Trends In Educational Technology Research Articles

Bibliometric Analysis to Reveal Research Evolution and Educational Technology Trends in Civil Engineering Education

Civil engineering education is a discipline that endeavors to find the best way through various pedagogical methods to teach civil engineering to prospective civil engineers. Civil engineering education is in the spotlight along with developments in construction technology and its application in learning. Thus, civil engineering education offers a broad field of research in the context of education and construction sciences. Therefore, investigating the evolution of educational research and technology trends in civil engineering education is of interest. In this context, we performed a bibliometric analysis of 545 Scopus and Web of Science (WoS) global publications in the field of civil engineering education published during the period 1967 to 2022. A comprehensive bibliometric analysis was conducted using the R language-based software Biblioshiny. The research results show that, first, research trends in civil engineering education in the 55-year period were divided into 6 themes, namely: engineering education, civil engineering education or construction education, fields of civil engineering, technology in engineering education, global and social aspects, and other. Second, the United States is a leader in civil engineering education research, as most authors and journals are from this country. Third, the evolution of educational technology in civil engineering education can be described in five eras: 1) simple software era (1976–1990); 2) geographic information systems (GIS) and virtual reality (VR) era (1991–2000); 3) multimedia and e-learning era (2001–2010); 4) building information modeling (BIM) era (2011–2022); and 5) the forthcoming era (2023−future). Using computers as analysis and visualization tools became increasingly accurate and real, such as the integration of VR technology and incorporation of BIM technology. These findings might help researchers regarding the future direction of research and educational technology in civil engineering.

Benefits of Teaching English to Children in Virtual Classes: Teachers’ Perspectives from Khanh Hoa Province, Viet Nam

Over the past decade, technological advancements have greatly impacted the education industry, leading to the rise of online teaching and learning as a promising trend worldwide. However, in Viet Nam, research on virtual classrooms for young learners has been relatively limited. As a result, a recent study sought to examine English teachers’ perspectives on the benefits of teaching English to children virtually. This study utilized a mixed-methods approach to collect data through an online questionnaire distributed to 52 English teachers in Khanh Hoa Province, Central Viet Nam, who had at least one-year experience in teaching English to children online and in-depth interviews with 15 of them. The findings revealed that virtual classrooms offer numerous benefits for teachers, such as integrating all four language skills, enhancing teaching and learning performance, improving their digital skills, keeping up with educational technology trends, accessing a wealth of resources on educational websites, and fostering creativity in developing activities that enhance children’s engagement and motivation in English lessons. Overall, this study highlights the valuable benefits of teaching the English language to children in virtual settings. The findings hold relevance for other stakeholders involved in the development of virtual language education in Viet Nam and similar contexts.

The Influence of Technology in the World of Education

This study investigates the influence of technology in the world of education. With the rapid advancement of digital technology, its impact on educational practices and outcomes has become increasingly significant. Through a comprehensive review of existing literature, this research explores the multifaceted influence of technology on various aspects of education, including teaching methods, learning experiences, student engagement, and educational outcomes. The study examines how technology has transformed traditional classroom settings, facilitating the adoption of innovative teaching strategies such as flipped classrooms, blended learning, and personalized instruction. Additionally, it investigates the role of educational technology tools such as learning management systems, interactive whiteboards, and educational apps in enhancing instructional delivery and facilitating student learning. Furthermore, the research explores the broader implications of technology in education, including its potential to democratize access to education, bridge learning gaps, and foster lifelong learning. It also addresses challenges associated with technology integration, such as digital divide, privacy concerns, and the need for teacher professional development. Moreover, the study discusses emerging trends in educational technology, such as the use of artificial intelligence, virtual reality, and gamification, and their potential to revolutionize educational practices and outcomes. By synthesizing empirical evidence and theoretical frameworks, this research provides insights into the transformative power of technology in education and its implications for educational policy and practice. Ultimately, this study contributes to a deeper understanding of the influence of technology in the world of education and highlights the opportunities and challenges associated with its integration into teaching and learning environments. It serves as a foundation for future research and informs evidence-based strategies for leveraging technology to enhance educational outcomes and promote lifelong learning.

Bibliometric Analysis of Technology Trends in Education: Analysis from 2018 to 2022

Technology is a basic need of everyone so it can be said that educational innovation and educational technology are inseparable whole and causes the use of technology in the scope of education to be a must to achieve a more advanced and quality education. Therefore, it is important to know the development of technology in the scope of education so that it can be the basis for technological development in education in the future. The purpose of this study is to analyze and find out the trends of technology research in the field of education in the last 5 years starting from 2018 to 2022. This study uses bibliometric analysis which is a quantitative statistical analysis tool that is often used to provide analysis of existing publications with the help of VOSviewer to visualize data and use databases in Scopus. Then, based on the results of the analysis, 547 publications were obtained in the span of 5 years, starting from 2018 to 2022, furthermore, technological research trends in education related to publication growth and leading affiliations, leading country and subject area, the most source title, the most cited source, the most cited authors, and keywords co occurances analysis. In addition, this research contributes and also opens up opportunities for future researchers to be able to conduct research related to technology in education, which is still small in the density visualization area.

Rethinking Education: An In-Depth Examination of Modern Technologies and Pedagogic Recommendations

Educational technology has changed the teaching and learning process in many ways. As teachers needed new strategies to adapt to emerging technology tools and to interact with students, immediate feedback and digital instructional resources had become the norm. Teaching and learning expectations are growing because of technological improvements. Many digital libraries and online resources are now easily accessible to teachers and students. Therefore, a qualified teacher must be aware of the new teaching requirements and the adjustments related to educational technology trends. Additionally, it is important to adopt a Technological Pedagogical Content Knowledge (TPCK) framework and to clarify how teachers and students can collaborate to achieve learning outcomes through updated educational practices. This collaborative education can occur because technology makes it easier for students and teachers to interact together, despite the physical distance that could separate them. This paper emphasizes the optimum use of educational technologies and the potential of new digital tools that have already been exploited in an unprecedented way. It aims to provide a comprehensive review of current technologies with pedagogic recommendations, to highlight the importance of educational technologies in teaching, and to reconsider strategies for acquiring digital skills in the Artificial Intelligence era. The discussion revolves around identifying and depicting various advanced educational technologies that can be integrated with engaging pedagogical approaches. Furthermore, it explains how each technology can enhance the learning experience, emphasizing the teacher’s role in the technology-based educational process.

Revisiting Unified Theory of Technology and Use of Technology Using Meta-analytic Structural Equation Modelling

The Unified Theory of Technology and Use of Technology (UTAUT) has been widely used in information system studies since its introduction in 2003. The current study synthesizes 40 empirical studies based on UTAUT in educational contexts using the one-stage meta-analytic structural equation modelling method. While the study confirmed the initial findings by Ventakesh et al. (2003), the model in this study underperformed in the explained variance of behavioral intention. However, the explained variance of usage behavior performed better than the original UTAUT. After introducing new direct relationships between the UTAUT constructs, it was found that the construct, facilitating conditions, was a new predictor of behavioral intention. At the same time, effort expectancy and social influence were new predictors of usage behavior. There have been studies on the UTAUT model with many diverse findings since its inception in 2003. The method introduced in this study, a One-Stage combined Meta-Analysis and Structural Equation Modelling (OSMASEM), offers an approach for researchers to use past empirical data to examine the UTAUT framework without relying on replicating similar studies. As more empirical data from UTAUT research are added to train the data model using OSMASEM, researchers can now study how educational technology trends change over time.

How Educational Technology Trends Benefit Children with Autism Spectrum Disorder (ASD)

This study explores various educational technology trends used in Autism Spectrum Disorder (ASD) education by examining peer-reviews published investigations. ASD is a neurodevelopmental disorder characterized by an unfortunate lack of social skills and ongoing categorized behavior. These characteristics affect people with the socialization of ASD and present barriers to initiating and engaging in social interactions. As a result, more and more children worldwide are diagnosed with ASD. According to the US Centers for Disease Control and Prevention (CDC), the latest occurrence estimate is 1 in 59 (Pliasa & Fachantidis, 2019). The purpose of the study also includes the "augmentative and alternative communication" (AAC) systems because these methods provide support for the effectiveness of high-tech "electronic speech generating devices" (SGD) and low -the tech of "picture exchange communication system" (PECS) (Gilroy et al., 2018, p. 6). As a part of technology trends, this paper also analyzes assistive technology (AT) and how it benefits children with Autism Spectrum Disorder (ASD)

Research Trends in Educational Technology

The researchers of this study selected five journals in the field of education and conducted a series of analyses regarding publications dating from 2010 to 2019 to investigate the research trends and characteristics in the field of Educational Technology. By using the analytic tool Content Analysis Toolkit for Academic Research (CATAR), the researchers in this study conducted bibliometric analysis and breakdown analyses to summarize major contributing countries, educational institutions, most productive authors, and most cited papers; moreover, they used co-word analysis to reveal the representative items within each cluster. The findings in this study can provide implications and references for educators and researchers in the field of Educational Technology when selecting variables for their studies and technologies for their students.

The Role of Emerging Trends in Education

Emerging Technology Trends in Education is defined as those technologies that represent new and significant developments in the field like the Internet of Things (IoT), Education 4.0 which uses the Blending Learning, Augmented Reality, and Virtual Reality. In this time of Pandemic there are lots of challenges encountered like we cannot conduct a face to face classroom instruction and even the simulation of activities. Educational courses that require laboratory of simulation of activities is the biggest challenges because students are having hard time in understanding the practical real-time applications. In this time of Pandemic the evolution of Emerging Trends in Education helps a lot because it’s characteristics to adopt the requirements as required by the Inter-Agency Task Force on COVID-19 (IATF.)The purpose of the study is to help and strengthen the role of the Emerging Trends in our Education amidst the Pandemic and to help our Educational Sector boost up the level of education in the new Normal Approach and schools will be able to adapt these emerging technologies specially in this time of a pandemic. In conclusion Emerging Trends plays a vital role because majority of the educational sector are now using Augmented Reality (AR) and Virtual Reality (VR) in their practical laboratory exercises while at home.

Towards teaching analytics: a contextual model for analysis of students' evaluation of teaching through text mining and machine learning classification.

Recent trends in educational technology have led to emergence of methods such as teaching analytics (TA) in understanding and management of the teaching–learning processes. Didactically, teaching analytics is one of the promising and emerging methods within the Education domain that have proved to be useful, towards scholastic ways to make use of substantial pieces of evidence drawn from educational data to improve the teaching–learning processes and quality of performance. For this purpose, this study proposed an educational process and data mining plus machine learning (EPDM + ML) model applied to contextually analyze the teachers’ performances and recommendations based on data derived from students’ evaluation of teaching (SET). The EPDM + ML model was designed and implemented based on amalgamation of the Text mining and Machine learning technologies that builds on the descriptive decision theory, which studies the rationality behind decisions the learners are disposed to make based on the textual data quantification and statistical analysis. To this effect, the study determines pedagogical factors that influences the students' recommendations for their teachers, what role the sentiment and emotions expressed by the students in the SET play in the way they evaluate the teachers by taking into account the gender of the teachers. This includes how to automatically predict what a student’s recommendation for the teachers may be based on information about the students’ gender, average sentiment, and emotional valence they have shown in the SET. Practically, we applied the Text mining technique to extract the different sentiments and emotions (intensities of the comments) expressed by the students in the SET, and then utilized the quantified data (average sentiment and emotional valence) to conduct an analysis of covariance and Kruskal Wallis Test to determine the influential factors, as well as, how the students’ recommendation for the teachers differ by considering the gender constructs, respectively. While a large proportion of the comments that we analyzed (n = 85,378) was classified to be neutral and predominantly interpreted to be positive in nature considering the sentiments (76.4%), and emotional valence (88.2%) expressed by the students. The results of our analysis shows that for the students’ comments which contain some kind of positive or negative sentiment (23.6%) and emotional valence (11.8%); that females students recommended the teachers taking into account the sentiments (p = .000). While the males appear to be slightly borderline in terms of emotions (p = .056) and sentiment (p = .077). Also, the EPDM + ML model showed to be a good predictor and efficient method in determining what the students’ recommendation scores for the teachers would be, going by the high and acceptable values of the precision (1.00), recall (1.00), specificity (1.00), accuracy (1.00), F1-score (1.00) and zero error-rate (0.00) which we validated using the k-fold cross-validation method, with 63.6% of optimal k-values observed. In theory, we note that not only does the proposed method (EPDM + ML) proves to be useful towards effective analysis of SET and its implications within the educational domain. But can be utilized to determine prominent factors that influences the students’ evaluation and recommendation of the teachers, as well as helps provide solutions to the ever-increasingly need to advance and support the teaching–learning processes and/or students’ learning experiences in a rapidly changing educational environment or ecosystem.

Identification and evaluation of technology trends in K-12 education from 2011 to 2021.

Educational technologies have captured the attention of researchers, policy makers, and parents. Each year, considerable effort and money are invested into new technologies, hoping to find the next effective learning tool. However, technology changes rapidly and little attention is paid to the changes after they occur. This paper provides an overall picture of the changing trends in educational technology by analyzing the Horizon Reports’ predictions of the most influential educational technologies from 2011 to 2021, identifying larger trends across these yearly predictions, and by using bibliometric analysis to evaluate the accuracy of the identified trends. The results suggest that mobile and analytics technologies trended consistently across the period, there was a trend towards maker technologies and games in the early part of the decade, and emerging technologies (e.g., VR, AI) are predicted to trend in the future. Overall, the specific technologies focused on by the HRs’ predictions and by educational researchers’ publications seem to coincide with the availability of consumer grade technologies, suggesting that the marketplace and technology industry is driving trends (cf., pedagogy or theory).

Co-word analysis and academic performance from the Australasian Journal of Educational Technology in Web of Science

Since its inception in 1985, the Australasian Journal of Educational Technology (AJET) has been dedicated to the diffusion of studies on the integration of technology in higher education. Its track record in this field has placed it in the first quartile of the Scimago Journal & Country Rank. The objective of the study was to reveal to the scientific community the journey and evolution that this journal has had throughout its existence in Web of Science. A bibliometric methodology was used, supported by a scientific mapping from a unit of analysis of 798 documents. For this reason, a co-word analysis can be a fundamental tool for understanding the characteristics of their production and their impact on the scientific community. There is an evident progressive evolution of the studies published in the Australasian Journal of Educational Technology, with a first phase focused on the design and implementation of educational technology in learning environments, a second phase focused on the enrichment of technology and its acceptance within the processes of teaching and learning, and finally a stage focused on student and teacher perceptions of the implementation of technology in the educational context.
 Implications for practice or policy:
 
 We have established a contextual framework to show researchers current trends in educational technology and delineate future lines of research.
 Those interested in this subject will have a set of bibliometric indicators to delve into the field of educational technology.
 Higher education teachers and students will discover the evolution of the use of technology in learning spaces.

Educational Technology Trends in Online Lectures

Educational Technology Trends in Online Lectures

Educational Technology Research Trends: A Bibliometrics Analysis And Visualization

Educational Technology has been developing in recent years. The implementation of educational technology has collaborated in several fields such as social scienc-es, computer science, engineering, and medicine. In this study, the researcher has conducted a bibliometric analysis of educational technology research during the period 1971 to 2019. A total of 8,134 bibliographic data have collected from the Scopus database. VOSviewer software are used for analysis. In the bibliometric analysis, various extracted metadata include journals and affiliations, citations, keyword distribution, many cited papers, and the most influential authors and journals. This study shows the development status and trends in educational technology. On the other hand, this study can be used as a reference for research and application of bibliometric analysis.

The Potential of Artificial Intelligence in Higher Education

Artificial Intelligence (AI) is seeping into many aspects of our everyday lives, with common internet applications, smartphones and even household appliances. Within education, AI is a rapidly emerging field and there is a strong potential for AI to greatly extend and enhance teaching and learning in higher education (Crompton et al., 2020). AI is defined as “computing systems that are able to engage in human-like processes such as learning, adapting, synthesizing, self-correction and use of data for complex processing tasks” (Popenici & Kerr, 2017). In the Horizon Report 2020 report (Brown et al., 2020), AI is listed as one of six technologies with the potential for high impact in higher education. The Horizon Report (2020), is an annual publication that examines the major trends in educational technology that are shaping global higher education. This paper will highlight some of the ways AI is supporting both students and faculty members including bespoke learning, intelligent tutoring systems, facilitating collaboration, and automated grading. This is followed by a section on ethical implications.

Adoption and Use of Educational Technology Tools by Marketing Students

Changing trends in educational technology are one of the driving forces behind many of the new educational strategies Higher Education Institutions are introducing. These changes are frequently justified with the “digital native” nature of the current generation of students who have been surrounded by digital technology from the moment they were born and are expected to also feel comfortable to use and adopt technological tools for their learning purposes. There have been many studies trying to assess the veracity of this assumption, but we still do not have enough data to confirm or deny this willingness and aptitude or even assess if students benefit from a technologically supported approach to learning. More studies are therefore necessary, in particular in subject areas that are not so connected to the technology, like humanities, economics, and social sciences, where students cannot be expected to be so proficient in the use of those tools and therefore their technology adoption process might be dependent of other variables. This article intends to contribute to this effort by presenting a study that uses the UTAUT model to assess which variables influence the use and adoption of educational technologies’ tools by Higher Education Marketing students. The result showed that, for these students, Social Influence (or Social Factors) was the most relevant variable to determine their Behavioural Intention.

Research Trends in Educational Technology in Turkey: 2010-2018 Year Thesis and Meta-Analysis of Articles

Research Trends in Educational Technology in Turkey: 2010-2018 Year Thesis and Meta-Analysis of Articles

A Framework for the Systematic Evaluation of Anatomy Education Apps

BackgroundMobile‐based applications (Apps) are one of the fastest growing trends in educational technology. A search on the iTunes App Store, for example, results in 142 Apps in response to the search term “anatomy”. However, most educational Apps are not peer‐reviewed. The quality and accuracy are suspect, and few have been evaluated in the classroom. A comprehensive resource that provides guidance as to the educational usefulness, quality, and content accuracy of Apps in the anatomical sciences is needed.Aims To triangulate existing educational technology frameworks into a framework for evaluating anatomy education Apps With a national sample of academic technology leads, faculty and students, test and validate the framework MethodsPhase 1 triangulated peer‐reviewed articles on Apps, with known educational technology frameworks from the literature (Hanrahan et al., 2014; Liu et al., 2010; Romrell et al., 2014; Ruiz et al., 2006; Van Nuland et al., 2017). Phase 2 validated the framework in two steps. Phase 2A used chain referral sampling (i.e. n = 6 with at least one educational technology lead from each of the four AAMC regions: East, West, South, and Central) to obtain feedback. In Phase 2B, participants were recruited from Anatomy Connected Open Forum and through chain referral sampling (n = 58 agreed to participate). Participants applied the revised framework to two anatomy apps (Complete Anatomy and Heart Pro III) and completed a content validity survey. All methods were approved by the Colorado Multiple Institutional Review Board.ResultsPhase 1 resulted in the formation of a framework that was revised in Phase 2a and is hosted here https://docs.google.com/forms/d/1s5VWA1OfE‐HGNLz_LezMb3ngofPztRaOb7PFCXl_jjc/viewform?edit_requested=true. A total of 25 participants (14 faculty, 4 tech leads and 7 students) fulfilled all parts of Phase 2b to completion. Content validity was analyzed using Lawshe's content validity ratio; critical values (>0.39 as determined by Wilson et al., 2012) with 0.05 significance for two‐tailed test were achieved with 11 of the 26 criteria, including usability, organization, reliability, navigation, self‐assessment, content breadth, content depth, content accuracy, multimedia accuracy, recommendation for others, and overall value.Discussion and ConclusionAnatomy Education App framework validation presents a major asset for students, faculty and administrators based on feedback from a national panel; the framework is freely available. The validation is limited by the low number of respondents, but will be enhanced as more investigators apply the framework to their research.Support or Funding InformationRymer Small Grants Program, Academy of Medical Educators, University of Colorado School of MedicineThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Effectiveness of Gamification of Web-Based Learning in Improving Academic Achievement and Creative Thinking among Primary School Students

Gamification is one of the most significant modern trends in educational technology. The present study aims to identify the effectiveness of gamification of web-based learning on academic achievement and creative thinking among primary school students. A learning environment was designed based on gamification of web-based learning. A quasi-experimental approach was utilized to identify the effect of the independent variable, gamification, on the dependent variables, academic achievement and creative thinking among participants. An academic achievement test and the Torrance test of creative thinking were applied to the participants. Results revealed that there was a statistically significant difference between the means of scores of the experimental and control groups in the post-test academic achievement test and the Torrance test of creative thinking in favor of the experimental group. This suggests a high level of academic achievement and creative thinking after using gamification. The study recommends training in-service teachers in the use of gamification for web-based teaching of English.

Enjoy physics classes with your own devices

Introducing the latest educational technology trends has accelerated enormously in the past few years; therefore, the use of personal devices, especially smart phones, tablets, laptops has increased considerably also in the educational processes. Many researchers used M-learning for different purposes (Hsu & Ching, 2013), but only a few of them used it for physics teaching experiments (Crompton, Burke, Gregory & Gräbe, 2016; Jarosievitz, 2016; Kuhn & Vogt, 2013). The use of M-learning devices in experiments is based on the rich set of built-in sensors in smart phones (Kuhn & Vogt 2013; Staacks, 2016). However, beside the devices themselves, also free applications and teachers’ (instructors’) expertise is required.In this work some meaningful use of M-learning during physics lectures will be presented. Some of the key terms describing the quality of the measurement have also been discussed with the students, and will be presented here. After the conclusion of the measurements, students used their own devices as clickers, and answered the questions synchronously and anonymously through an on-line assessment system.