Educational technology

This systematic literature review investigates K-12 social studies educators' perspectives on digital game-based learning (DGBL) from 2015 to 2024, focusing on its impact on student engagement, motivation, and learning outcomes. Using Braun and Clarke’s (2006) reflexive thematic analysis, data from 10 studies were synthesized. Four main themes emerged regarding engagement and motivation, and three concerning learning outcomes. Findings indicate that while teachers recognize DGBL's potential benefits, they prioritize meeting learning objectives over new instructional strategies due to teaching demands and limited suitable digital games. Barriers such as time constraints and resource limitations hinder broader DGBL implementation. Overcoming these challenges requires collaboration among educators, administrators, and policymakers to leverage DGBL in K-12 social studies education fully.

The computer industry does not understand how adults learn (Knowles, 1983). A profound statement made nearly 40 years ago. With the advancement of technology and the tremendous growth of online learning, the learning management system (LMS) has become the tool for delivering distance education. E-learning platforms have witnessed exponential uptake by the education and corporate sectors over the past three to five years (Wadhwani & Gankar, 2020). From this author's experience in the field of instructional design and online instruction, all LMSs are just a "database with a different user interface (Price, 2016)". But are there opposing perceptions from the online learner regarding two different systems of learning? With the migration of one LMS to another LMS at a large public state university, can an assumption be measured to determine significant differences between the two LMSs?
This quantitative research aims to answer if there are significant differences in online student perception between two different learning management systems. Using responses to Instructor Evaluation Forms during four academic years (12 semesters), this study determined if a significant difference existed between the perceived quality of two learning management systems. Moreover, this study added to a minimal body of research regarding improving the quality of learning management systems based on the perception of online students.

This mixed methods research study examined the relationship between faculty mindset and their perceived use of instructional technology in the higher education classroom. Recognizing the growing importance of technology-mediated learning interventions, the researcher sought to gain a deeper understanding of how mindset influenced the use of technology particularly amongst college of education faculty in Florida public 4-year universities.
Data analyses revealed the following findings: (a) Although participants shared a range of integration patterns, faculty predominantly integrated technology for knowledge transmission, backstage activity, and communication purposes; (b) Participants predominantly occupied the integration phase of technology implementation, suggesting that they used technology committedly, but in ways that were familiar and common; (c) The way participants perceived and approached technological realities influenced their patterns of technology integration; and (d) Faculty shared similar concerns about the challenges and benefits associated with technology integration in their classrooms.
The key implications that emerged from this study were that student-centered technology implementation practices were underrepresented, and that faculty seemed ill-equipped or underprepared to implement strategies surrounding accessibility.

This mixed methods study examined secondary teachers’ technology selfefficacy,
their professional development activities regarding mobile handheld devices,
and how those activities affect their use of mobile devices as instructional tools.
Additionally, this study also explored teachers’ perceptions of other factors that act as
barriers or enablers to their use of such devices. The study included 104 middle and high
school teachers who taught in a large, urban public school district in the Southeastern
United States. Data were collected through the administration of an electronic survey and
semi-structured interviews. The researcher utilized multiple regression and moderator
analyses, as well as qualitative analysis of the interview data.
The results of the multiple regression analysis revealed teachers’ technologyrelated
self-efficacy to be a significant predictor of their instructional use of mobile
handheld devices. However, secondary teachers’ level of professional development was found not to contribute significantly to the model. The moderator analysis too revealed
professional development to be a nonsignificant factor. The findings of the qualitative
phase of the study revealed secondary teachers’ awareness of their varied and fluid
technology-related self-efficacy, as well as those factors that modify it. Qualitative data
also revealed four categories of essential elements that teachers must have in order to
most effectively implement mobile handheld devices within their pedagogy: intellectual
capital, emotional capital, social-cultural capital, and technological capital. When
lacking, these elements can represent barriers to teachers’ implementation of mobile
handheld devices. Targeted professional development and increased funding to minimize
the digital divide are recommended to reduce these barriers. The findings of the study
inform designers of professional development programs, school and district and
secondary teachers, as they are all stakeholders in the process of increasing the effective
implementation of mobile handheld devices as instructional tools.

The purpose of this research study was to determine K-12 school leaders' concepts of ability and technology readiness. The Theories of Intelligence Scale (TIS) was used to analyze concepts of ability and the Technology Readiness Index (TRI) 2.0 was used to analyze the technology readiness of K-12 school leaders. Data from the two instruments were used to determine if there was any relationship between K-12 school leaders' concept of ability and technology readiness. This analysis filled a blank spot in the research contributing to the literature on leadership, Mindset Theory (Dweck, 2006; Dweck, Chiu, & Hong, 1995), and Technology Readiness (Lin & Hsieh, 2012; Parasuraman, 2000). Furthermore it helped to determine the state of K-12 school leaders' status as 21st century leaders. The sample consisted of the school leaders of School District of Palm Beach County (SDPBC). This included 158 principals from 104 elementary, 31 middle, and 23 high schools. The researcher was a school district employee and therefore had access to the participants. Each of the four null hypotheses were rejected as SDPBC school leaders scored significantly higher on the TIS (p < .05) and TRI 2.0 (p < .01), there was a significant (p < .0125) positive relationship between TIS and the TRI 2.0, and that relationship was affected (p < .05) by gender, race, and experience.

The purpose of this mixed methods study was twofold. First, the study
assessed whether Davis’ (1989) Technology Acceptance Model (TAM) was
useful in predicting instructional usage of the interactive whiteboard (IWB), as
reported by K-8 teachers. Second, the study set out to understand what
motivated those teachers to use the IWB for classroom instruction, and to further
describe the ways in which they used them. Through surveying 155 teachers
and 40 administrators of the Lutheran Church Missouri Synod (LCMS) schools,
the researcher used multiple regression and moderator analyses to examine
whether the TAM model helped explain teachers’ reported teacher-centered and
student-centered instructional IWB usage. The researcher followed this by oneon-
one interviews with 5 of the teachers surveyed. With the data gathered from
the interviews and open-ended items from the original surveys, an analysis using qualitative methods was performed. The results from the qualitative analysis
were then used to help refine and explain the quantitative findings.
The results of the study’s quantitative phase indicated two variables
adapted from the TAM, teachers’ perceived usefulness and perceived ease of
use of the IWB, contributed to the prediction of teacher-centered instructional
usage of the device. Further it was found that the perceived usefulness variable
contributed to the prediction of student-centered instructional usage. Moderator
analysis indicated the variable for teachers’ IWB technological pedagogical
content knowledge, adapted from Mishra and Koehler’s (2006) technological
pedagogical content knowledge framework, moderated the relationships between
the variable perceived ease of use of the IWB and teacher and student-centered
instructional usage respectively, as well as between the variable perceived
usefulness of the IWB and teacher-centered instructional usage.
The qualitative phase results revealed those teachers surveyed used their IWBs
in a variety of ways for both teacher-centered and student-centered instruction.
Teachers frequently reported they were motivated to use the device by its overall
user-friendliness and its utility as an instructional tool. Central to the teachers’
discussion of its utility were ways in which the tool positively impacted the
students during instruction. Specifically how it engaged students by attracting
their attention, keeping them focused, and offering them a better way to learn.

The purpose of this research project was to develop a predictive model for faculty integration of technology in higher education, specifically among faculty who are members of the Commission of Professors of Adult Education. The variables included both those that the educational institution could affect, such as technical support, release time, tenure and promotion opportunities, and personal variables of faculty, such as computer self-efficacy, attitudes towards computers and perceived institutional support. Three hundred and eighty-nine (389) surveys were mailed to the sample participants. One hundred and twenty-four (124) were returned completed, thirty-six were returned undeliverable and seven were deemed unusable, for a return rate of 33.14%. The survey used in this study, the "Instructional Technology Integration Assessment" was adapted from the Computer Self Efficacy Scale (CSE), developed by Murphey and others (1988) and the Middle Tennessee State University Survey developed by Lea, Brace and Roberts (1998). Multiple regression was performed, using the Statistical Package for the Social Sciences (SPSS) to determine which of the variables showed a stronger influence on the dependent variable. Integration of technology significantly correlated with five of the variables: Job Satisfaction (.403, p < .001); Quality of My Instruction (.422, p < .001); Tenure and Promotion Opportunities (.240, p < .05); and the Impact of Technology on the Depth and Breadth of Content and Student Participation (.347, p < .001). Years Teaching in Higher Education was negatively correlated with Integration (-.185, p < .05). With a multiple regression correlation coefficient (R) of .550, the squared multiple correlation coefficient (R2) resulted in .303. Thirty percent (30%) of the variance in integration could be accounted for by the predictor variables. Analysis of responses to open-ended questions revealed three main themes in regards to barriers and incentives for technology integration: psycho/social barriers, student readiness barriers and institutional barriers. Suggestions for future research included adding variables such as learning style, teaching style and fear of change to the overall survey.

Studying the relationship between the achievement of technology standards and the availability of on-site support will help educational leaders prepare and modify individual and district-wide technology plans in the years ahead. There are many factors influencing success rates in attaining these standards, including the availability of hardware and software, the adequacy of the equipment, and the amount of training provided to teachers. The relationships between the predictor variable, on-site support and the dependent variables, hardware, software, training, integration, and networking were investigated using correlation analysis in the 190 public schools of Broward County, Florida. The relationships between the additional predictor variables of socioeconomic status and school level and the dependent variables were also examined. An alpha level of.01 was used for all statistical tests. Correlations were found to be significant (p<.01) between on-site support (N=190) and the dependent variables, hardware (r=.338), software (r=.563), training (r=.451), integration (r=.432), and networking (r=.315). Correlations between socioeconomic status (n=174) and school level (N=190) and the dependent variables were found not to be significant (p<.01). The study confirmed that increased levels of technological support helped public schools in Broward County realize greater success in achieving specific technology standards. Educational leaders should consider these findings significant when staffing schools and centers. Further, the socioeconomic status of a school did not influence the achievement of technology standards in the sample. This indicated that schools in this study had access to hardware, software, training, and other resources at a level equal to each other. Broward County policymakers seemed to have succeeded with their efforts to ensure that all schools had access to the funds and other resources needed to meet the locally established standards of technology.

The purpose of this study was to describe the influences that impact upon an individual faculty member as he or she makes the decision whether or not to participate in technology-based distance education. A two-site, qualitative case study design was used and the primary sources of data were interviews, document analysis, and researcher non-participant observations. The sample of 20 included ten higher education faculty members who currently are teaching courses using distance learning technology and ten who are not, five from each category at each of the two sites. Findings were grouped and addressed by seven areas of influence: trappings of the job, instructional quality, pioneering spirit, leadership, student needs and capabilities, supporting students, and competition and image. Within the seven areas, 21 specific influences were identified and described. Strong enhancers were an interest in emerging technology, desire to improve the current situation, changing student demographics, need for increased flexible access to educational opportunities, technology training and assistance for students, student to student support systems, distance-friendly student services, competition with other institutions, and collaboration. Detractors included extra workload, tenure and job security fear, love of the traditional classroom paradigm, lack of a reliable technology infrastructure, lack of administrative direction and support, and a negative image of distance education. Acting both as enhancers and detractors were student readiness, match of technology with learning sought, ability to create an interactive learning community, and ability of students as independent learners. The conclusion is drawn that faculty members at these two institutions are more likely to decide to use technology-based distance education if they hold four primary beliefs: (1) that it can produce a quality learning experience, (2) that it will better meet student needs, (3) that they personally are capable of developing and/or delivering it effectively, and (4) that it is to their advantage to develop and/or deliver it. These four beliefs are in their order of importance as voiced by the participants in this study. Recommendations are offered to administrators, in the form of specific actions to take to encourage participation by faculty members at their institution.

The identification of effective practices is of significant interest to school administrators, faculty, and staff planning and implementing professional development initiatives in technology. This study identified recommended practices for professional development in technology in elementary schools and determined if current practices reflected those recommendations. Studies by Wenglinsky (1998) for the Educational Testing Service reported the effective use of technology by classroom teachers has a positive impact on student performance. More recent studies frequently indicate teachers are not being trained to use technology effectively; and consequently, limited integration of technology in the classroom is taking place (Catchings, 2000; Howery, 2001; Johnson, 2002). Ham's assertion in 1999 that very few studies make the process of professional development the object of research remains true today. A literature review of current research revealed commonly recommended professional and governmental guidelines, standards, and principles. Published recommended practices of professional development in technology indicated similar practices in the areas of planning, implementation, and follow up/support. The Staff Development in Technology Survey was sent via the Internet to 200 participants including 56 providers of professional development and 144 receivers. Actual practices as described by providers and receivers were compared with recommended practices from the literature review. An analysis of variances (ANOVA) indicated a significant difference between the responses of the providers and receivers in the areas of planning (p < .02), implementation (p < .01), and follow up/support (p < .01). The providers' mean ratings of perception of the effectiveness of planning (p < .01) and effectiveness of follow up/support (p < .05), was significantly different from the receivers' perceptions. There was no significance between responses regarding the effectiveness of implementation. A Model of Effective Professional Development in Technology, developed from the analysis of the literature reviewed and responses from providers and receivers, provides a foundation for school administrators, faculty, and staff in planning, implementing, and providing follow up/support for professional development in technology. Professional development should take place in a collaborative environment with extensive support and resources available. Administrators, faculty, and staff working together using the model ought to be able to implement effective professional development in technology.