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Intro: In this survey the academic performance of primary and secondary school students in Greece, for three consecutive school years, was examined. The data concerned all Greek students of the last two grades of elementary school and the three grades of junior high school. Method: Unsupervised learning methods such as an X-means algorithm in combination with descriptive and inductive statistical methods were used, in order to examine students' performance levels. The longitudinal stability of academic performance levels and the influence of demographic characteristics such as the region, gender and guardians' profession were also examined. Results: The existence of four levels of academic performance and longitudinal stability of frequencies per performance level was confirmed. There was also statistically significant differentiation based on the profession of guardian, gender, and area of residence. Discussion: The results demonstrated specific challenges that the educational policy of the country has to address. The stability of the percentages of students in the four groups of academic performance that emerged over time, shows corresponding stability in the factors that affect academic performance. A gradual reduction in the performance of students in high School was found, as the level of difficulty of the courses increases from class to class. Some demographic characteristics of students are not independent of their performance. However, due to the compliance with the general regulation of personal data, there was no access to additional features that may be related to performance, such as nationality and exact place of residence.

In compliance with national legislation, Greek tertiary education institutions assess educational quality often using a standardized anonymous questionnaire completed by students. This questionnaire aims to independently evaluate various course components, including content organization, instructor quality, facilities, infrastructure, and grading methods. Despite widespread use across universities, the questionnaire's validity remains unexamined. This study addresses this gap by analyzing 48,000+ questionnaire responses from the University of the Peloponnese (2014–2022), encompassing 68 undergraduate and graduate programs. Confirmatory factor analyses were used to assess the quality of the questionnaire, while exploratory factor analyses were used to assess the dimensions of the tool based on the data. Both analyses reveal shortcomings: confirmatory analysis detects strong correlations between supposedly different factors, and exploratory analysis identifies dimensions inconsistent with the expected structure. These findings question the questionnaire's quality and the validity of drawn conclusions, while additionally identifying opportunities for reducing the number of questions, which can contribute to increased questionnaire submission rates. Given its common use across Greek universities and its influence on shaping courses, urgent redesigning of the questionnaire for tertiary education evaluation is recommended. [ABSTRACT FROM AUTHOR]

Digital assistants—such as chatbots—facilitate the interaction between persons and machines and are increasingly used in web pages of enterprises and organizations. This paper presents a methodology for the creation of chatbots that offer access to museum information. The paper introduces an information model that is offered through the chatbot, which subsequently maps the museum's modeled information to structures of DialogFlow, Google's chatbot engine. Means for automating the chatbot generation process are also presented. The evaluation of the methodology is illustrated through the application of a real case, wherein we developed a chatbot for the Archaeological Museum of Tripolis, Greece. [ABSTRACT FROM AUTHOR]

Intro: In this survey the academic performance of primary and secondary school students in Greece, for three consecutive school years, was examined. The data concerned all Greek students of the last two grades of elementary school and the three grades of junior high school. Method: Unsupervised learning methods such as an X-means algorithm in combination with descriptive and inductive statistical methods were used, in order to examine students' performance levels. The longitudinal stability of academic performance levels and the influence of demographic characteristics such as the region, gender and guardians' profession were also examined. Results: The existence of four levels of academic performance and longitudinal stability of frequencies per performance level was confirmed. There was also statistically significant differentiation based on the profession of guardian, gender, and area of residence. Discussion: The results demonstrated specific challenges that the educational policy of the country has to address. The stability of the percentages of students in the four groups of academic performance that emerged over time, shows corresponding stability in the factors that affect academic performance. A gradual reduction in the performance of students in high School was found, as the level of difficulty of the courses increases from class to class. Some demographic characteristics of students are not independent of their performance. However, due to the compliance with the general regulation of personal data, there was no access to additional features that may be related to performance, such as nationality and exact place of residence. [ABSTRACT FROM AUTHOR]