This study addresses the effectiveness of learning via educational software. Recent decades have seen the integration of technologies, which are changing teaching and transforming teachers into mediating, facilitating, and guiding figures by means of digital learning methods that serve as a major tool in schools, colleges, and universities. The current study focuses on instruction provided within the Israeli Air Force and examined the effectiveness of instruction provided via educational software in terms of learning products: Bloom’s revised taxonomy, Te’eni’s affective-cognitive model of organizational communication and the STEM model. We randomly divided the learners into three groups who studied the same topic: one group studied with the educational software only, the second with the educational software together with an instructor, and the third with an instructor who used a presentation. The learners took a test and four months later they took another test to examine the effectiveness of the instruction over time. The research results show that the recall levels and performance levels on the tests were almost identical in all groups, but in the categories of understanding and applying the addition of an instructor strongly contributed to achievements: Those who received instruction via educational software achieved the best results in the understanding category, while those who studied with an instructor who used a presentation achieved the best results on the test with regard to application of the studied material. The findings of this study can illuminate the effectiveness of using educational software in learning processes in all educational systems.

The increasing sophisticated learning technology and COVID-19 have pushed the teaching-learning process to use pedagogy, andragogy, and cybergogy approaches. The current research aims to investigate the relationship between the practices of these three approaches and student self-regulated learning. The structural equation model used indicates that pedagogy practices may affect the andragogy practices in teaching-learning process. Pedagogy approach shows no direct effect but has an indirect effect on students’ self-regulated learning. The indirect effect comes from the pedagogy-andragogy continuum and the impact of pedagogy instruction on cybergogy practices. Andragogy practices also gives a significant impact on students’ self-regulated learning and how the students use learning technology in cybergogy approach. Andragogy and the continuum of cybergogy promote students’ self-regulated learning. These results indicate that pedagogy-andragogy continuum can have an interplay with cybergogy. The interplay of these approaches may encourage students’ self-regulated learning. The current research can be a baseline to construct a new approach in teaching-learning process and its instructions in the classroom.

The purpose of the current study was to analyze social media content related to physical education. In the context of summative qualitative content analysis, I took advantage of big data analytics to access the data. Machine learning of this big data mapped the large content volume from four major social media platforms. The data was collected by extracting social media posts from January to December 2020. The big data analysis process sorted, categorized, and classified the enormous data into several preeminent topics regarding PE. These computerized analyzes were used to identify themes that were further analyzed using qualitative methods. The results revealed two overarching themes. These themes were (a) PE representation as a school subject and (b) the images of PE teachers on social media. The second theme consisted of three subthemes: masculine traits of PE teachers and negative and positive sentiments toward these teachers. I concluded that key aspects of PE discourse in virtually mediated reality share topical characteristics with what people have previously socially constructed. However, the themes offer a new addition to the literature in that the analysis offers a new perspective on ongoing debates about the social construction of PE through enormous large data sets.