Research Article
Stavros Papakonstantinidis, Piotr Kwiatek, Filomachi Spathopoulou
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep495
ABSTRACT
This research investigates the perspectives of using artificial intelligence writing software (AIWS) in professional contexts, focusing on academic and non-academic writers. These two groups, while standing to gain increased productivity through the adoption of AIWS, also express concerns regarding the widespread implementation of this technology. Notably, artificial intelligence (AI) writing tech’s impact on content creation has been profound, with its swift grammatically accurate content generation. This adoption, however, remains controversial. The study employs a quantitative approach, combining technology acceptance model and new computer game attitude scale. This approach allows us to discern implications of using AI-powered writing tools while accounting for possible differences in different domains of use. Through a survey of 219 participants, spanning academia and business, the study explores attitudes and willingness to use AIWS. Findings yield insights into non-academic writers’ readiness and implications of AIWS adoption. Business, non-academic professionals view AIWS as a tool for efficiency and content quality, while writers in academic contexts express concerns about biases, manipulation, and job displacement. The study contributes to AIWS understanding, benefiting developers, educational institutions, and content creators, and elucidates differing attitudes and age dynamics between academics and professionals. The research underscores the multifaceted influence of AIWS, providing a foundation for future exploration in this emerging domain, as well as practical applications for industries and educational institutions.
Keywords: artificial intelligence, chatbots, ChatGPT, education, educational technologies
Research Article
Tobias Alexander Bang Tretow-Fish, Md Saifuddin Khalid
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep496
ABSTRACT
Existing methods for software requirements elicitation, five-point Likert scales and voting methods for requirements prioritization, and usability and user experience evaluation methods do not enable prioritizing the learning analytics dashboard requirements. Inspired by management and product design field, this research applies Kano’s two-factor theory to prioritize the features of learning analytics dashboards (LADs) of adaptive learning platform (ALP) called RhapsodeTM learner, based on students’ perceived usefulness to support designers’ decision-making. Comparing usability and user experience methods for evaluating LAD features, this paper contributes with the protocol and a case applying Kano method for evaluating the perceived importance of the dashboards in ALP. The paper applies Kano’s two-factor questionnaire on the 13 LADs features of RhapsodeTM learner. Responses from 17 students are collected using a questionnaire, which is used to showcase the strength of the two-factor theory through five tabular and graphical techniques. Through these five tabular and graphical techniques, we demonstrate the application and usefulness of the method as designers and management are often carried away by the possibilities of insights instead of actual usefulness. The results revealed a variation in the categorization of LADs depending on the technique employed. As the complexity of the techniques increases, additional factors that indicate data uncertainty are gradually incorporated, clearly highlighting the growing requirement for data. In the case of RhapsodeTM learner platform, results based on the students responses show that 11 of 13 LADs being excluded due to low significance level in categorization (technique 1) and low response rate.
Keywords: adaptive learning platforms, Kano’s two-factor theory, learning analytics dashboard, design methods
Review Article
Kai Hu, Arumugam Raman
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep497
ABSTRACT
This systematic literature review (SLR) explores the integration of e-learning in universities, emphasizing a comprehensive approach that intertwines various mainstream perspectives. Despite numerous studies on e-learning implementation evaluation, few have holistically considered financial, human, technical, and policy factors. This review used PRISMA guidelines and sources from Scopus, Google Scholar, ERIC, SAGE, and ProQuest. Of 26 analyzed studies, seven core themes emerged: Policy, financial, technical, human, institutional factors, others, and an integrated perspective, further distilled into 13 sub-themes. Findings highlight the importance of an integrative framework for evaluating e-learning, underscoring the interplay between macro and institutional policies. Additionally, the authors recommend cross-national comparisons and data synthesis from stakeholders, including students, educators and directors, to fully grasp e-learning implementation dynamics. Distinctively, it adopts an integrated perspective, filling the research gap by emphasizing overlooked financial considerations and presenting a comprehensive view through an SLR. By drawing insights from human, finance, technical, and policy perspective, the study provides a multidimensional lens on e-learning. This forward-looking approach not only captures the current state of e-learning integration but also charts future research directions, establishing its originality and significance in higher education.
Keywords: an integrated perspective, holistic integration of e-learning, systematic literature review, universities
Research Article
Leonardo David Glasserman-Morales, Carolina Alcantar-Nieblas, Marcela Inés Sisto
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep498
ABSTRACT
Nowadays, digital competencies encompass skills and attitudes with technical, informational, content, media, and communication aspects that are crucial for students and future professionals. Hence, there is a need to investigate the possible correlations between demographic and contextual variables and the development of digital competencies in higher education. This paper reports on several university-student demographic factors associated with digital competencies. The work used a quantitative approach with descriptive statistical techniques such as a means test and Pearson correlation analysis. The findings identified that (a) there are statistically significant differences between the mean obtained in the previous semester in digital competencies and the gender of the students, (b) there are no statistically significant differences in the final mean for digital competencies and the students’ institution of origin, and (c) the variables included in the study are statistically significant. They also found that the mean attained by the university students in the previous semester had a strong predictive power of student performance; in contrast, the student’s high school institution of origin variable was a weak predictor of their digital competency. This paper presents the findings and implications for practice and research.
Keywords: digital competencies, higher education, educational innovation, demographic factors, school factors, educational technology
Review Article
Hassan Abuhassna, Mohamad Azrien Bin Mohamed Adnan, Fareed Awae
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep499
ABSTRACT
To enhance education, we conducted a comprehensive investigation into integrating instructional design models (IDMs) and learning theories in this systematic literature review. We methodically selected and analyzed 25 publications from a pool of 1,102 documents using the preferred reportinfg items for systematic reviews and meta-analyses framework to guarantee a rigorous and systematic approach to literature selection. Our results demonstrate the worldwide span of study on this topic, including contributions from prestigious academic institutions and scholarly journals. This examination explores both the benefits and drawbacks of combining IDMs with learning theories. Noteworthy positives include increased student motivation, support for innovative teaching methods, and the development of complex and diverse learning environments. However, several shortcomings were observed. most notably relating to accessibility problems, evaluation difficulties, and questions about the adaptability of such integrated techniques. Our findings have implications for a broad range of stakeholders, including educators, instructional designers, and students functioning in a variety of educational contexts. The increase of learner motivation, the creation of novel pedagogical tools, the refining of teacher training programs, and the promotion of interdisciplinary learning methods are significant areas of focus. In addition, our evaluation uncovered a number of gaps in the current literature, indicating intriguing possibilities for future research. The examination of holistic learning environments, the untapped potential of integrated systems, the incorporation of educational robots into pedagogical tactics, and the refining of schema assessment approaches are notable research fields. By providing these insights, this systematic review not only adds to the current body of knowledge, but also has the potential to shape the future trajectory of educational practices, so acting as a significant resource for boosting learning outcomes in a variety of educational environments.
Keywords: instructional design models, learning theories, systematic literature review, SLR
Research Article
Olga V. Sergeeva, Marina R. Zheltukhina, Zhanna M. Sizova, Alfia M. Ishmuradova, Oleg V. Khlusyanov, Elena P. Kalashnikova
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep500
ABSTRACT
It is essential for pre-service teachers to hold positive beliefs about information and communication technology (ICT) and possess digital skills to integrate digital technology successfully into the teaching and learning environments. Although numerous studies have examined teachers’ attitudes toward ICT, little research has examined teachers’ ICT competency beliefs. This research aimed to explore pre-service teachers’ ICT competence beliefs. We used an instrument developed by previous researchers for data collection. The results showed that the pre-service teachers had good ICT competence beliefs. A few gender differences were found between participants’ mean scores on six dimensions of the data collection instrument. No gender differences were found for many items. It was found that there were no significant differences in the years of study of participants across five different grade levels. However, the lowest mean scores were found in analyzing and reflecting, problem-solving, and information and data literacy. Conversely, the highest mean scores were detected in communication and collaboration, digital content creation, and safety and security. Based on these findings, recommendations have been made for practice and future research.
Keywords: ICT competence beliefs, digital skills, pre-service teachers, information and communication technology, ICT
Research Article
Gulten Genc, Muhammed Nazif Kutlu, Ozge Kirmizibayrak
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep501
ABSTRACT
In recent years, the widespread use of online learning environments and tools, especially with the outbreak of the COVID-19 pandemic, has brought students’ readiness for online learning and their ability to manage their own learning processes to the fore. This study aims to investigate the online learning readiness (OLR) and self-directed learning skills of English language learners at a state university in Turkey. For this purpose, a cross-sectional, descriptive study methodology was employed. The study group consisted of 202 randomly selected first-year volunteer students. An information form and two scales were used to collect data. Additionally, the effects of some demographic factors on EFL students’ OLR and self-directed learning skills were also investigated. The results of the study revealed that university students have a moderate level of self-directed learning and readiness to learn in the online environment. As another result of the study, it was determined that various independent variables had an impact on the participants’ OLR levels. In parallel with the findings of the study, some pedagogical strategies were discussed and suggested.
Keywords: readiness for online learning, self-directed learning, English as a foreign language, higher education, technology in education
Review Article
Yessane Shrrie Nagendhra Rao, Chwen Jen Chen
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep502
ABSTRACT
This bibliometric study on data mining in education synonymous with big educational data utilizes VOSviewer and Harzing’s Publish and Perish to analyze the metadata of 1,439 journal articles found in Scopus from 2010 to 2022. As bibliometric analyses in this field are lacking, this study aims to provide a comprehensive outlook on the current developments and impact of research in this field. This study employs descriptive and trends analysis, co-authorship analysis, co-citation analysis, co-occurrences of keywords, terms map analysis, and analysis of the impact and performance of publications. It also partially replicates a similar study conducted by Wang et al. (2022), who used the Web of Science (WoS) database. The study is reported in an article entitled ‘Big data and data mining in education: A bibliometrics study from 2010 to 2022’. Results show that data mining in education is a growing research field. There is also a significant difference between the publications in Scopus and WoS. The study found several research areas and topics, such as student academic performance prediction, e-learning, machine learning, and innovative data mining techniques, to be the core basis for collaborating and continuing current research in this field. These results highlight the importance of continuing research on data mining in education, guiding future research in tackling educational challenges.
Keywords: educational data mining, big data, education, bibliometric analysis, Scopus
Review Article
Othman Abu Khurma, Fayrouz Albahti, Nagla Ali, Aiman Bustanji
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep503
ABSTRACT
This PRISMA-based literature review aims to assess and analyze the measurement of student engagement dimensions within AI ChatGPT interactions. The central question is how to effectively evaluate these dimensions using established methods and leverage insights to enhance AI ChatGPT’s capacity to foster student engagement. The systematic review of PRISMA methodology identifies 16 relevant peer-reviewed research. All relevant and eligible research according to PRISMA methodology are analyzed to comprehend the intricacies of student engagement in AI ChatGPT interactions. The synthesis of these findings unveils the current state of knowledge on AI ChatGPT’s influence on student engagement and uncovers opportunities for future research. This review underscores AI ChatGPT’s potential as an educational tool, offering personalized experiences that bolster student engagement and learning outcomes. The systematic review established that, even though using ChatGPT has many advantages such as enhancing student engagement and academic involvement and supporting inquiry-based learning. However, there are some negative aspects such as lacking empathy and human emotions, limited contextual understanding, increased technology dependence and possibility of Inaccurate or Biased Information. In summary, this PRISMA-based review contributes to understanding the measurement of student engagement within AI ChatGPT. It identifies best practices, laying the foundation for further research and development. By optimizing AI ChatGPT’s effectiveness, educators and developers can craft more engaging and tailored learning experiences, ultimately enhancing educational outcomes.
Keywords: artificial intelligence, ChatGPT, teaching, learning, student engagement
Research Article
Josef Buchner, Elke Höfler
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep504
ABSTRACT
Fake news is increasingly becoming a major problem for global social coexistence, for example by undermining trust in democracies. There is a consensus that educational institutions need to respond and prepare students to recognize fake news. Teachers have a central role to play in preparing students and therefore need to learn about fake news during their studies. Previous research has shown that games are particularly effective for learning about fake news, but the group of pre-service teachers has not yet been investigated. The aim of this study is to address this gap by examining whether pre-service teachers can learn about fake news using the augmented reality escape game Escape Fake. To investigate this question, a pre-/post-test design was conducted with 45 pre-service teachers (four males, mean age=22.59 years, standard deviation=1.80). The results show that after playing Escape Fake, the pre-service teachers demonstrate significantly higher knowledge about fake news, are significantly more critical towards online information, and are significantly more confident in being able to recognize fake news in the future. However, playing the game did not promote the ability to discern real from false information. The paper discusses reasons for this finding and suggests ways to improve learning with the game. Implications and future research needs are discussed.
Keywords: fake news, fake news education, educational escape game, augmented reality, teacher education, teacher training
Research Article
Asmahan Masry-Herzallah, Abeer Watted
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep505
ABSTRACT
During the COVID-19 outbreak, Israel’s higher education system swiftly transitioned to emergency-adapted online distance learning. Yet, limited research has assessed effectiveness of online learning (EOL) for Arab students in Israel. This study delves into Arab students’ EOL perceptions, focusing on cognitive and emotional aspects. Using a quantitative method, it explored the link between technological self-efficacy (TS), mindfulness ability (MA), and EOL during the pandemic among students from three Israeli academic institutions (N=378). Results showed a positive association between TS and EOL. Further, MA moderated TS-EOL relationship. Men demonstrated higher TS than women. There were noticeable EOL differences between undergraduate (pre-service teachers) and graduate (in-service teachers) students, with the latter exhibiting an advantage. This research contributes to the evolving discourse on post-pandemic online learning, shedding light on potential gender disparities and highlighting the importance of both TS and MA for successful online learning. The findings have implications for instructional designers, educators, policymakers, and academic programs.
Keywords: COVID-19 crisis, online learning effectiveness, technological self-efficacy, gender differences, mindfulness ability
Research Article
Kate Tzu-Ching Chen
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep506
ABSTRACT
This study assessed the readiness and perceptions of 215 secondary school teachers in Taiwan regarding distance English as a foreign language (EFL) learning. Data collection encompassed survey questionnaires, which were refined based on a pilot study. The responses underwent analysis using descriptive statistics, one-way ANOVA, and the Pearson correlation coefficient in the most recent iteration of SPSS. In addition, content analysis was conducted on follow-up interviews. The findings indicated a noteworthy degree of readiness among teachers for distance EFL learning, nonetheless the challenges arising from the abrupt transition to distance education during the COVID-19 pandemic. While teachers exhibited confidence in their ability to navigate EFL distance learning, they also accentuated the necessity for specialized training and institutional support to effectively manage its demands. Despite their preference for traditional in-person classes, teachers acknowledged the importance of ongoing support and training to enhance the quality of instruction in digital EFL learning contexts, emphasizing the need for continuous development in this newly developed teaching trend to align with evolving educational landscapes.
Keywords: distance education and online learning, K-12 education, computer-assisted language learning, English teaching
Research Article
Soonri Choi, Hongjoo Ju, Jeein Kim, Jihoon Song
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep507
ABSTRACT
Computer-supported collaborative learning is an instructional technique to solve complex tasks. One of the key factors to enhance collaboration is increasing the level of interdependence among the collaborators. This study was conducted to examine if the heterogeneous knowledge held by each member promoted by heterogenous instructional sequencings enhances the level of interdependence during collaboration. A quasi-experiment was conducted with college seniors preparing for their careers in a Shinhan University located in Gyeonggi-do, South Korea. The experiment consisted of two phases: one was, where students gained prior knowledge using homogeneous or heterogeneous complex-task sequencing. The other was, where they collaborated with each other using a computer-supported tool. The results showed the statistically significant difference between the two groups in terms of extraneous collective cognitive load, intrinsic motivation, and learning transfer. The collaborative groups of members, which utilized heterogeneous instructional sequencings during the individual learning phase showed relatively lower extraneous collective cognitive load, and higher intrinsic motivation in three consecutive collaborative sessions except for the first. As well as groups of members had higher learning transfer results. Implications and limitations were further discussed on results.
Keywords: collaborative learning, computer-supported collaborative learning, conservation of resource theory, collective cognitive load theory, complex-task instructional sequencings, intrinsic motivation
Review Article
Izida I. Ishmuradova, Alexey A. Chistyakov, Alexey D. Chudnovskiy, Elena V. Grib, Sergey V. Kondrashev, Sergei P. Zhdanov
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep508
ABSTRACT
This study looks closely at research papers about blended learning (BL) from the last 10 years (2014-2023). It pulls information from Scopus and Web of Science (WoS). By using both, it gives a full picture of what is being published and what’s important in BL research. The search found 1,704 articles in Scopus and 1,545 in WoS. After putting them together and removing duplicates, there were 2,455 articles for the study. The study used a Bibliometrix R to look at who published a lot, which countries and schools did most, who worked together, and which articles got mentioned a lot. Each year, the number of articles grew by about 15.58%. Most of these, 93.00%, were articles. Universities in Australia were among those that wrote the most. “Education and Information Technologies” and “International Journal of Educational Technology in Higher Education” were often cited, which shows they have big roles in this research area. Some of the main researchers who connect a lot of the work are Zhu, Graham, and Jackson. It is found that keywords “higher education”, “online learning”, “students”, and “COVID-19” are very common in discussions and help shape the research being done. While much research comes from Australia and the West, there is also growing work from Asia and the Middle East. This shows that BL is becoming important in different parts of the world. But there’s a chance to get more research from less wealthy countries. This study puts together a clear picture of BL research. It looks at what’s been published, who talks to who, and which places are doing the work. The research has grown who the main people are, where there’s a gap between different regions, and what we should think about for the future. This can help make policies and change how we teach.
Keywords: bibliometrics, blended learning, higher education, research impact, knowledge mapping
Research Article
Reginald Gerald Govender
CONT ED TECHNOLOGY, Volume 16, Issue 2, Article No: ep509
ABSTRACT
A new era of artificial intelligence (AI) has begun, which can radically alter how humans interact with and profit from technology. The confluence of chat interfaces with large language models lets humans write a natural language inquiry and receive a natural language response from a machine. This experimental design study tests the capabilities of three popular AI chatbot services referred to as my AI students: Microsoft Bing, Google Bard, and OpenAI ChatGPT on completeness and accuracy. A Likert scale was used to rate completeness and accuracy, respectively, a three-point and five-point. Descriptive statistics and non-parametric tests were used to compare marks and scale ratings. The results show that AI chatbots were awarded a score of 80.0% overall. However, they struggled with answering questions from the higher Bloom’s taxonomic levels. The median completeness was 3.00 with a mean of 2.75 and the median accuracy was 5.00 with a mean of 4.48 across all Bloom’s taxonomy questions (n=128). Overall, the completeness of the solution was rated mostly incomplete due to limited response (76.2%), while accuracy was rated mostly correct (83.3%). In some cases, generative text was found to be verbose and disembodied, lacking perspective and coherency. Microsoft Bing ranked first among the three AI text generative tools in providing correct answers (92.0%). The Kruskal-Wallis test revealed a significant difference in completeness (asymp. sig.=0.037, p<0.05) and accuracy (asymp. sig.=0.006, p<0.05) among the three AI chatbots. A series of Mann and Whitney tests were carried out showing no significance between AI chatbots for completeness (all p-values>0.015 and 0<r<0.2), while a significant difference was found for accuracy between Google Bard and Microsoft Bing (asymp. sig.=0.002, p<0.05, r=0.3 medium effect). The findings suggest that while AI chatbots can generate comprehensive and correct responses, they may have limits when dealing with more complicated cognitive tasks.
Keywords: artificial intelligence, chatbots, generative text, completeness, accuracy