Academic self-efficacy, academic amotivation, attitude toward the teaching profession, and classroom management anxiety are four of the most significant factors for both teacher training and performance because these psychological and behavioral constructs are first developed during the initial training, and reflect on the actual teaching quality of teachers. Therefore, investigation into their development and relationships, particularly with regard to prospective teachers, is significant both for the theory and practice of teaching. Hence, the current study aims to explore the casual relationships between these variables with a sample of prospective mathematics teachers, using the structural equation modelling (SEM). The participants were selected using simple random sampling method from prospective mathematics teachers studying at educational faculties of seven universities in different regions of Turkey. The data were collected using the academic amotivation scale, academic self-efficacy scale, attitude toward the teaching profession scale, classroom management anxiety scale, and a personal information form developed by the researchers. Data obtained from 581 participants were analyzed using path analysis. The findings showed that prospective mathematics teachers had a positive attitude toward the profession, and were eager to teach. Their academic self-efficacy predicted their attitude toward the teaching profession. Similarly, prospective mathematics teachers’ attitude toward the teaching profession correlated negatively with their academic amotivation. In other words, as prospective mathematics teachers’ attitude scores toward the profession increased, their academic amotivation scores decreased. However, prospective mathematics teachers had a high level of classroom management anxiety. Interestingly, prospective mathematics teachers with a positive attitude toward the profession experienced higher levels of classroom management anxiety. The findings mostly supported previous results in the literature. Implications were suggested both for teacher training and practice of quality teaching.

Digital addiction (DA), an umbrella term referring to addiction to any type of digital media, such as the internet, smartphone, digital games, and social media, is a significant factor influencing students’ academic achievement (AA). Many scholars have contributed to this line of research from around the world. Nevertheless, the literature lacks a holistic investigation of how the DA–AA research field evolved, which could guide future studies. The current study aims to address this void and conducts a combined bibliometric and science mapping analysis of research addressing the relationship between DA and AA. Data were retrieved from the WoS database, considered one of the optimal databases for such studies with its comprehensive coverage of quality journals. One hundred eighteen articles were included in the final dataset and were analyzed using the SciMAT software, which allowed analysis over three consecutive periods and yielded comparable results regarding the conceptual and thematic evolution of the DA–AA domain. The results indicated an increased research interest in the topic, especially during the last five years. The science mapping analysis showed that the most-studied types of addiction were smartphone addiction for the first two periods and social media addiction for the last. Research in the DA–AA domain which focused on understanding the addictive use of smartphones during the first period, evolved to address factors such as self-efficacy or life satisfaction leading to smartphone addiction and lower grades. During the third period, the number of factors addressed gained significant variety and covered family-related and personal factors.

The current study uses “digital addiction” as an umbrella term to refer to addiction to the Internet, social media, smartphones, digital devices, video games, or similar digital technologies. The study aims to investigate the scientific landscape of the digital addiction research field through combining bibliometric and science mapping analysis and to facilitate insight into the development and evolution of this knowledge base. Data for the analysis were extracted from the Scopus database, which covers a wide range of journal articles, with 429 articles addressing digital addiction included in the analysis. The science mapping analysis was performed over three consecutive time periods using SciMAT software to observe the thematic evolution. The results indicated that addictive behavior was the most significant theme across the three time periods. Cross-sectional studies addressing the risk factors or outcomes of addiction among adults and different sexes were prevalent during the first period (1997–2012), while interest moved to the addictive behavior of adolescents and students during the second period (2013–2017). Research during the third period (2018–2022) was driven by smartphone and social media addiction, and resilience as a preventive factor garnered more research interest than previously studied risk factors, which may indicate a perspective change by researchers. Implications are suggested for future investigations of digital addiction.

Artificial intelligence (AI) is one of the ground-breaking innovations of the 21st century that has accelerated the digitalization of societies. ChatGPT is a newer form of AI-based large language model that can generate complex texts that are almost indistinguishable from human-generated text. It has already garnered substantial interest from people due to its potential utility in a variety of contexts. The current study was conducted to evaluate the utility of ChatGPT in generating accurate, clear, concise, and unbiased information that could support a scientific research process. To achieve this purpose, we initiated queries on both versions of ChatGPT regarding digital school leadership and teachers’ technology integration, two significant topics currently discussed in educational literature, under four categories: (1) the definition of digital leadership, (2) the digital leadership skills of school principals, (3) the factors affecting teachers’ technology integration, and (4) the impact of digital leadership on teachers’ technology integration. Next, we performed a comparative analysis of the responses generated by ChatGPT-3.5 and ChatGPT-4. The results showed that both versions were capable of providing satisfactory information compatible with the relevant literature. However, ChatGPT-4 provided more comprehensive and categorical information as compared to ChatGPT-3.5, which produced responses that were more superficial and short-cut. Although the results are promising in aiding the research process with AI-based technologies, we should also caution that, in their current form, these tools are still in their infancy, and there is a long way to go before they become fully capable of supporting scientific work. Meanwhile, it is significant that researchers continue to develop the relevant knowledge base to support the responsible, safe, and ethical integration of these technologies into the process of scientific knowledge creation, as Pandora’s box has already been opened, releasing newer opportunities and risks to be tackled.

Transformational leadership has been persistently studied in the educational administration field considering that it can be a viable tool to respond to the increasing demands on school systems for greater effectiveness. As a result, a rich knowledge base has been accumulated. Our study aims to investigate this knowledge base by combining bibliometric and science mapping analysis so as to exhibit its intellectual and conceptual architecture, and to reveal the strategic themes that emerged during the scientific evolution of transformational school leadership (TSL). 300 articles retrieved from the Scopus database were included in the analysis. The thematic evolution analysis was performed using the SciMAT software over three time periods: the Incubation Period (1989–2009), the Development Period (2010–2020), and the Maturation Period (2021–2022). The findings show that research during the Incubation Period mostly attempted to conceptualize TSL while it mostly focused on principals, instructional leadership, and self-efficacy during the Development Period. The mentoring theme emerged during the first period but disappeared later without being fully-developed. Teacher leadership emerged as a weakly-addressed theme during all periods. Work-family conflict and digital competencies were the two prominent themes during the Maturation Period while online learning and learning culture were found to be the emerging themes. The findings suggest significant implications for the sustainable development of the TSL research field.