean scores on all determinants of the TAM survey, particularly with perceived usefulness and perceived ease of use. The results of this study have implications for K-12 educators seeking to implement educational technology within their classroom. If teachers who use Twitter more frequently exhibit higher levels of implementation within the classroom, then it can be
concluded more teachers should engage in professional learning activities using the social media site to improve their educational technology deployment. It is important, then, that teachers be provided the opportunity to learn how to use Twitter and engage with the site for professional development.
ACKNOWLEDGEMENTS I would like to express my sincere appreciation to the community of Apple Distinguished Educators who have been tremendously supportive during the past three years in inspiring me to be innovative, collaborative, and persistent in my educational endeavors. I would also like to recognize my amazing wife, who has kept our household in one piece while I’ve spent countless nights typing away in pursuit of my doctoral degree. Lastly, I must thank my dissertation committee for the hours they devoted to reviewing and editing, and their tremendous support throughout this process. It is these people that have paved the way for me to complete this study, and I can’t thank them enough.
iii
Table of Contents List of Tables
viii
List of Fugures
ix
Chapter I
II
Page
Introduction to the Study
1
Background
1
Problem Statement
3
Theoretical Foundation
3
Perceived usefulness, perceived ease of use, and attitude
4
Extending the Technology Acceptance Model
5
The TAM3 model
6
Statement of the Purpose and Research Questions
6
Rationale and Significance of the Study
9
Assumptions
10
Limitations and Delimitations
10
Definitions of Terms
11
Summary and Organization of the Study
12
Review of the Literature
13
Technology Usage in the K-12 Classroom
16
Challenges with educational technology implementation
17
Teachers’ beliefs and TAM
18
Challenges with Collaboration Environmental considerations
iv
19 19
Online vs. traditional methods The Role of Social Media in Collaboration
20 20
Using Twitter as a tool for collaboration
21
Twitter and the Technology Acceptance Model
24
Implications
27
The need for convenient collaboration
27
Interventions to influence perceived ease of use and usefulness 27
III
IV
Literature Review Summary
28
Summary
28
Methodology
29
Purpose of the Study and Research Questions
29
Research Design
32
The Participants and the Setting
33
Instrumentation
36
Data Collection
37
Treatment of the Data
37
Summary
38
Findings or Analysis of Data
39
Research Questions and Hypotheses
39
Teachers’ Use of Twitter
41
Findings for Research Question One
45
Findings for Research Question Two
45
Findings for Research Question Three
46
v
V
Findings for Research Question Four
47
Findings for Research Question Five
48
Findings for Research Question Six
49
Summary
51
Summary, Conclusions, Implications, and Recommendations Summary of the Study
52 52
Brief overview of the problem
52
Purpose statemement and research questions
53
Review of the study design
55
Summary of major findings
56
Research question one
57
Research question two
57
Research question three
57
Research question four
57
Research question five
58
Research question six
58
Conclusions
58
Implications for Practice
60
Recommendations for Future Research
62
Concluding Remarks
63
References
64
Appendices
72
Appendix A IRB Informed Consent Approval
73
vi
Appendix B Email: Invitation to Participate
74
Appendix C Email: Closing Survey
76
Appendix D Statement of Informed Consent
78
Appendix E Survey Instrument
80
Biographical Note
88
vii
List of Tables Table
Page
Table 1 Determinants of TAM Constructs
26
Table 2 Demographic Information of Participants
34
Table 3 Disciplines and Grade Levels Taught by Participants
35
Table 4 Twitter Usage Among Participants
42
Table 5 Amount of Twitter Usage for Moderate to High Participants
42
Table 6 Descriptive Statistics for Users and Non-users of Twitter
44
Table 7 Independent T-tests for Three Variables
47
Table 8 Pearson Product-Moment Correlation Tests for Three Variables
50
viii
List of Figures Figure
Page
Figure 1. Twitter Basics
22
Figure 2. Comparison of Twitter to Perceived Ease of Use, Perceived Usefulness, and Behavioral Intent
51
ix
Meredith
1
Chapter I Introduction to the Study Although increased spending has worked to add educational technologies into K12 schools, teacher implementation within the classroom has been a challenge (Laferrière, Hamel, & Searson, 2013). Properly utilizing technology to enhance student learning and achievement requires teachers to make changes for which most are unprepared (Shirley, Irving, Sanalan, Pape, & Owens, 2011). Consequently, multiple factors play a role in the slow progression of educational technology, including lack of professional development and time to learn and implement new tools (Hsu, 2016). To combat these challenges, collaborative Professional Learning Communities (PLCs) have been utilized and shown to successfully impact teacher performance and skill development (Battersby & Verdi, 2015), but there also exist many barriers to the traditional methods of face-to-face collaboration (Johnson, 2015). Alternative methods, through social media sites such as Twitter, offer a more convenient way for teachers to collaborate and form Professional Learning Networks (PLNs), connecting with others on specific topics of which they can learn from one another (Trust, Krutka & Carpenter, 2016). This study sought to examine if those educators who use Twitter for such collaborative purposes might exhibit a higher degree of educational technology implementation within their classroom. Background Recent changes in educational technology have opened the gateway for student success in the 21st century, transforming traditional methods of teaching and learning (Thota & Negreiros, 2015). Studies show improved student performance and academic
Meredith
2
achievement when integrating educational technology into the K-12 curriculum (Pierce & Cleary, 2014). Whereas government spending has helped put technology into schools, the implementation within the classroom has been slow (Shirley et al., 2011). Among the many reasons for poor implementation are improper infrastructure, minimal availability of educational applications, and lack of educator training on how to effectively use educational technology in the classroom (Pierce & Cleary, 2014). Studies have identified multiple barriers to educational technology implementation, including a lack of exposure to technology (Hsu, 2016), lack of professional development (Hew & Brush, 2006) and negative beliefs about the effectiveness of technology in the classroom (Kale & Goh, 2014). A separate body of research, however, has led to the creation of the Technology Acceptance Model (TAM), a highly-tested theory that has identified two key factors related to technology usage: perceived usefulness and perceived ease of use (Ramayah, Ma’ruf, Jantan, & Mohamad, 2002). TAM, first proposed by Davis (1989), has been validated in numerous studies (Donaldson, 2011; Fan, 2014; Hidayanto & Setyady, 2014; Ramayah et al., 2002; Shroff, Deneen, & Ng, 2011; Yuan, et al, 2017), showing these two conditions to be a strong determinant for degree of technology implementation. Davis (1989) explained if a user feels the particular technology will aid him or her at his or her job, the user is more likely to implement the tool. In addition, if the user perceives the technology as easy to use, he or she is more likely to utilize it (Davis, 1989). Other factors, such as attitude towards use and intent to use, affect implementation as well (Ramayah et al., 2002). The implication within the classroom setting is teachers must see the usefulness of educational technology, and they must feel capable of using the technology (Hew & Brush, 2007).
Meredith
3
Social media such as Twitter can be useful for collaboration (Mills, 2014), but it is unclear whether or not social media is effective in helping teachers to learn and implement new skills, in particular, educational technology integration. Studies have been conducted on the use of social media for organizational collaboration (Cardon & Marshall, 2014), but less research exists on its use within K-12 educational institutions. This means more research must be conducted on the use of social media (i.e., Twitter for this research application) and its usefulness for collaboration, especially as it relates to helping teachers implement educational technology. Problem Statement The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. Specifically, this study looked at the results of the TAM questionnaire regarding the perceived ease of use, perceived usefulness, and behavioral intent to use educational technology by both educators who use Twitter and those who do not. The researcher sought to identify if a relationship existed regarding Twitter usage for educational purposes and educational technology usage by K-12 teachers. Theoretical Foundation A variety of models exist to explain why individuals choose to accept and use new technology in both personal and professional settings (Shroff et al., 2011). The Technology Acceptance Model (TAM), first published by Fred Davis (1989), attempts to organize the multiple factors into two main determinants: perceived usefulness of the
Meredith
4
technology and its perceived ease of use. Davis (1989) also identified one’s beliefs, attitudes and intention to use the technology as influencing one’s usage behavior. Since the theory’s inception, multiple studies (Donaldson, 2011; Fan, 2014; Hidayanto & Setyady, 2014; Ramayah et al., 2002; Shroff et al., 2011; Yuan et al., 2017) have validated the relationship between the perceived usefulness and ease of use of a particular technology and one’s behavioral intention towards its use. Previous research shows a direct correlation between users’ behavioral intentions and their documented usage of the technology (Yi & Hwang, 2003). A user’s behavioral intention is influenced by how easy the technology is perceived to be as well as how useful it appears. In other words, if the technology is seen as easy to use and useful for a specific purpose, then one is more likely to use it (Shroff et al., 2011). Additional factors related to perceived ease of use and perceived usefulness have been identified by Venkatesh and Davis (2000) and Venkatesh and Bala (2008). Taking these factors into account, the TAM model could offer an explanation as to why there exists a shortage of educational technology being effectively implemented within the K-12 classroom. The following sections discuss the determinants of perceived usefulness, perceived ease of use, and attitude, and how they have been studied and extended into the TAM2 and TAM3 models. Perceived usefulness, perceived ease of use, and attitude. Davis (1989) first defined perceived usefulness as “the degree to which an individual believes that using a particular system would enhance his or her productivity” and perceived ease of use as “the degree an individual believes that using a particular system would be free of effort” (p. 320). Continuous research on these two determinants has shown perceived ease of use has a significant impact on perceived usefulness as well as attitude toward using a tool or
Meredith
5
system (Shroff et al., 2011). The study done by Shroff et al. (2011) further explained if the technology is not easy to use, then people will not perceive it as useful, indicating that perceptions about usefulness and ease of use determine whether there will be intention to use the technology. However, Ramayah et al. (2002) found perceived usefulness had a stronger and more consistent effect on usage than did other factors, stating that there could exist a relationship between one’s beliefs about the technology and their intent to use. The underlying principle of TAM is a positive correlation between how useful and easy technology is perceived and a user’s behavioral intent to implement, meaning that the easier and more useful the technology is viewed, the more likely the usage of technology will increase (Fan, 2014). Furthermore, the effect from outside influential factors, like system design, will be minimized by the factors of perceived usefulness and perceived ease of use (Venkatesh & Bala, 2008). Extending the Technology Acceptance Model. A study done by Venkatesh and Davis (2000) explained factors that influence perceived usefulness and behavioral intent. Called the TAM2, this model posits the relationship between achieving work related tasks and the ramifications in using technology determines one’s perceptions of the technology’s usefulness (Venkatesh & Davis, 2000). Laid out in this extended model, social influence and cognitive instrumental processes are responsible for the influence determinants have on perceived usefulness and behavioral intent. Venkatesh and Davis (2000) tested the social influence of subjective norm and image in relation to perceived ease of use. They also tested the cognitive instrumental processes of job relevance, output quality, and result demonstrability as they relate to perceived usefulness and usage
Meredith
6
intention. Also, they tested experience and voluntariness as they relate to perceived usefulness. Their results indicated a strong foothold for the TAM2 model (Fan, 2014). The TAM3 model. More recent studies have extended the TAM model even further, combining the TAM2 and determinants of perceived usefulness (Venkatesh & Davis, 2000) with factors of perceived ease of use: computer self-efficacy, perception of external control, computer anxiety, computer playfulness, perceived enjoyment, and objective usability (Adetimirin, 2015; Venkatesh & Bala, 2008). Now called TAM3, the theory makes up for gaps in TAM2 by explaining how experience can lessen the effect of perceived ease of use on perceived usefulness, and the determinants of perceived ease of use won’t affect perceived usefulness (Venkatesh & Bala, 2008). TAM3 also suggests “that experience will moderate the relationships between (i) perceived ease of use and perceived usefulness; (ii) computer anxiety and perceived ease of use; and (iii) perceived ease of use and behavioral intention” (Venkatesh & Bala, 2008, p. 281). Statement of the Purpose and Research Questions The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. For this study, six research questions and hypotheses were addressed: 1. RQ1: Is there a difference in perceived usefulness of educational technology between users and non-users of Twitter? o RQ1 Hypothesis:
§
H0: There is no difference in perceived usefulness of
Meredith
7
educational technology between users and non-users of Twitter. §
H1: There is a difference in perceived usefulness of educational technology between users and non-users of Twitter.
2. RQ2: Is there a difference in perceived ease of use of educational technology between users and non-users of Twitter? o RQ2 Hypothesis:
§
H0: There is no difference in perceived ease of use of educational technology between users and non-users of Twitter
§
H1: There is a difference in perceived ease of use of educational technology between users and non-users of Twitter.
3. RQ3: Is there a difference in teachers’ intent to use educational technology between users and non-users of Twitter? o RQ3 Hypothesis:
§
H0: There is no difference in teachers’ intent to use educational technology between users and non-users of Twitter.
§
H1: There is a difference in teachers’ intent to use educational technology between users and non-users of Twitter.
4. RQ4: Does a relationship exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators?
Meredith
8
o RQ4 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators.
5. RQ5: Does a relationship exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators? o RQ5 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators.
6. RQ6: Does a relationship exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators? o RQ6 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
Meredith §
9
H1: A relationship does exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
Rationale and Significance of the Study Barriers regarding lack of professional development, negative beliefs, and exposure to technology could potentially be overcome if teachers consistently participated in collaborative learning opportunities that afforded them the knowledge, skills, and beliefs necessary for successful technology integration (Laferrière et al., 2013). Previous research has demonstrated problems associated with traditional methods of face-to-face collaboration such as geographic isolation (Johnson, 2015), but social media has provided a new venue for facilitating PLNs (Mills, 2014). Twitter could potentially be a method in which to form effective collaborations, exposing educators to information that might change their perspectives and thereby increase implementation of educational technology. Twitter was chosen as the social media platform for this study because of the increased use of the site by educators as a professional development tool. Research has shown it to be one of the most popular microblogging platforms and it has been utilized for multiple educational activities (Marin & Tur, 2014). Although social media has been shown to positively impact collaboration (Mills, 2014), it has not been researched for its ability to invoke change within teachers’ technology usage. Many studies have been conducted on the validity of the TAM model, but few have identified interventions necessary to change a participant's responses (Venkatesh & Bala, 2008). Additionally, research has been done on the barriers of educational technology implementation (Hew & Brush, 2006; Laferrière et al., 2013), but
Meredith 10 none have investigated the effects of social media collaborations. A quantitative study on social media’s ability to impact educational technology usage in the classroom may shed light on this unexplored topic. Through such a study, teachers could learn of the possibilities of educational technology, changing their perception of its use in the classroom and in turn impacting students as they learn from educators that purposefully and effectively use technology in the classroom. Assumptions An assumption in research is a factor in the study that is accepted as true and guides in the collection and analysis of data (Creswell, 2015). In this study, it was assumed participants were able to properly use the online platform to answer the TAM survey questionnaire. All participants received instructions on how to properly utilize the Qualtrics platform used to disseminate the questions. It was also assumed participants were honest and truthful in their responses to the TAM survey instrument, as they were assured of the confidentiality of the study and their option to withdraw at any time. Limitations Within a study, limitations are influences that are not controllable by the researcher (Creswell, 2015). One limitation of this study was the generalizability of the findings due to the method of sampling and sample size. Participants were limited to those willing to participate who could speak English and were able to be contacted via email. This sample may not have been indicative of the population of educators as a whole. Delimitations are characteristics of a study that can influence the results and are in the control of the researcher (Creswell, 2015). A delimitation of this study was that the
Meredith 11 only social media platform that was examined was Twitter, while all others were excluded. A limitation and delimitation was that the researcher did not know what specific types of educational technology teachers were using in the classroom as the only measurement that was taken in regards to technology usage was the amount of time spent utilizing it in the classroom. These delimitations were purposeful, however, as the researcher was only seeking to identify if Twitter usage has any relationship to the amount of educational technology implementation with the K-12 classroom. The requirement that participants must teach in a K-12 classroom within the United States was also a delimitation. Definitions of Terms The relevant terms used in this research study are defined as follows: •
Educational Technology (also known as “EdTech”) - Specific type of technology that is geared towards the creation and implementation of tools designed to promote education (Lazaro, 2015).
•
Professional Learning Community (PLC) - a name applied to a type of collaboration between educators who share a common goal towards learning, communicating, and teaching (Battersby & Verdi, 2014).
•
Professional Learning Network (PLN) - a learning network that is structured specifically to provide input to a particular individual (Sie et al., 2013).
•
Technology Acceptance Model (TAM) – A model positing that perceived usefulness and perceived ease of use are key determinants to whether or not a particular technology or system is used (Ramayah & Jantan, 2007).
Meredith 12 •
Twitter - A social networking platform in which users publish posts that are 140 characters or less and can be searched using the # symbol (Mills, 2014).
Summary and Organization of the Study This dissertation is organized into five chapters, a references section, and appendices. Chapter I introduced the study including background information, the theoretical framework, and problem statement. Assumptions, limitations, and delimitations were also discussed. Chapter II includes a review of the literature relevant to this study. Chapter III explains the research design and methodology. Chapter IV presents the findings, and Chapter V summarizes the study while providing a conclusion, implications, and recommendations for further studies.
Meredith 13 Chapter II Review of the Literature The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. Recent changes in educational technology have opened the gateway for student success in the 21st century, transforming traditional methods of teaching and learning (Thota & Negreiros, 2015). Studies show improved student performance and academic achievement when integrating educational technology into the K-12 curriculum (Pierce & Cleary, 2014). In addition, the movement toward integrating technology with a collaborative approach has shown to result in improved student success aligned with the educational goals of the state, school, and region (Battersby & Verdi, 2014). However, although government spending has helped to put devices and infrastructure into schools, implementation within the classroom has been slow (Shirley et al., 2011). Many studies have been conducted in an effort to identify causes for the slowed progression of educational technology and to suggest possible solutions. (Kale & Goh, 2014; Laferrière et al., 2013; Pierce & Cleary, 2014). Among the many reasons for poor implementation are inadequate infrastructure and student devices, minimal availability of educationally appropriate applications, and lack of educator training on how to effectively use educational technology in the classroom (Pierce & Cleary, 2014). The Technology Acceptance Model (TAM) seeks to identify possible barriers to technology implementation. TAM is a highly-tested theory that pinpoints two key factors related to technology usage: perceived usefulness and perceived ease of use (Ramayah et
Meredith 14 al., 2002). The theory, first proposed by Davis (1989), has been validated in numerous studies, showing these two conditions to be a strong determinant for degree of technology implementation. Davis explained if a user feels that the particular technology will aid him or her at his or her job, the user is more likely to implement the tool. In addition, if the user perceives the technology as easy to use, he or she is more likely to utilize it (Davis, 1989). Other factors, such as attitude towards use and intent to use, affect implementation as well (Ramayah et al., 2002). The implication within the classroom setting, therefore, is teachers must see the usefulness of educational technology and they must feel capable of using the technology to increase the amount of it used within the classroom (Hew & Brush, 2007). In seeking to identify solutions to poor technology implementation, research documents the effectiveness of collaboration in supporting both teacher and school improvement (Poulos, Culberston, Piazza, & D’Entremont, 2014). Further, collaboration used as a tool for professional development could create both professional and personal benefits for teachers (Forte & Flores, 2014). Previous research has demonstrated problems associated with traditional methods of face-to-face collaboration such as geographic isolation (Johnson, 2015), but social media has provided a new venue for facilitating PLCs often referred to as professional learning networks (PLNs) (Mills, 2014). Many educators have turned to social media sites like Facebook and Twitter to participate in a variety of professional development activities and meetings (Carpenter, 2015). The question remains, though, if those who use social media for such purposes actually possess better technology skills and implementation within K-12 classrooms.
Meredith 15 In researching the topic of PLCs, there was an abundance of information regarding teacher collaboration, particularly about its uses and potential barriers (Battersby & Verdi, 2014). Many types of programs to enhance collaboration were documented throughout the research studied for this review, all describing different methods of promoting collaboration for the betterment of teachers (Johnson, 2015). Many articles described the use of social media for the creation of PLNs and the results of these collaborations (Blitz, 2013; Mills, 2014). There was also adequate information on various methods of implementing educational technology, but because of the constant flux of newly evolving platforms, the research is very widespread (Laferrière, et al., 2013). The following sections of this paper focus on studies done utilizing the Technology Acceptance Model (TAM), and how it could potentially explain the lack of proper educational technology implementation in the K-12 classroom. Challenges to collaboration and how social media addresses these issues will be discussed, as well as how Twitter has been used in education to support learning for both students and teachers. The question of whether Twitter users hold a better perception of educational technology implementation was also analyzed. This literature review investigates the challenges associated with implementing educational technology, and how using collaborations can positively impact skill development and teacher performance. It specifically looks at the role of collaborations, both traditional and online, in the implementation of educational technology in the K-12 classroom. It also explores how social media, including the use of Twitter, could possibly have an impact in regard to the framework of the TAM theory, providing collaborations
Meredith 16 that improve teacher perception, attitude, and use of educational technology within their classroom. Technology Usage in the K-12 Classroom With the influx of technology into the K-12 classrooms, teachers face a new challenge in leveraging mobile devices, the Internet, and social media with effective instruction for students who possess new digital skills (Thota & Negreiros, 2015). Research shows that incorporating opportunities for students to create and curate digital information as well as engage in virtual exchanges and collaborations can increase student motivation for learning (Kale & Goh, 2014). However, continued research shows new technology can be a source of stress for educators if they are left by themselves to create lessons and properly implement new tools within their curriculum (Laferrière et al., 2013). To this end, emphasis on collaboration has been driven to the forefront of educational reform, and there have been multiple initiatives by state education departments as they mandate PLCs in an effort to provide support for teachers (Battersby & Verdi, 2014). Success has been documented, as PLCs have been shown to lessen feelings of isolation for teachers not accustomed to collaborating with others on a regular basis and also to create opportunities for educators in which to gain new perspectives and skill set thereby equipping them to better serve their students (Battersby & Verdi, 2014). Likewise, collaboration has demonstrated improvements in teacher practices when it occurs through connections between public schools and students enrolled in teacher preparations programs at the college level (Duffield, Olson, & Kerzman, 2013). Research shows those teachers consistently participating in collaborative learning opportunities
Meredith 17 have the opportunity to develop the knowledge, skills, and beliefs necessary for successful technology integration (Laferrière et al., 2013). Challenges with educational technology implementation. Multiple roadblocks exist in the effective implementation of educational technology in the K-12 classroom. Although in recent years, governments have worked to supply schools with devices and internet capability, progress on the implementation of educational technology has been minimal, citing the required changes within teaching practices as one possible reason (Shirley et al., 2011). Additionally, research has identified multiple barriers to educational technology implementation including a lack of teacher exposure to technology (Hsu, 2016), lack of professional development for educators (Hew & Brush, 2007) and negative beliefs about the effectiveness of technology in the classroom (Kale & Goh, 2014). Disagreements between those administering and regulating the use of technology and those implementing it within the classroom can also stand in the way of effective integration (Laferrière et al., 2013). Kale and Goh (2014) identified specific factors that stand in the way of successful educational technology integration. These include: ● lack of access to technology resources, ● lack of time to learn new technology skills, ● minimal professional development available for learning, and ● weak support provided by schools and districts. A final factor discussed by Kale and Goh (2014) was teachers’ feelings and beliefs about the effectiveness of technology in the classroom. This factor, in relation to the TAM model, is discussed in the next section.
Meredith 18 Teachers’ beliefs and TAM. One of the most significant indicators in regard to a teacher’s use of technology is their attitude regarding the effectiveness for student instruction and learning (Kale & Gohl, 2014). Research has shown that teachers hesitate to invest time in learning new tools when previous patterns indicate that typically the newest technology items will soon become obsolete (Mishra, Koehler, & Kereluik, 2009). Also, an important determinant is the belief in one’s ability to teach with technology and feelings regarding the value involved in integrating it with student learning are also important determinants (Hsu, 2016). Research on the technology acceptance model indicates despite the major investments made by entities to provide technology, a large portion of it remains unused simply because of lack of user acceptance (Shroff et al., 2011). Davis (1989) explained the importance of teacher belief in implementing educational technology when he stated “people tend to use or not use an application to the extent they believe it will help them perform their job better” (p. 320). He further asserted if the technology is not easy to use, this will act as a hindrance that outweighs any benefits associated with using the application. The implication in the K-12 classroom is that teachers must see relevance in educational technology devices and applications in helping students to learn, and they must feel equipped to properly utilize the tools with students (Hew & Brush, 2007). PLCs, whose ultimate goal is to improve student learning through teachers’ exchange of ideas and information (Blitz, 2013), could serve as an aid for helping educators view technology as useful and themselves as capable of proper implementation. Dufour and Eaker (1998) defined key aspects of collaborative groups classified as PLCs. First, the group must have a commonly shared intent, meaning all participants are
Meredith 19 working toward the same end. Second, the group must consistently analyze current data trends and their implications toward student success, and they must also show a willingness to act. However, facilitating this type of learning environment for teachers has its own set of challenges (Johnson, 2015; Tseng, Wang, Ku, & Sun, 2009. Challenges with Collaboration Despite the importance of collaborative efforts of PLCs, many challenges exist with implementing effective programs to provide appropriate opportunities. These include issues with both environmental conditions (Johnson, 2015; Tseng et al., 2009) and the method of collaboration, online or traditional (Blitz, 2013). Technology has been shown to be an effective was to facilitate communication that might otherwise be difficult (Carpenter & Krutka, 2014). Environmental considerations. Factors regarding the collaborative environment can influence the effectiveness in many ways (Trust et al., 2016). For educators teaching in secluded regions, geographic isolation can interfere with their ability to learn from and collaborate with other experts in their field (Johnson, 2015). Some environments are not conducive to collaboration because administration and faculty lack clear and concise communication (Tseng et al., 2009). Additionally, a lack of trust between those involved in collaborative discussions can also become a barrier to the benefits achieved through collaboration (Bantwini, 2015). Because of these issues, it can be difficult to facilitate the five factors identified by Tseng et al. (2009) that are necessary for an effective collaborative environment: administrative support, the degree to which participants are familiar with one another, organization of the collaboration, use of open communication, and feelings of confidence amongst those participating. In response to these challenges
Meredith 20 associated with traditional collaborations, many educators are moving towards online PLNs via social media sites in order to engage with their peers and like-minded educators (Trust et al., 2016). Online vs. traditional methods. Social networking sites have changed the way in which people interact and exchange information with each other (Cardon & Marshall, 2014), and the effectiveness of virtual PLNs has been the focus of recent research. The flexibility afforded by online platforms has prompted continued studies on the difference between online and traditional methods of collaboration (Blitz, 2013), but the results have been somewhat mixed. Online learning has been shown to develop more questioning behaviors in participants versus those in traditional models, a trait which is necessary for learning collaboratively (Tutty & Klein, 2008). However, the extent to which participants are motivated to interact with others is greater in a traditional face-to-face collaboration, likely due to online collaborations being less formal (Blitz, 2013). Continued research must be conducted on the use of online methods, including how to address collaborations when they incorporate participants with diversified backgrounds, specialties, and geographic locations (Pugach, Blanton, & Correa, 2011). The Role of Social Media in Collaboration New communication technologies can offer opportunities to take professional learning and collaboration outside the walls of the schools and regions, affording teachers the opportunity to easily exchange knowledge and skills in the constantly evolving global society (Tseng et al., 2009). Previous studies on using social media for teacher collaboration have shown it to be an effective modality (Blitz, 2013; Mills, 2014; Trust et al., 2016). The social networking site Facebook has been documented for its use in
Meredith 21 providing asynchronous collaborations across multiple nations for those teaching in an isolated field, such as art or music (Palmquist & Barnes, 2015). In many cases, there is only one of these specialty teachers per building, so giving them the opportunity to connect with others outside their geographical region is important and communication technologies are a must (Battersby & Verdi, 2014). Balcikanli (2015) also suggested social media can offer more interesting learning experiences as opposed to face-to-face meetings. Using Twitter as a tool for collaboration. Studies have also been done on the usage of Twitter within an educational setting (Lin, Hoffman, & Borengasser, 2013). When used as a professional development tool, research shows Twitter to be beneficial for learning about classroom resources, strategies and technologies (Mills, 2014). The social media site has also been studied as a venue for communication with other educators outside of one’s school (Carpenter, 2015). An effective means to use Twitter is through the participation in a Twitter chat. This process involves using a Twitter account to post various questions and responses denoted with a shared phrase, called a hashtag, to which others can follow and respond (Carpenter, 2015). Two examples of these hashtags are #ADEchat and #EdTechchat, both being Twitter chats associated with the use of technology in the classroom. A typical Twitter chat involves the posing of a question and participants responding back using the assigned hash-tagged phrase (see Figure 1). This allows anyone who has the hashtag to search and respond, creating online conversations regarding specific topics (Sie et al., 2013). Twitter helps connect teachers worldwide, which means educators can get a
Meredith 22 glimpse into the bigger picture of education and how they can work with others to make an impact (Kattak, Batool, Salem, & Takreem, 2016).
Figure 1. Twitter basics when using the #AppleEDUchat hashtag. Graphics and Tweets used with permission from account owners.
If teachers have confidence in their ability to perform, research suggests they will likely be more accepting of new ideas and methods, and will apply more effort towards achieving success (Thoonen, Sleegers, Oort, Peetsma, & Geijsel, 2011). The study conducted by Thoonen et al. (2001) indicated teachers may be reluctant to implement new technology if views about their own ability to learn and successfully integrate technology within their classroom are negative. However, studies have shown improved knowledge, attitudes, and skills when using social media, as well as its usefulness in
Meredith 23 creating PLNs to helps educators to try new innovations within their instruction (Schirr, 2013). Social media also has the capabilities of providing a supportive environment for exchanging experiences, something that can positively affect psychological learning but that is sometimes difficult to find within schools (Forte & Flores, 2014). Furthermore, social media could also be an effective means for forming mentorships that would help experienced educational technology users to influence beginning users in understanding the importance of implementation (Murthy, Hastings, & Marie, 2015). Another belief that might deter teachers from implementing educational technology could be how they view the value of it within the educational setting. Teachers who do not see the value in integrating a specific tool will not take the time to learn the tool (Mishra et al., 2009). Teachers must see the cost of learning new skills as being outweighed by the benefits achieved through using educational technology (Shirley et al., 2011). By engaging in a virtual PLN, teachers can be exposed to new methods, ideas, and beliefs about educational technology, facilitating opportunities to learn from one another (Sie et al., 2013). Teachers may have a belief that educational technology is useful and want to implement it within their classroom, but without possessing the proper skills they will not be successful (Laferrière et al., 2013). Social media gives educators a safe place in which to experiment with new behaviors and receive feedback, allowing them to gain confidence in their use of educational technology (Yost & Fan, 2014). However, participants must express collaborative behaviors, such as the degree to which they show interest in discussions with others, in order to greatly impact the gains experienced
Meredith 24 through teacher collaboration whether they engage in traditional methods or online collaborative discussions (Putman, Ford, & Tancock, 2012). Certain barriers must be overcome for educators to use social media for collaboration on a regular basis. One such barrier is a lack of teacher know-how in using the specified online platform (AWWA…, 2011). If the site is not user-friendly and users are unaware of key features, teachers will be less likely to engage in collaboration or to exhibit positive behaviors towards learning from it (Yost & Fan, 2014). Additionally, the practice of institutions blocking social media sites and the time required to create and maintain a social media account have been identified as deterrents from engaging in online collaboration (AWWA…, 2011). Finally, users may prefer using a particular social media site over another, causing them to miss learning opportunities presented through other collaborative online ventures (Yost & Fan, 2014). If these challenges are overcome, though, social media sites like Twitter could provide more convenient opportunities for effective collaboration regarding educational technology. Twitter and the Technology Acceptance Model Twitter has been found to be an effective tool for facilitating communication within education. Among its documented successful uses includes serving as a back channel for dialogue between students and providing a platform for teacher to student announcements (Carpenter, 2015) and as a professional development tool for pre-service teachers (Mills, 2014). Research into its effectiveness as a professional development tool is still limited (Carpenter, 2015), however, and it is uncertain if the social media site has any major impact on teachers’ beliefs and attitudes regarding educational technology. In
Meredith 25 examining this relationship, the TAM model, a widely-accepted theory for studying the factors affecting technology adoption and usage, can provide a framework for study. The TAM model’s validity has been widely tested and proven through many studies over nearly 30 years (Donaldson, 2011; Fan, 2014; Hidayanto & Setyady, 2014; Ramayah et al., 2002; Shroff et al., 2011; Yuan, et al, 2017). The theory states a person’s usage of a technology is affected by the perceived usefulness and perceived ease of use of the tool (Ramayah et al., 2002). Davis (1989) defined perceived usefulness as “the degree to which an individual believes that using a particular system would enhance his or her productivity” (p. 320) and perceived ease of use as “the degree an individual believes that using a particular system would be free of effort” (p. 320). In addition, a user’s beliefs and attitudes about the usefulness of the technology can have an impact on usage as well. However, its impact is not to the degree of perceived usefulness (Ramayah et al., 2002). Since the emergence of TAM, other research has been conducted to include specific determinants of perceived ease of use and perceived usefulness (see Table 1) based on individual differences, system characteristics, social influence, and facilitating conditions (Venkatesh & Bala, 2008). Further investigations must be done on which types of interventions can affect these determinants (Venkatesh & Bala, 2008). Twitter could be one such possible intervention that has an effect on how a user perceives the ease of use and usefulness of educational technology.
Meredith 26 Table 1 Determinants of TAM Constructs (Venkatesh & Bala, 2008) Perceived Usefulness
Perceived Ease of Use
Perceived ease of use
Computer Self-Efficacy
Subjective Norm
Perceptions of External Control
Image
Computer Anxiety
Job Relevance
Computer Playfulness
Output Quality
Perceived Enjoyment
Result Demonstrability
Objective Usability
The TAM model could explain the gap between the extent of educational technologies that exist and the degree to which they are properly used in the K-12 classroom. Two key factors, perceived ease of use and perceived usefulness, are determinants as well as user belief and attitude. The research discussed in this literature review illustrates how collaboration can be an effective means of professional development for learning new skills. However, despite the documented effectiveness of skill development through collaborations, many challenges keep educators from forming effective PLCs that can have a real impact on their profession (Johnson, 2015). Social media provides a solution for creating PLNs amongst educators that might otherwise be forced to deal with problems associated with traditional methods of collaboration (Munoz, Pellegrini-Lafont, & Cramer, 2014).
Meredith 27 Implications As described by the TAM model, key determinants in the use of educational technology are the perceived usefulness of the system, how easy it appears to use the system, and the attitude or beliefs the teacher has about the technology (Davis, 1989). In operating under the assumption that beliefs determine one’s attitude, teachers must believe in the reliability of educational technology to produce beneficial results for student achievement (Hew & Brush, 2007). Additionally, in order for teachers to effectively bridge their understanding of technology and pedagogical content with that of student achievement, they must have a positive attitude in regard to implementing the technology (Kale & Goh, 2014). Engaging in collaborations regarding the topic of educational technology might help educators view technology as both useful and easy to implement. The need for convenient collaboration. Studies conducted on collaboration show its effectiveness, but there is a growing need to make collaboration and professional learning more convenient so that more educators will take advantage of the rewards it offers (Jang, 2014). Social media, such as Twitter, provides the means to facilitate PLNs that can impact teacher professional development and the learning of new skills for the diversified field of educators across the world (Mills, 2014). It is unclear, however, if those who participate in collaborations via Twitter exhibit a higher degree of implementation of educational technology within their classrooms. Interventions to influence perceived ease of use and usefulness. Since the inception of the Technology Acceptance Model, numerous studies have been conducted demonstrating its validity (Adetimirin, 2015; Venkatesh & Bala, 2008; Venkatesh &
Meredith 28 Davis, 2000). They have expanded upon the components that impact perceived ease of use and usefulness to include factors such as subject norm, voluntariness, job relevance, and output quality (Venkatesh & Bala, 2008). Few studies exist, however, on the successfulness of interventions designed to improve user acceptance of technology. One study addressing interventions by Venkatesh and Bala (2008) tested an intervention framework for pre- and post-implementation of informational technology. Their study concluded with suggestions for further research on the effectiveness of intervention strategies for influencing employees and increasing technology use. Literature Review Summary Although social media has been shown to positively impact educator collaboration (Mills, 2014), it has not been researched for its ability to invoke change within teachers’ technology usage. Many studies have been conducted on the validity of the TAM model, but few have identified interventions necessary to change a participant's responses (Adetimirin, 2015; Venkatesh & Bala, 2008; Venkatesh & Davis, 2000). Additionally, research has been conducted on the barriers of educational technology implementation (Hew & Brush, 2007; Laferrière et al., 2013), but none have investigated the effects of social media collaborations. Summary Chapter II reviewed the literature regarding collaboration and the Technology Acceptance Model. In Chapter III the methodology is presented for the quantitative study. Chapter IV presents the findings while Chapter V contains a summary of the study, conclusions, implications for practice, and recommendations for further study.
Meredith 29 Chapter III Methodology The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. Specifically, this study looked at the results of the TAM questionnaire regarding the perceived ease of use, perceived usefulness, and intent to use educational technology by both educators who use Twitter and those who do not. The researcher sought to identify if a relationship existed regarding Twitter usage for educational purposes and educational technology usage by K12 teachers. The purpose, research design and methodology, and treatment of the data are described in this chapter. Purpose of the Study and Research Questions The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. The following questions were addressed in this study: 1. RQ1: Is there a difference in perceived usefulness of educational technology between users and non-users of Twitter? a. RQ1 Hypothesis:
§
H0: There is no difference in perceived usefulness of educational technology between users and non-users of Twitter
§
H1: There is a difference in perceived usefulness of
Meredith 30 educational technology between users and non-users of Twitter. 2. RQ2: Is there a difference in perceived ease of use of educational technology between users and non-users of Twitter? a. RQ2 Hypothesis:
§
H0: There is no difference in perceived ease of use of educational technology between users and non-users of Twitter
§
H1: There is a difference in perceived ease of use of educational technology between users and non-users of Twitter.
3. RQ3: Is there a difference in teachers’ intent to use educational technology between users and non-users of Twitter? a. RQ3 Hypothesis:
§
H0: There is no difference in teachers’ intent to use educational technology between users and non-users of Twitter.
§
H1: There is a difference in teachers’ intent to use educational technology between users and non-users of Twitter.
4. RQ4: Does a relationship exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators? a. RQ4 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators.
Meredith 31 §
H1: A relationship does exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators.
5. RQ5: Does a relationship exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators? a. RQ5 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators.
6. RQ6: Does a relationship exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators? a. RQ6 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
Meredith 32 Research Design This study was designed to test for differences between users and non-users of Twitter regarding the three TAM model determinants of perceived usefulness, perceived ease of use, and behavioral intent. The study also explored the relationship between the amount of time spent using Twitter for educational purposes and perceptions regarding educational technology. Independent t-tests and Pearson product-moment correlation coefficient tests were utilized to test for the difference between groups and the relationship between Twitter and the TAM determinants. The use of explanatory correlational research design is beneficial because it explains the relationship between two variables. According to Creswell (2015), explanatory correlational design is used when the researcher wants to identify how changes in one variable can be seen through changes in another variable. For this study, correlation tests allowed the researcher to analyze the relationship between the use of Twitter as a professional development tool and the perceived ease of use, perceived usefulness, and intent to use educational technology. Conducting independent sample ttests provided the researcher with information regarding differences in groups: Twitter users and non-users. An electronic TAM questionnaire, developed by Venkatesh and Bala (2008), was used to gather the information required for the study. The questionnaire (Appendix E) elicited information on demographics including age, gender, highest level of education, and information regarding the content and age level the participants teach. These questions were designed by the researcher. The questionnaire also included questions regarding participant’s degree of Twitter use, perceived usefulness of educational
Meredith 33 technology, perceived ease of use of educational technology and intention to use educational technology in the K-12 classroom. The independent variable was Twitter Usage, and the dependent variable was perceived ease of use, perceived usefulness, and behavioral intention. In order to complete the t-tests, participants were split into two groups: those with little to no use (less than one hour per week) and those with moderate to high use (more than one hour per week). The Participants and the Setting The participants were a non-random representative population of K-12 teachers from a variety of disciplines and grade levels within the United States and have varying years of teaching experience. These teachers are a mix of users and non-users of Twitter, and were included in this study because of their willingness to participate. Snowball sampling was used in identifying the participants, and sample size was determined by power analysis (Creswell, 2015). The setting varied, as each participant accessed the electronic questionnaire in their individual work or home location. Teachers were from a variety of schools and districts across the United States. Diversity of the sampling population was intentional as the researcher sought to identify if commonality of Twitter usage impacts educational technology implementation across a variety of demographics. The study used snowball sampling to obtain 130 participants to take the online survey in Qualtrics. Of those 130, only 124 completed the survey and are included in the results of this study. Descriptive statistics were used to summarize the demographic data collected in these surveys. The age of the participants, displayed in Table 2, varied with 5% being 18 to 24 years old, 27% being 25-34 years old, 33% being 35 to 44 years old, 24% being 45 to 54 years old, and 11% being 55 to 64 years old. Years of experience also
Meredith 34 varied with 18% having 0-5 years, 17% having 6-10 years, 22% having 11-15 years, 16% having 16-20 years, 16% having 21-25 years, 8% having 26-30 years, and 4% having 30 or more years in education (Table 2).
Table 2 Demographic Information of Participants
Age
Years of Experience
18-24
5%
25-34
27%
35-44
33%
45-54
24%
55-64
11%
0-5
18%
6-10
17%
11-15
22%
16-20
16%
21-25
16%
26-30
8%
30+
4%
The participants were from a variety of disciplines and grade level classrooms. Kindergarten teachers made up 7% of the study, grade 1-2 teachers were 18%, grade 3-5 teachers were 24%, grade 6-8 were 35%, and grades 9-12 teachers were 16%. There was
Meredith 35 some overlap between teachers who taught more than one of these grade bands (Table 3). 21% of the teachers taught science, 17% taught social studies, 24% taught English Language Arts, 20% taught mathematics, 3% taught visual arts, 2% performing arts/ music, 1% physical education, 2% health and consumer science, 1% agriculture, 1% foreign language, and 8% indicated they teach other subjects. These other subjects included technology, computer science, and coding as shown in Table 3.
Table 3 Grade Levels and Disciplines Taught by Participants
Grade Levels
Disciplines
Kindergarten
7%
Grade 1-2
18%
Grades 3-5
24%
Grades 6-8
35%
Grades 9-12
16%
Science
21%
Social Studies
17%
English Language Arts
24%
Mathematics
20%
Visual Arts
3%
Performing Art/Music
2%
Physical Education
1%
Health and Consumer Science
2%
Agriculture
1%
Foreign Language
1%
Other
8%
Meredith 36 Instrumentation The instrument (Appendix E) consisted of validated items from prior research conducted by Davis (1989), Venkatesh and Bala (2008), and Venkatesh and Davis (2000). Venkatesh and Bala (2008) developed the TAM3 model and established reliability in the survey instrument which included items on perceived ease of use, perceived usefulness, and behavioral intention. Determinants of perceived ease of use measured included computer self-efficacy, perceptions of external control, computer playfulness, computer anxiety, and perceived enjoyment. Determinants of perceived usefulness measured included subjective norm, voluntariness, image, job relevance, output quality, and result demonstrability, For the independent t-tests, participants were asked to rate their degree of Twitter usage for educational purposes between two options, 1= little to no use (less than one hour per week) and 2= moderate to high use (more than one hour per week). For the Pearson r correlation coefficient tests, participants were asked specifically how much time they spend each week using Twitter for educational purposes on a scale of 1-5 with 1= 0-1 hour per week, 2= 1-2 hours per week, 3= 2-3 hours per week, 4= 3-4 hours per week, and 5= more than 5 hours per week. They rated their opinion using a 5-point Likert scale ranging from 1= Strongly disagree, 2= Disagree, 3= Neither disagree nor disagree, 4= Agree and 5= Strongly agree, for determinants of perceived usefulness, perceived ease of use, behavioral intent, and all determinants. Lastly, participants were asked to indicate how much time they spend using educational technology in their classroom each day. Reliability and validity of the instrument was ensured by basing the survey questions on TAM 3 construct items previously tested by Venkatesh and Davis (2000)
Meredith 37 and Venkatesh and Bala (2008), who assessed the instrument over a five-month period. At each time period, all constructs had strong psychometric properties satisfying the criteria of reliability and validity. Venkatesh and Davis (2000), calculated the reliability of all constructs as having Cronbach’s alpha coefficients exceeding 0.80. The validity of the instrument was supported by principal components analysis using oblique rotation. Data Collection This research proposal was approved by the Lamar University IRB (Appendix A) prior to beginning data collection. Data collection for this study involved collecting participants’ responses to an electronic questionnaire containing items on degree of Twitter usage, perceived usefulness of educational technology, perceived ease of use of educational technology, and intention to use educational technology. The Qualtrics online survey tool was used to create and distribute the questions to all possible participants who were provided the link by email. The email contained information about the purpose of the study, options to withdraw from the study, and any known risks associated with the study. Embedded within the survey (Appendix E), was a consent form of which participants were required to accept before continuing on to the questionnaire. Participants who agreed to be a part of the study gave their consent by completing the survey. Treatment of the Data Analysis of the data required the researcher to eliminate preconceived notions in order to fully understand how the teachers’ experiences have shaped their values and behaviors. Data was recorded on teachers’ responses to the questionnaire utilizing the Technology Acceptance Model of determinants for educational technology. After the
Meredith 38 data were organized and assembled, analysis was accomplished by entry on the computer within the software SPSS. Independent t-tests were used to determine if a significant difference existed between the means of Non-Users of Twitter and means of Users of Twitter on the three variables of Usefulness, Ease of Use, and Intent to Use. Further analysis was conducted using Pearson Product Moment Correlation Coefficient to determine if a significant relationship existed between Online Collaboration with Twitter and the three variables of Usefulness, Ease of Use, and Intent to Use. A p value of .05 was established for all statistical tests. Summary This chapter presented the purpose and methodology of the study. The TAM was presented and explained in relation to the determinants of perceived ease of use, perceived usefulness, and behavioral intention to the integration of education technology in the K-12 classroom. The research design was also explained in regards to the participants, setting, and how the data was collected and treated. Chapter IV will discuss data results and Chapter V will summarize the study with conclusions, implications for practice, and recommendations for further study.
Meredith 39 Chapter IV Analysis of Data The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. This chapter explains the results of this study. Descriptive statistics are reported for all variables, as well as findings in regards to the demographics and differences between groups. Research Questions and Hypotheses The following research questions and hypotheses guided this study. 1. RQ1: Is there a difference in perceived usefulness of educational technology between users and non-users of Twitter? o RQ1 Hypothesis:
§
H0: There is no difference in perceived usefulness of educational technology between users and non-users of Twitter
§
H1: There is a difference in perceived usefulness of educational technology between users and non-users of Twitter.
2. RQ2: Is there a difference in perceived ease of use of educational technology between users and non-users of Twitter? o RQ2 Hypothesis:
§
H0: There is no difference in perceived ease of use of educational technology between users and non-users of Twitter
§
H1: There is a difference in perceived ease of use of
Meredith 40 educational technology between users and non-users of Twitter. 3. RQ3: Is there a difference in teachers’ intent to use educational technology between users and non-users of Twitter? o RQ3 Hypothesis:
§
H0: There is no difference in teachers’ intent to use educational technology between users and non-users of Twitter.
§
H1: There is a difference in teachers’ intent to use educational technology between users and non-users of Twitter.
4. RQ4: Does a relationship exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators? o RQ4 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators.
5. RQ5: Does a relationship exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators? o RQ5 Hypothesis: §
H0: A relationship does not exist between online collaboration using Twitter and perceived ease of use of educational
Meredith 41 technology by K-12 educators. §
H1: A relationship does exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators.
6. RQ6: Does a relationship exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators? o RQ6 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
Teachers’ Use of Twitter Of the 124 participants who completed the survey responses, 44 indicated they were frequent users of Twitter for educational purposes. This included using the site more than one hour per week for searching Twitter for educational hashtags (i.e. #edchat, #edtech, #teacherpd), reading articles or other resources found on Twitter regarding an educational topic, viewing videos or other resources found on Twitter regarding an educational topic, participating in a Twitter chat regarding an educational topic, or communicating one-on-one with a Twitter user regarding education. Of the 44 participants that indicated they were frequent Twitter users, 19 used Twitter 1-2 hours per week, 7 used it for 2-3 hours per week, 10 used the site for 3-4 hours per week, and 8
Meredith 42 used the site for 5 or more hours per week for educational purposes. Table 4 and 5 show these percentages below.
Table 4 Twitter Usage Among Participants Type of Twitter usage
Users
Percentage
80
65%
44
35%
1= Little to no use (less than one hour per week) 2= Moderate to high use (more than one hour per week)
Table 5 Amount of Twitter Usage for Moderate to High Participants Users
Percentage
1-2 hours per week
19
43%
2-3 hours per week
7
16%
3-4 hours per week
10
23%
5 or more hours per week
8
18%
Twitter usage for moderate to high participants
For each participant, scores were calculated within each section of the survey by calculating the mean rating for the questions within the particular group. Minimum, maximum, and mean scores for both Twitter users and non-users are represented in Table
Meredith 43 6. Final scores for perceived usefulness, ease of use, and behavioral intent were calculated by averaging the values of each determinant under the category. For instance, to calculate the perceived usefulness total score, the mean value of perceived ease of use, subjective norm, image, job relevance, output quality, and results demonstrability were used. These values are listed in Table 4.
Meredith 44 Table 6 Descriptive Statistics for Users and Non-users of Twitter Twitter Users
Twitter Non-Users
(N=44)
(N=80)
Variable
Min
Max
Mean
Min
Max
Mean
Perceived Usefulness Total
3.048
4.638
4.024
2.638
4.591
3.756
- Perceived ease of use
2.875
5.00
4.003
2.250
5.00
3.78
- Subjective norm
1.50
5.00
4.091
2.50
5.00
4.013
- Image
1.00
4.33
3.144
1.33
5.00
3.155
- Job relevance
3.00
5.00
4.712
2.67
5.00
4.425
- Output quality
2.33
5.00
4.265
1.33
5.00
3.550
- Results demonstrability
3.00
5.00
3.932
2.50
5.00
3.613
Perceived Ease of Use Total
2.848
4.445
3.922
2.443
4.487
3.540
- Computer self-efficacy
2.75
5.00
4.3409
2.00
5.00
3.938
- Perceptions of external control
2.00
5.00
4.394
1.00
5.00
3.926
- Computer anxiety
3.00
5.00
4.777
2.25
5.00
4.240
- Computer playfulness
2.00
4.25
3.619
1.50
5.00
3.131
- Perceived enjoyment
2.67
5.00
4.568
2.33
5.00
3.948
- Objective usability
2.50
5.00
4.642
2.50
5.00
4.194
Behavioral Intention Total
3.00
5.00
3.930
2.625
5.00
3.816
- Behavioral Intent
3.75
5.00
4.869
2.75
5.00
4.460
- Voluntariness
1.00
5.00
2.992
1.00
5.00
3.171
Meredith 45 Findings for Research Question One Research question one was, “Is there a difference in perceived usefulness of educational technology between users and non-users of Twitter?” To test if there was a statistically significant difference in mean perceived usefulness scores between users and non-users of Twitter, a sample of teachers (n= 124) was used in an independent samples t-test. Type of Twitter user (1= little to no use, n= 80 and 2= moderate to high use, n= 44) was used as the independent variable and the mean perceived usefulness score (1-5) was used as the dependent variable. As shown in Table 5, the independent samples t-test (t(120)= -3.502, p= .001) indicated there was a statistically significant difference between users’ (M= 4.024) and non-users’ (M= 3.749) perceived usefulness mean scores. The effect size, Cohens d calculated to determine the magnitude of the difference between the two groups. The Cohens d calculation for perceived usefulness was 0.275/0.4183= .66, which indicated a moderate magnitude of difference in perceived usefulness of educational technology between users and non-users of Twitter. The data, summarized in Table 7, suggests Twitter usage does account for differences in how teachers perceive the usefulness of educational technology. Therefore, for research question one, the null hypothesis is rejected as there does exist a difference in perceived usefulness of educational technology between users and non-users of Twitter. Findings for Research Question Two Research question two was, “Is there a difference in perceived ease of use of educational technology between users and non-users of Twitter?” To test if there was a statistically significant difference in mean perceived ease of use scores between users and non-users of Twitter, a sample of teachers (n= 124) was used in an independent samples
Meredith 46 t-test. Type of Twitter user (1= little to no use, n= 80 and 2= moderate to high use, n= 44) was used as the independent variable and mean perceived ease of use score (1-5) was used as the dependent variable. As shown in Table 5, the independent samples t-test (t(120)= -4.853, p= .000) indicated there was a statistically significant difference between users’ (M= 3.922) and non-users’ (M= 3.526) perceived ease of use mean scores. The Levene's Test for Equality of Variances revealed variances in the variable for perceived ease of use were not homogeneous. For this variable, a Welch-Satterthwaite test was used to determine if mean differences existed between the two groups. The effect size, Cohens d, was calculated to determine the magnitude of the difference between the two groups. The Cohens d calculation for perceived ease of use was 0.396/0.4105 = .96, which indicated a large magnitude of difference between users and non-users of Twitter. The data, summarized in Table 7, suggests Twitter usage does account for differences in how teachers perceive educational technology as easy to use. Therefore, for research question two, the null hypothesis is rejected as there does exist a difference in perceived ease of use of educational technology between users and nonusers of Twitter. Findings for Research Question Three Research question three was, “Is there a difference in teachers’ intent to use educational technology between users and non-users of Twitter?” To test if there was a statistically significant difference in mean behavioral intent scores between users and non-users of Twitter, a sample of teachers (n= 124) was used in an independent samples t-test. Type of Twitter user (1= little to no use, n= 80 and 2= moderate to high use, n= 44) was used as the independent variable and mean behavioral intent score (1-5) was used as
Meredith 47 the dependent variable. As shown in Table 7, the independent samples t-test (t(120)= 1.266, p= .208) indicated there was not a statistically significant difference between users’ (M= 3.930) and non-users’ (M= 3.807) behavioral intent mean scores. The data, summarized in Table 7, suggests Twitter usage does not account for differences in teachers’ intent to implement educational technology in the classroom. Therefore, for research question three, there was insufficient evidence to reject the null hypothesis. The data is consistent with having no difference in teachers’ intent to use educational technology between users and non-users of Twitter.
Table 7 Independent T-tests for Three Variables Mean Scores
Mean Scores
Sig. t
df
Twitter Users
Non-users
(2-tail)
Perceived Usefulness
4.024
3.749
-3.502
120
.001
Perceived Ease of Use
3.922
3.526
-4.853
120
.000
Behavioral Intent
3.930
3.807
-1.266
120
.208
Findings for Research Question Four Research question four was, “Does a relationship exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators?” A Pearson r correlation tests was conducted to determine if a relationship existed between perceived usefulness mean scores ranging from 1-5 (n= 124, M=3.851,
Meredith 48 SD=.433) and the amount of time spent using Twitter for educational purposes (M=1.80, SD=1.243). There was a statistically significant positive correlation between perceived usefulness and time spent using the social media site, r(124) = 0.264, p< 0.003, two-tailed. The effect size, or coefficient of determination (r2=0.07), indicates 7% of the variation in mean perceived usefulness scores can be explained by the amount of time spent on Twitter for educational purposes. The data in Table 8 suggests that a relationship does exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators. Therefore, for research question four, the null hypothesis is rejected as there does exist a positive correlation between perceived usefulness and the amount of time spent on Twitter, as seen in Figure 2. Findings for Research Question Five Research question five was, “Does a relationship exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators?” A Pearson r correlation tests was conducted to determine if a relationship existed between perceived ease of use mean scores ranging from 1-5 (n= 124, M=3.676, SD=.471) and the amount of time spent using Twitter for educational purposes (M=1.80, SD=1.243). There was a statistically significant positive correlation between perceived usefulness and time spent using the social media site, r(124) = 0.363, p< 0.000, two-tailed. The effect size, or coefficient of determination (r2=0.13), indicates that 13% of the variation in mean perceived ease of use scores can be explained by the amount of time spent on Twitter for educational purposes. The data in Table 8 suggests a relationship does exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators. Therefore, for research question five, the null
Meredith 49 hypothesis is rejected as there does exist a positive correlation between perceived ease of use and the amount of time spent on Twitter, as seen in Figure 2. Findings for Research Question Six Research question six was, “Does a relationship exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators?” A Pearson r correlation tests was conducted to determine if a relationship existed between behavioral intent mean scores ranging from 1-5 (n= 124, M=3.856, SD=.523) and the amount of time spent using Twitter for educational purposes (M=1.80, SD=1.243). There was not a statistically significant correlation between perceived usefulness and time spent using Twitter, r(124) = 0.115, p< 0.205, two-tailed. The data in Table 8 suggests that a relationship does not exist between online collaboration using Twitter and behavioral intent to use educational technology by K-12 educators. Therefore, for research question six, there was insufficient evidence to reject the null hypothesis. The data is consistent with having no relationship between online collaboration using Twitter and intent to use educational technology by K-12 educators.
Meredith 50 Table 8 Pearson Product-Moment Correlation Tests for Three Variables Twitter
Perceived
Perceived
Behavioral
Usage
Usefulness
Ease of Use
Intent
Twitter
Pearson Correlation
Usage
Sig. (2-tailed)
Perceived
Pearson Correlation
.264
Usefulness
Sig. (2-tailed)
.003
Perceived
Pearson Correlation
.363
1
1 .735 1 Ease of Use
Sig. (2-tailed)
.000
.000
Behavioral
Pearson Correlation
.115
.121
.255 1
Intent
Sig. (2-tailed)
.205
.180
.004
Meredith 51
Figure 2: Multiple line means of three tested variables.
Summary This chapter presented descriptive statistics on the three variables of perceived ease of use, perceived usefulness, and behavioral intent between the two groups of Twitter users and non-users. It also included analysis of the three independent-tests that were conducted as well as the three Pearson correlation coefficient tests. The final chapter, Chapter V, will summarize the study in regards to conclusions, implications for practice, and recommendations for further study.
Meredith 52 Chapter V Summary, Conclusions, Implications, and Recommendations The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. Specifically, this study looked at the results of the Technology Acceptance Model questionnaire regarding the perceived ease of use, perceived usefulness, and behavioral intent to use educational technology by both educators who use Twitter and those who do not. This study explored the idea that Twitter could be used as a professional development tool to support improved and increased used of educational technology in the classroom. This chapter summarizes the study and discusses conclusions of the findings, implications for educators and recommendations for further research. It closes with concluding remarks from the researcher. Summary of the Study This study sought to identify if there was a difference in teacher’s beliefs regarding the perceived usefulness, perceived ease of use, and behavioral intent in regards to educational technology between those who use Twitter and those who do not. A summary of the data and results in addition to their effect on the research hypotheses is explained in the following sections. This includes an overview of the problem, purpose statement and research questions, as well as the study design and a summary of major findings. Brief overview of the problem. Although increased spending has worked to add educational technologies into K-12 schools, teacher implementation within the classroom
Meredith 53 has been a challenge (Laferrière et al., 2013). Multiple factors play a role in the slow progression of educational technology, including lack of professional development and time to learn and implement new tools (Hsu, 2016). Professional Learning Communities (PLCs) have been shown to successfully impact teacher performance and skill development (Battersby & Verdi, 2015), but can be difficult to facilitate (Johnson, 2015). Social media sites, such as Twitter, offer a more convenient way for teachers to collaborate and form Professional Learning Networks (PLNs). This study sought to examine if those educators who use Twitter for such collaborative purposes exhibit a higher degree of educational technology implementation within their classroom. Purpose statement and research questions. The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. For this study, there were six research questions that were addressed. The following research questions and hypotheses guided this study. 1. RQ1: Is there a difference in perceived usefulness of educational technology between users and non-users of Twitter? o RQ1 Hypothesis:
§
H0: There is no difference in perceived usefulness of educational technology between users and non-users of Twitter
§
H1: There is a difference in perceived usefulness of educational technology between users and non-users of Twitter.
Meredith 54 2. RQ2: Is there a difference in perceived ease of use of educational technology between users and non-users of Twitter? o RQ2 Hypothesis:
§
H0: There is no difference in perceived ease of use of educational technology between users and non-users of Twitter
§
H1: There is a difference in perceived ease of use of educational technology between users and non-users of Twitter.
3. RQ3: Is there a difference in teachers’ intent to use educational technology between users and non-users of Twitter? o RQ3 Hypothesis:
§
H0: There is no difference in teachers’ intent to use educational technology between users and non-users of Twitter.
§
H1: There is a difference in teachers’ intent to use educational technology between users and non-users of Twitter.
4. RQ4: Does a relationship exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators? o RQ4 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and perceived usefulness of educational
Meredith 55 technology by K-12 educators. 5. RQ5: Does a relationship exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators? o RQ5 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators.
6. RQ6: Does a relationship exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators? o RQ6 Hypothesis:
§
H0: A relationship does not exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
§
H1: A relationship does exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators.
Review of the study design. The sample for this study was 124 teachers within the United States who taught in a K-12 classroom and completed an online TAM questionnaire within the Qualtrics platform. Demographic information was gathered to identify participant’s type of experience in the classroom including number of years,
Meredith 56 grade level, and content area. Data regarding the TAM questions were analyzed with SPSS using descriptive and inferential statistics. Independent sample t-tests were conducted to determine if there was a difference in perceived usefulness, perceived ease of use, and behavioral intent between users and non-users of Twitter. Pearson productmoment correlations were conducted to determine if a relationship existed between perceived usefulness, perceived ease of use, and behavioral intent mean scores and the amount of time spent using Twitter for educational purposes. Summary of major findings. This study explored the relationship between use of Twitter for educational purposes and perceived usefulness, perceived ease of use, and behavioral intent toward educational technology. Descriptive statistics for each of the variables used in the TAM survey revealed a higher mean score for Twitter users than non-users. Independent t-tests and Pearson product-momentum correlations indicated Twitter may have an impact on the determinants of perceived usefulness and perceived ease of use. Results from the three independent t-tests indicate a significant difference in scores for perceived usefulness and perceived between users and non-users of Twitter. The third t-test for behavioral intent, however, was not statistically significant. Results from the Pearson product-momentum correlations indicated a significant relationship between Twitter usage and perceived ease of use and perceived usefulness. The third variable, behavioral intent showed no significant relationship. These results are discussed further in the following sections organized by research question. Research question one. This research question asked if there was a difference in perceived usefulness of educational technology between users and non-users of Twitter?
Meredith 57 Educators who used Twitter for more than one hour per week exhibited higher scores on determinants of perceived usefulness, indicating there was a difference between groups. This included the determinants of perceived ease of use, subjective norm, image, job relevance, output quality, and results demonstrability. Research question two. This research question asked if there was a difference in perceived ease of use of educational technology between users and non-users of Twitter? Again, educators who used Twitter for more than one hour per week exhibited higher scores on most determinants of perceived ease of use, indicating there was a difference between groups. This included the determinants of computer self-efficacy, perceptions of external control, computer anxiety, computer playfulness, perceived enjoyment, and objective usability. Research question three. This research question asked if there was a difference in behavioral intent to use educational technology between users and non-users of Twitter? Educators who used Twitter for more than one hour per week did exhibit slightly higher scores on both the determinants of behavioral intent and voluntariness, but not enough for the category as a whole to be statistically significant. This is possibly due to the fact that the responses in the category of voluntariness vary based upon the different administrative requirements of school districts and not of an individual teacher’s preference. Research question four. This research question was “Does a relationship exist between online collaboration using Twitter and perceived usefulness of educational technology by K-12 educators?” Correlation tests indicated a significant positive relationship does exist between the time spent using Twitter for educational purposes and
Meredith 58 the perceived usefulness of educational technology. Trend analysis showed more time spent using the social media site indicated a higher degree of perceived usefulness. Research question five. This research question was “Does a relationship exist between online collaboration using Twitter and perceived ease of use of educational technology by K-12 educators?” Correlation tests indicated a significant positive relationship does exist between the time spent using Twitter for educational purposes and the perceived ease of use of educational technology. Trend analysis showed more time spent using the social media site indicated a higher degree of perceived ease of use. Research question six. This research question was “Does a relationship exist between online collaboration using Twitter and the intent to use educational technology by K-12 educators?” There was a slight difference in mean behavioral intent scores between those who use Twitter more frequently than those who do not. However, correlation tests indicated there was not a statistically significant relationship between the amount of time spent using Twitter for educational purposes and one’s behavioral intent to use educational technology. This is possibly due to the responses in the category of voluntariness, a determinant of behavioral intent, varying based upon administrative requirements of school districts and not of an individual teacher’s preference. Conclusions The literature reviewed for this study documented the challenges associated with the increased influx of technology into education, including lack of exposure and professional development (Hew & Brush, 2006; Hsu, 2016; Thota & Negreiros, 2015). However, previous studies failed to explore how PLNs supported through social media could play a part in educational technology implementation. This study sought to identify
Meredith 59 a possible solution through participation in collaborative learning opportunities for educators through the use of the social media site Twitter. Through the constructs of the Technology Acceptance Model, this study adds insight into how educators perceive the usefulness and ease of use of technology. Findings of this study suggest using Twitter for educational purposes may impact how useful and easy to use technology is perceived by teachers. This includes the use of Twitter for searching educational hashtags, reading articles or other resources found on Twitter regarding an educational topic, viewing videos or other resources found on Twitter regarding an educational topic, participating in a Twitter chat regarding an educational topic, or communicating one-on-one with a Twitter user regarding education. In each of the questions related to perceived usefulness, those educators who used Twitter for one hour or more per week exhibited higher mean scores than those who did not. This included scores on questions regarding the determinants of perceived ease of use, subjective norm, image, job relevance, output quality, and result demonstrability. Based upon these findings, it can be concluded that using Twitter for self-driven professional development may result in perspectives of improved status and job quality though technology usage. Participants who used Twitter for educational purposes saw apparent benefits from technology use in the classroom, believed that its use improved job performance, and often shared results of educational technology implementation with others. Additionally, in all questions related to perceived ease of use, educators who used Twitter for one hour or more per week exhibited higher means than those who did not. On questions about the topics of computer self-efficacy, perceptions of external control,
Meredith 60 computer anxiety, computer playfulness, perceived enjoyment, and objective usability, those educators who used Twitter for professional development responded with confidence and assertiveness in their use of educational technology. These educators indicated that they have less feelings of anxiety regarding technology and more confidence and enjoyment in implementing it within their classroom. Findings of this study suggest using Twitter for educational purposes impacts how useful and easy to use technology is perceived by teachers. This can likely be attributed to the benefits often associated with social media, such as the collective learning and sharing of new information as well as social rapport and interconnection (Jang, 2014). Previous research on social media shows that engaging in self-driven professional development through Twitter can result in transformational learning opportunities, better instructional practices within the classroom, a collaborative culture of learning, and interactive relationships (Visser, Evering, & Barrett, 2014). Based on the findings of this study, it can further be concluded that using Twitter for one hour or more per week for educational purposes may improve teachers’ perceptions of usefulness and ease of use, ultimately having a positive impact on the use of educational technology in the classroom. Implications for Practice Barriers regarding lack of professional development, negative beliefs, and exposure to technology could potentially be overcome if teachers consistently participated in collaborative learning opportunities that afforded them the knowledge, skills, and beliefs necessary for successful technology integration (Laferrière et al., 2013). The findings of this study indicate that engaging in Twitter for educational
Meredith 61 purposes impacts teachers’ perceptions of the ease of use and usefulness, key determinants for the amount of time spent using technology (Davis, 1989). These results have implications for K-12 educators seeking to engage in professional learning activities to improve educational technology implementation in the classroom. First, initiatives to get more educators to use Twitter is essential, as few in the profession engage in self-driven professional development facilitated by the site. This is evidenced by this study of which only one third of participants responded as having used Twitter for at least one hour per week. This could be attributed to features that make Twitter less user-friendly than other social media sites, ultimately deterring teachers from taking advantage of its benefits (AWWA…, 2011). Providing opportunities for teachers to learn how to navigate Twitter is critical so that more educators can begin to use the site for professional development. Also, those new to Twitter should work to engage with the site over a moderate period of time such as one year, as Marin and Tur (2014) found that this helps unfamiliar users overcome challenges associated with Twitter. Secondly, administrators need to advocate for more use of the site for self-driven professional development. Visser et al. (2014) recommended daily use so that it becomes routine, ultimately affecting teaching and pedagogy. However, many school districts restrict access to social media sites, including Twitter, which can keep many educators from using it consistently for professional reasons (Visser et al., 2014). One of the critical factors in determining what technology and social media individuals choose to use is convenience (Jang, 2014), so allowing access to Twitter during school hours is important for providing teachers more opportunities to engage in learning experiences. Potentially, this could also save educational agencies money in professional development while
Meredith 62 connecting teachers with a personalized and differentiated method of professional learning. Recommendations for Future Research While this study examined the use of Twitter in creating professional learning networks for professional development, the body of information that exists on this subject is limited. The results of this study are promising in relation to using social media for self-directed professional development., but additional research is needed to determine its impact on measurable skill development, particularly in regards to technology. Replications of this study are needed in which a much larger population of educators are surveyed and interviewed on their uses of Twitter for professional development. Jang’s (2014) qualitative study on millennials’ use of social media indicated that technologies are chosen based upon their ability to meet students’ learning needs. Convenience was also identified as one of the biggest factors for students’ choice of social media (Jang, 2014). Further study would be useful on factors influencing teachers’ choice of social media, and why many may choose platforms other than Twitter. Future studies should also seek to identify specific methods of professional development in which educators engage on Twitter. Visser et al. (2014) identified methods such as microblogging and backchannel use at conferences. Further study of such approaches could help educators identify which specific means of professional development are most beneficial as learning opportunities. Finally, future research would be beneficial on which education-related hashtags teachers use the most for self- directed professional development on Twitter. This could ultimately aid schools and districts in
Meredith 63 learning how to best support teachers’ participation in learning opportunities through social media. Concluding Remarks This chapter presented the study’s conclusions and implications for educators using educational technology in the K-12 classroom. Twitter, when used for educational purposes, can be a useful tool for teachers learning to implement new technologies. This study contributed to the literature by identifying a relationship between the use of Twitter for professional development and higher mean scores on the Technology Acceptance Model. Teachers looking to learn more about educational technology and how to implement it within their classroom should turn to the social media site and engage in self-directed professional development.
Meredith 64 References Adetimirin, A. (2015). An empirical study of online discussion forums by library and information science post- graduate students using Technology Acceptance Model 3. Journal of Information Technology Education, 14, 257–269. Retrieved from http://www.jite.org/documents/Vol14/JITEv14ResearchP257269Adetimirin1854.pdf AWWA Water Science and Research Division Information Management and Technology Research Committee. (2011). TEC project report: Social media and online collaboration tools’ place and purpose in committee work. American Water Works Association Journal, 103(12), 42-45. Balcikanli, C. (2015). Prospective English language teachers’ experiences in Facebook: Adoption, use and educational use in Turkish context. International Journal of Education and Development Using Information and Communication Technology, 11(3), 82–99. Bantwini, B. D. (2015). Analysis of the state of collaboration between natural science school district officials and primary school science teachers in South Africa. Journal of Baltic Science Education, 14(5), 586–599. Battersby, S. L., & Verdi, B. (2014). The culture of professional learning communities and connections to improve teacher efficacy and support student learning. Arts Education Policy Review, 116, 22–29. Retrieved from http://doi.org/10.1080/10632913.2015.970096
Meredith 65 Blitz, C. L. (2013). Can online learning communities achieve the goals of traditional professional learning communities? What the literature says. Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Mid-Atlantic. Retrieved from http://eric.ed.gov/?id=ED544210 Cardon, P., & Marshall, B. (2014). The hype and reality of social media use for work collaboration and team communication. International Journal of Business Communication, 52(3), 273–293. doi: 10.1177/2329488414525446 Carpenter, J. (2015). Preservice teachers’ microblogging: Professional development via Twitter. Contemporary Issues in Technology and Teacher Education, 15(2), 1–21. Carpenter, J. P., & Krutka, D. G. (2014). How and why educators use Twitter: A survey of the field. Journal of Research on Technology in Education, 46(4), 414–434. Retrieved from https://doi.org/10.1080/15391523.2014.925701 Creswell, J. W. (2015). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. (5th ed.) Upper Saddle River, NJ: Pearson Education. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. Donaldson, R. L. (2011). Student acceptance of mobile learning (Unpublished Doctoral Dissertation). The Florida State University College of Communication and Information, Tallahassee, FL. Retrieved from http://diginole.lib.fsu.edu/islandora/object/fsu%253A168891
Meredith 66 Duffield, S., Olson, A., & Kerzman, R. (2013). Crossing borders, breaking boundaries: Collaboration among higher education institutions. Innovative Higher Education, 38(3), 237–250. Retrieved from http://10.1007/s10755-012-9238-8 DuFour, R., & Eaker, R. E. (1998). Professional learning communities at work: Best practices for enhancing student achievement. Bloomington, IN: National Education Service. Fan, C. (2014). Applied the Technology Acceptance Model to survey the mobile-learning adoption behavior in science museum. International Journal of Innovation and Scientific Research, 12(1), 22–29. Retrieved from http://www.ijisr.issrjournals.org/abstract.php?article=IJISR-14-272-01 Forte, A. M., & Flores, M. A. (2014). Teacher collaboration and professional development in the workplace: A study of Portuguese teachers. European Journal of Teacher Education, 37(1), 91–105. http://dx.doi.org/10.1080/02619768.2013.763791 Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: current knowledge gaps and recommendations for future research. Educational Technology Research and Development, 55, 223–252. http://10.1007/s11423-0069022-5 Hidayanto, A. N., & Setyady, S. T. (2014). Impact of collaborative tools utilization on group performance in university students. Turkish Online Journal of Educational Technology, 13(2), 88–98.
Meredith 67 Hsu, P. S. (2016). Examining current beliefs, practices and barriers about technology integration: A case study. TechTrends, 60(1), 30–40. doi:10.1007/s11528-0150014-3 Jang, Y. (2014). Convenience matters: A qualitative study on the impact of use of social media and collaboration technologies on learning experience and performance in higher education. Education for Information, 31(1), 73–98. doi:10.3233/EFI150948 Johnson, E. S. (2015). Evidence-based practices: A program description of the Boise State University. Rural Special Education Quarterly, 34(1), 5–9. Kale, U., & Goh, D. (2014). Teaching style, ICT experience and teachers’ attitudes toward teaching with Web 2.0. Education and Information Technologies, 19(1), 41–60. doi:10.1007/s10639-012-9210-3 Laferrière, T., Hamel, C., & Searson, M. (2013). Barriers to successful implementation of technology integration in educational settings: A case study. Journal of Computer Assisted Learning, 29(5), 463–473. doi:10.1111/jcal.12034 Lazaro, H. (2015). What is educational technology and why should it matter to you [Blog]? Retrieved September 08, 2016, from https://generalassemb.ly/blog/whatis-edtech. Lin, M. F., Hoffman, E. S., & Borengasser, C. (2013). Is social media too social for class? A case study of Twitter use. TechTrends, 57(2), 39–45. doi: 10.1007/s11528-013-0644-2 Marin, V. I., & Tur, G. (2014). Student teachers’ attitude towards Twitter for educational aims. Open Praxis, 6(3), 275–285. http://dx.doi.org/10.5944/openpraxis.6.3.125
Meredith 68 Mills, M. (2014). Effect of faculty member’s use of twitter as informal professional development during a preservice teacher internship. Contemporary Issues in Technology and Teacher Education, 14(4), 451–467. Mishra, P., Koehler, M. J., & Kereluik, K. (2009). The song remains the same: Looking back to the future of educational technology. TechTrends, 53(5), 48–53. Munoz, L. R., Pellegrini-Lafont, C., & Cramer, E. (2014). Using social media in teacher preparation programs: Twitter as a means to create social presence. Perspectives on Urban Education, 11(2), 57–69. Murthy, D., Hastings, C. M., & Marie, S.A. (2015). The use of social media to foster trust, mentorship, and collaboration in scientific organizations. Bulletin of Science, Technology & Society, 34(5-6), 170–182. doi:10.1177/0270467615582196 Palmquist, J. E., & Barnes, G. V. (2015). Participation in the school orchestra and string Teachers Facebook v2 group: An online community of practice. International Journal of Community Music, 8(1), 93–103. doi:10.1386/ijcm.8.1.93_1 Pierce, G. L., & Cleary, P. F. (2016). The K-12 educational technology value chain: Apps for kids, tools for teachers and levers for reform. Education and Information Technologies, 21(4), 863–880. doi:10.1007/s10639-014-9357-1 Poulos, E., Culberston, N., Piazza, P., & D’Entremont, C. (2014). Making space: The value of teacher collaboration. The Education Digest, 80(2), 28–32.
Meredith 69 Pugach, M. C., Blanton, L. P., & Correa, V. I. (2011). A historical perspective on the role of collaboration in teacher education reform: Making good on the promise of teaching all students. Teacher Education and Special Education: The Journal of the Teacher Education Division of the Council for Exceptional Children, 34(3), 183–200. http://doi.org/10.1177/0888406411406141 Putman, S. M., Ford, K., & Tancock, S. (2012). Redefining online discussions: Using participant stances to promote collaboration and cognitive engagement. International Journal of Teaching and Learning in Higher Education, 24(2), 151– 167. Ramayah, T., & Jantan, M. (2007). Technology acceptance: An individual perspective current and future research in Malaysia. Retrieved from http://www.ramayah.com/journalarticlespdf/techacceptanceindividual.pdf Ramayah, T., Ma’ruf, J., Jantan, M., & Mohamad, O. (2002). The role of harmonization of economics and business discipline in global competitiveness. The proceedings of The International Seminar, Indonesia-Malaysia. Banda Aceh, Indonesia. Schirr, G. R. (2013). Community-sourcing a new marketing course: Collaboration in social media. Marketing Education Review, 23(3), 225–240. Shirley, M. L., Irving, K. E., Sanalan, V. A., Pape, S. J., & Owens, D. T. (2011). The practicality of implementing connected classroom technology in secondary mathematics and science classrooms. International Journal of Science and Mathematics Education, 9(2), 459–481. doi:10.1007/s10763-010-9251-2
Meredith 70 Shroff, R. H., Deneen, C. C., & Ng, E. M. W. (2011). Analysis of the technology acceptance model in examining students’ behavioural intention to use an eportfolio system. Australasian Journal of Educational Technology, 27(4), 600– 618. Sie, R. L. L., Pataraia, N., Boursinou, E., Rajagopal, K., Margaryan, A., Falconer, I., Bitter-Rijpkema, M., Littejohn, A., & Sloep, P. B. (2013). Goals, motivation for, and outcomes of personal learning through networks: Results of a Tweetstorm. Educational Technology & Society, 16(3), 59–75. Thoonen, E. E. J., Sleegers, P. J. C., Oort, F. J., Peetsma, T. T. D., & Geijsel, F. P. (2011). How to improve teaching practices: The role of teacher motivation, organizational factors, and leadership practices. Educational Administration Quarterly, 47(3), 496–536. doi:10.1177/0013161X11400185 Thota, N., & Negreiros, J. G. M. (2015). Introducing educational technologies to teachers: Experience report. Journal of University Teaching & Learning Practice, 12(1), 1–13. Retrieved from http://ro.uow.edu.au/jutlp/vol12/iss1/5 Trust, T., Krutka, D. G., & Carpenter, J. P. (2016). “Together we are better”: Professional learning networks for teachers. Computers and Education, 102, 15–34. http://doi.org/10.1016/j.compedu.2016.06.007 Tseng, H., Wang, C., Ku, H.-Y., & Sun, L. (2009). Key Factors in online collaboration and their relationship to teamwork satisfaction. Quarterly Review of Distance Education, 10(2), 195–206.
Meredith 71 Tutty, J. I., & Klein, J. D. (2008). Computer-mediated instruction: A comparison of online and face-to-face collaboration. Educational Technology Research and Development, 56(2), 101–124. doi:10.1007/s11423-007-9050-9 Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186– 204. Visser, R. D., Evering, L. C. and Barrett, D. E. (2014). Twitter for Teachers: The implications of Twitter as a self-directed professional development tool for K-12 teachers. Journal of Research on Technology in Education, 46(4). doi: 10.1080/15391523.2014.925694. Yi, M., & Hwang, Y. (2003). Predicting the use of web-based information systems: Selfefficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59, 431-449. Yost, H. S., & Fan, S. (2014). Social media technologies for collaboration and communication: Perceptions of childcare professionals and families. Australasian Journal of Early Childhood, 39(2), 36–41. Yuan Y-H, Tsai S-B, Dai C-Y, Chen H-M, Chen W-F, Wu C-H, et al. (2017). An empirical research on relationships between subjective judgment, technology acceptance tendency and knowledge transfer. PLoS ONE, 12(9): e0183994. https://doi.org/10.1371/journal.pone.0183994
Meredith 72 Appendices Appendix A
IRB Informed Consent Approval
Appendix B
Email: Invitation to Participate
Appendix C
Email: Closing Survey
Appendix D
Statement of Informed Consent
Appendix E
Survey Instrument
Meredith 73 Appendix A IRB Informed Consent Approval Mar 8, 2018 9:19 AM CST Virginia Shelton Elizabeth Meredith Educational Leadership, Users loaded with unmatched Organization affiliation. Re: Exempt - Initial - IRB-FY18-190 Technology Acceptance Model and the Influence of Twitter on K-12 Educators Dear Dr. Virginia Shelton Elizabeth Meredith Lamar University Human Subjects Review Board has rendered the decision below for Technology Acceptance Model and the Influence of Twitter on K-12 Educators. Decision: Exempt - APPROVED Selected Category: This approval is for a period of one year from the date of this memorandum. Please make timely submission of renewal or closure to your study. Remember to obtain approval from the Institutional Review Board before instituting any changes to the study.
Sincerely, Lamar University Human Subjects Review Board
Meredith 74 Appendix B Email: Invitation to Participate Dear Fellow Educator, As a doctoral student at Lamar University, I am researching the influence of Twitter collaborations on educational technology implementation in the K-12 classroom. In order to conduct this research, I need K-12 classroom teachers to participate in an anonymous online survey regarding their use or non-use of the social media site Twitter and their beliefs regarding educational technology. I am looking for both teachers who are familiar with Twitter as well as those who are not, and am asking for your participation within this study. If you are a teacher and indicate willingness to participate, you will respond to questions in an online survey that will take approximately 12 minutes to complete. The survey instrument is designed to gather information on your beliefs and attitudes regarding educational technology as well as the level of implementation with your classroom. Again, there is no requirement for you to be actively using any technology at this time. You also do not need to have a Twitter account to participate, nor will you need to create one. Participants who agree to complete the survey will be entered into a drawing to win one of five $20 Amazon gift cards. Winners will be notified by July 1st, 2018. Should you choose to participate, please know that your responses will be anonymous and kept confidential. You may choose to withdraw at any time after agreeing to participate in the study. To participate in this research please click on the link below where you will be
Meredith 75 directed to a consent agreement and the survey questionnaire. If you are not a teacher, but have contact with other teachers who may be interested in taking the survey, please email me. If you have any questions, please feel free to contact me at
[email protected].
Thank you so much for your time. Elizabeth Meredith
Meredith 76 Appendix C Email: Closing Survey Dear Fellow Educator, This is a friendly reminder to please take a moment to answer the questions attached in the link below. As a doctoral student at Lamar University, I am researching the influence of Twitter collaborations on educational technology implementation in the K-12 classroom and would greatly appreciate your participation. In order to conduct this research, I need K-12 classroom teachers to participate in an anonymous online survey regarding their use or non-use of the social media site Twitter and their beliefs regarding educational technology. I am looking for both teachers who are familiar with Twitter as well as those who are not, and am asking for your participation within this study. If you are a teacher and indicate willingness to participate, you will respond to questions in an online survey that will take approximately 12 minutes to complete. The survey instrument is designed to gather information on your beliefs and attitudes regarding educational technology as well as the level of implementation with your classroom. Again, there is no requirement for you to be actively using any technology at this time. You also do not need to have a Twitter account to participate, nor will you need to create one. Participants who agree to complete the survey will be entered into a drawing to win one of five $20 Amazon gift cards. Winners will be notified by July 1st, 2018. Should you choose to participate, please know that your responses will be anonymous and kept confidential. You may choose to withdraw at any time after agreeing to participate in the study.
Meredith 77 To participate in this research please click on the link below where you will be directed to a consent agreement and the survey questionnaire. If you are not a teacher, but have contact with other teachers who may be interested in taking the survey, please email me. If you have any questions, please feel free to contact me at
[email protected].
Thank you so much for your time. Elizabeth Meredith
Meredith 78 Appendix D Statement of Informed Consent Project Title: Technology Acceptance Model and the Influence of Twitter on K-12 Educators Researcher: Elizabeth Meredith E-mail:
[email protected] You have agreed to participate in a research study that aims at investigating the influence of Twitter collaborations on educational technology implementation in the K12 classroom. Your participation in this study is completely voluntary, and you have the right to withdraw from this study at any time without repercussions. The purpose of this quantitative study was to investigate if a relationship existed between educators using Twitter for online collaboration and the perceptions and implementation of educational technology within K-12 classrooms. In order to conduct this research, you agree to complete a brief online survey containing questions about online collaborations and educational technology. With indication of your willingness to participate, you will respond to questions in an online survey that will take approximately 10 minutes to complete. The survey instrument is designed to gather information on your beliefs and attitudes regarding educational technology as well as the level of implementation with your classroom. There is no requirement for you to be actively using any technology at this time. You also do not need to have a Twitter account to participate. Questionnaire responses will not be linked to individuals, and every attempt will be made to keep information gathered during the survey process as private as possible.
Meredith 79 By consenting to complete the study, you are agreeing that the information supplied will appear in professional reports of this research. I foresee no risks beyond those that are normally encountered in the normal classroom or workplace setting. The benefits associated with this study are the information gained about using social media for increasing educational technology implementation in the classroom. Your participation in this study is greatly appreciated. Once data have been analyzed and reported, feel free to contact me for any findings or implications of the study. Please feel free to email me if you have any questions or concerns about this research study. Your consent is being given voluntarily. You may refuse to participate in the survey. No service of any kind, to which you are otherwise entitled, will be lost or jeopardized if you choose to "not participate" in the study. If you decide to participate in the survey, you are free to withdraw at any time. Having read the above and having had an opportunity to ask any questions, please choose the option to give consent and begin the questionnaire.
Meredith 80 Appendix E Survey Instrument Demographics Please respond to the questions below: What is your age? 18 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 55 to 64 years Age 65 or older What is your gender? Female Male What is your highest education level? (choose one) Completed some high school High school graduate Completed some college Associate degree Bachelor's degree Completed some postgraduate Master's degree Ph.D., law or medical degree
Meredith 81 Other advanced degree beyond a Master's degree What subject(s) do you teach? (indicate all) Science Social Studies English Language Arts Mathematics Visual Arts Performing Arts Music Physical Education Health and Consumer Sciences Agriculture Foreign Language Other (please indicate:) What grade level(s) do you teach? (indicate all) Kindergarten Grades 1-2 Grades 3-5 Grades 6-8 Grades 9-12 How many total years of experience do you have within the field of education? (choose one) 0-5
Meredith 82 6-10 11-15 16-20 21-25 26-30 30+
Twitter Usage Twitter The following questions ask about your participation on Twitter for educational purposes. This includes the following types of activities: •
Searching Twitter for educational hashtags (i.e. #edchat, #edtech, #teacherpd).
•
Reading articles or other resources found on Twitter regarding an educational topic.
•
Viewing videos or other resources found on Twitter regarding an educational topic.
•
Participating in a Twitter chat regarding an educational topic.
•
Communicating one-on-one with a Twitter user regarding education.
How would you describe your use of Twitter for educational purposes? 1= little to no use (less than one hour per week) 2= moderate to high use (more than one hour per week) How much time do you spend each week using Twitter for educational purposes? 1= 0-1 hour per week 2= 1-2 hours per week
Meredith 83 3= 2-3 hours per week 4= 3-4 hours per week 5= more than 5 hours per week
Please answer the following questions using the scale below: 1= Strongly disagree 2= Disagree 3= Neither disagree nor disagree 4= Agree 5= Strongly agree Perceived Ease of Use (PEOU) •
PEOU1 My interaction with educational technology is clear and understandable.
•
PEOU2 Interacting with educational technology does not require a lot of my mental effort.
•
PEOU3 I find educational technology to be easy to use.
•
PEOU4 I find it easy to get educational technology to do what I want it to do.
Subjective Norm (SN) •
SN1 People who influence my behavior think that I should use educational technology.
•
SN2 People who are important to me think that I should use educational technology.
Meredith 84 •
SN3 The administration in my school and/or district has been helpful in the use of educational technology
•
SN4 In general, the district has supported the use of educational technology.
Image (IMG) •
IMG1 People in my school and/or district who use educational technology have more prestige than those who do not.
•
IMG2 People in my school and/or district who use educational technology have a high profile.
•
IMG3 Having the system is a status symbol in my organization.
Job Relevance (REL) •
REL1 In my job, usage of educational technology is important.
•
REL2 In my job, usage of educational technology is relevant.
•
REL3 The use of educational technology is pertinent to my various job-related tasks.
Output Quality (OUT) •
OUT1 The quality of the output I get from the system (educational technology) is high.
•
OUT2 I have no problem with the quality of the system’s (educational technology) output.
•
OUT3 I rate the results from the system (educational technology) to be excellent.
Result Demonstrability (RES)
Meredith 85 •
RES1 I have no difficulty telling others about the results of using educational technology.
•
RES2 I believe I could communicate to others the consequences of using educational technology.
•
RES3 The results of using educational technology are apparent to me.
•
RES4 I would have difficulty explaining why using educational technology may or may not be beneficial.
Computer Self-Efficacy (CSE) I could implement educational technology... •
CSE1 if there was no one around to tell me what to do as I go.
•
CSE2 if I had just the built-in help facility for assistance.
•
CSE3 if someone showed me how to do it first.
•
CSE4 if I had used similar packages before this one to do the same job.
Perceptions of External Control (PEC) •
PEC1 I have control over using educational technology in my classroom.
•
PEC2 I have the resources necessary to use educational technology in my classroom.
•
PEC3 Given the resources, opportunities and knowledge it takes to use educational technology, it would be easy for me to implement it within my classroom
Computer Anxiety (CANX) •
CANX1 Technology does not scare me at all.
•
CANX2 Working with technology makes me nervous.
Meredith 86 •
CANX3 Technology makes me feel uncomfortable.
•
CANX4 Technology makes me feel uneasy.
Computer Playfulness (TPLAY) The following questions ask you how you would characterize yourself when you use computers, tablets, or other technological device: •
CPLAY1 . . . spontaneous
•
CPLAY2 . . . creative
•
CPLAY3 . . . playful
•
CPLAY4 . . . unoriginal
Perceived Enjoyment (ENJ) •
ENJ1 I find using educational technology to be enjoyable.
•
ENJ2 The actual process of using educational technology is pleasant
•
ENJ3 I have fun using educational technology.
Objective Usability (OU) •
OU1 Using educational technology improves my performance in my job.
•
OU2 Using educational technology in my job increases my productivity.
•
OU3 Using educational technology enhances my effectiveness in my job.
•
OU4 I find educational technology to be useful in my job.
Behavioral Intention (BI) •
BI1 Assuming I had access to educational technology, I intend to use it.
•
BI2 Given that I had access to educational technology, I predict that I would use it.
•
BI3 I plan to use educational technology in the next
months.
Meredith 87 Voluntariness (VOL) •
VOL1 My use of educational technology is voluntary.
•
VOL2 My administrator does not require me to use educational technology.
•
VOL3 Although it might be helpful, using educational technology is certainly not compulsory in my job.
Use (USE) (USE1) The definition of educational technology is "a specific type of technology that is geared towards the creation and implementation of tools designed to promote education (Lazaro, 2015)." This includes activities such as: • Using the internet in class to teach a whole group or small groups of students. • Use of applications, simulations, or programs on technology devices to teach a whole group or small groups of students. • Guiding individual students using technology devices such as iPads, laptops, or other means to engage in learning and/or assessment. On average, how much time do you spend using educational technology in your classroom each day? 5= A great deal 4= A lot 3= A moderate amount 2= A little 1= None at all
Meredith 88 Biographical Note Elizabeth Meredith is the Coordinator of Curriculum and Director of Innovation at Rolling Hills Local Schools in rural southeastern Ohio. She has more than a decade of teaching experience in middle school science, and has also presented at multiple educational conferences. Having also spent two years as a curriculum writer for the Challenger Learning Center at Wheeling Jesuit University, she continues to conduct professional development workshops for other teachers on the use of educational technology in the classroom. In 2015, she became an Apple Distinguished Educator while also receiving NSTA’s Distinguished Teaching Award.
Style manual delegation:
Publication Manual of the American Psychological Association, Sixth Edition