ABSTRACT: Over the last two decades, discussions, rhetoric, recommendations have proposed numerous suggestions for the integrated STEM approach. Different approaches are based on different “interpretations” of the nature of integration, epistemological approaches and the implementation of didactic models to include engineering design. New aspects like artificial intelligence and mixed reality included in this volume can serve as STEM practices in alignment with the 21^st century skills.

ABSTRACT: The aim of this research is to suggest a didactic approach as to how students comprehend the growth and the activities of the two most well-known Ancient Greek civilizations (i.e. the Mycenaean and the Cycladic). The teaching approach is based on STEM perspective, the use of several digital technologies, as well as several learning theories. Digital technologies help students delve into the process of scientific discovery. The degree of new technology and STEM – based didactic approach appealing to students is evaluated through questionnaires. In particular, in our survey, 115 students participated and the questionnaires distributed to four schools of Volos and Veria Greece region. The Research was carried out with the consensus of their parents. According to our results, students expressed great interest in STEM activities that they were exposed to. Moreover, they expressed high interest in the integration of a classic history lesson with new technologies and they developed the ability to create simulations of ancient civilization activities. Furthermore, our work is focusing on issues regarding the process and efficiency, through the use, of an interactive time – line robotic car, which will be used to categorize historical events into periods on a timeline.

ABSTRACT: This research aims in shedding light on international high school students’ perceptions, awareness, and prior knowledge about Artificial Intelligence and Machine Learning, as well as to investigate the effect of taking a relevant learning unit within a STEAM course on students’ dispositions toward and understanding about Artificial intelligence. The analysis of performance and reflection data from 62 individuals revealed low prior student engagement with Artificial Intelligence and Machine Learning content, a positive shift in the anticipated societal impact of Artificial Intelligence and an active engagement with online Artificial Intelligence applications during the unit, as well as no correlation between student performance and gender. It is suggested that the development and implementation of learning designs that focus on conceptual understanding of Artificial Intelligence and Machine Learning could benefit all students.

ABSTRACT: The aim of this study was to adapt ‘Biology Attitude Questionnaire’ (Prokop, Tuncer, & Chudá, 2007) into Turkish. Participants were 242 high school students from Ankara, Turkey. Exploratory and confirmatory factor analysis were performed in order to determine the structural validity of the six dimensional scale. As a result, the final structure of the scale was found to be consisting of three factors and 22 items. The Alpha coefficients of the three factors were found to be 0.882 for the first factor- importance of biology, 0.854 for the second factor- progress of biology lessons and 0.828 for the third factor- interest toward biology.