Artificial intelligence has evolved enormously over the last two decades, becoming mainstream in different scientific domains including education, where so far, it is mainly utilized to enhance administrative and intelligent tutoring systems’ services and academic support. ChatGPT, an artificial intelligence-based chatbot, developed by OpenAI and released in November 2022, has rapidly gained attention from the entire international community for its impressive performance in generating comprehensive, systematic, and informative human-like responses to user input through natural language processing. Inevitably, it has also rapidly posed several challenges, opportunities, and potential issues and concerns raised regarding its use across various scientific disciplines. This paper aims to discuss the legal and ethical implications arising from this new technology, identify potential use cases, and enrich our understanding of Generative AI, such as ChatGPT, and its capabilities in education. The paper is part of the Proceedings of the 1st International Conference of the Network of Learning and Teaching Centers in Greece: Transforming Higher Education Teaching Practice

Worldwide, the detection of epidemics has been recognized as a continuing problem of crucial importance to public health surveillance. Various approaches for detecting and quantifying epidemics of infectious diseases in the recent literature are directly influenced by methods of Statistical Process Control (SPC). However, implementing SPC quality tools directly to the general health care monitoring problem, in a similar manner as in industrial quality control, is not feasible since many assumptions such as stationarity, known asymptotic distribution etc. are not met. Toward this end, in this paper, some of the open statistical research issues involved in this field are discussed, and a distribution-free control charting technique based on change-point analysis is applied and evaluated for detection of epidemics. The main tool in this methodology is the detection of unusual trends, in the sense that the beginning of an unusual trend marks a switch from a control state to an epidemic state. The in-control and out-of-control performance of the adapted control scheme from SPC is thoroughly investigated using Monte Carlo simulations, and the applied scheme is found to outperform its parametric and nonparametric competitors in many cases. Moreover, the empirical comparative study provides evidence that the adapted change-point detection scheme has several appealing properties compared to the current practice for detection of epidemics.

The impact of COVID-19 and the associated lockdown measures on people’s physical and mental wellbeing, as well as their daily lives and functioning, has been extensively studied. This study takes the approach of investigating the consequences of COVID-19 on a national scale, considering sociodemographic factors. The main objective is to make a contribution to ongoing research by specifically examining how age, gender, and marital status influence the overall impact of COVID-19 and wellbeing indicators during the second lockdown period that was implemented in response to the COVID-19 pandemic in the Greek population. The study involved a sample of 16,906 individuals of all age groups in Greece who completed an online questionnaire encompassing measurements related to personal wellbeing, the presence and search for meaning in life, positive relationships, as well as symptoms of depression, anxiety, and stress. Additionally, to gauge the levels of the perceived COVID-19-related impact, a valid and reliable scale was developed. The results reveal that a higher perception of COVID-19 consequences is positively associated with psychological symptoms and the search for meaning in life, while being negatively correlated with personal wellbeing and the sense of meaning in life. In terms of individual differences, the findings indicate that unmarried individuals, young adults, and females tend to report higher levels of psychological symptoms, a greater search for meaning in life, and a heightened perception of COVID-19-related impact. These findings are analyzed in depth, and suggestions for potential directions for future research are put forth.

Change-point analysis is the task of finding abrupt (and significant) changes in the underlying model of a signal or time series. Change-point detection methods typically involve specifying the maximum number of segments to search for and the minimum segment length. However, there is no objective way to pre-specify these two parameters, and it mostly depends upon the particular application. Within this framework, a recursive optimization algorithm is developed that is capable of exploring and fine tuning these two input parameters, and optimally segmenting a time series. This multiple change-point detection technique therefore addresses a wide class of real-life contexts and problems where the identification of optimal level shifts in a time series is the main goal. Extensive simulation results are presented and a real-life example is given to illustrate the implementation of the developed scheme in practice and to unfold its capabilities. Concluding remarks and suggestions for future research are also provided.

Artificial intelligence has evolved enormously over the last two decades, becoming mainstream in different scientific domains including education, where so far, it is mainly utilized to enhance administrative and intelligent tutoring systems services and academic support. ChatGPT, an artificial intelligence-based chatbot, developed by OpenAI and released in November 2022, has rapidly gained attention from the entire international community for its impressive performance in generating comprehensive, systematic, and informative human-like responses to user input through natural language processing. Inevitably, it has also rapidly posed several challenges, opportunities, and potential issues and concerns raised regarding its use across various scientific disciplines. This paper aims to discuss the legal and ethical implications arising from this new technology, identify potential use cases, and enrich our understanding of Generative AI, such as ChatGPT, and its capabilities in education.