The current offer of training courses for university teachers is due, among other needs, to the implementation of an educational model based on student learning, promoting the use of active methodologies for their motivation and academic performance. An exploratory-descriptive and ideographic study is presented where the main technique is the analysis of content. To this end, 15 Spanish universities with the greatest prestige were analyzed according to the parameters of the Academic Ranking of World Universities (ARWU) in relation to the topics related to active methodologies and the profile of university teachers. The results show the different teacher training courses that have been carried out during the 2019/2020 academic year. We find that there are more universities that present more training of this type than others, and who this type of training is aimed at: new teachers and teachers with professional experience. The conclusions are related to the importance of the courses for the professional development of university teachers, since they should not be anchored in the same methodology, but should be open to new challenges and always taking into account the students, enhancing their motivation and academic performance.

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.

Online learning is an obligation in teaching and learning activities during the Coronavirus disease (COVID-19). Game-based learning is a solution in improving student learning outcomes. This research aims to determine the level of acceptance of gamification in terms of Gamification quality (GQ), instructor characteristic (IC), and technology anxiety (TA). The target respondents were students taking information systems courses based on enterprises resources planning (ERP) Gamification. The sample used is a census. That is, the entire population is taken as a sample. A total of 93 students filled out the online questionnaire. Then, data analysis using Structural Equation Model - Partial Least Square (SEM-PLS). Student satisfaction (SS) and perceived ease of use (PEOUG) are the most influences. PEOUG is also the construct that has the most significant relationship impact, especially with the perceived usefulness (PUG). Meanwhile, two constructs do not significantly impact TA on PUG and PUG on Intention to use gamification (INTG). The obligation of students requires students to ignore the impact and function of gamification. The results of this research also show that technology acceptance model (TAM), the constructs IC, TA, and GQ have a positive effect on PEOUG. Then PUG and PEOUG can positively affect SS.

Academic failure and school dropout, or early school leaving, are two of the situations that most concern countries and educational institutions worldwide, because of their prevalence and also their economic and social implications. Despite this prominent role that academic failure and school dropout have in societies, there seems to be no consensus on the literature on their conceptualization, definition, and relationship. Moreover, it is frequent to observe how both concepts are confused or overlap in the scientific literature and how many authors avoid defining these constructs, using them indistinctly. Therefore, this work analyses whether educational research considers them as two different concepts or if they are used indistinctly. For this purpose, 2,051 keywords from 450 articles were subjected to a systematic review and classified into the Education Resources Information Center (ERIC) thesaurus´ descriptors. The results reveal statistically significant differences in the descriptors according to the type of paper to which they correspond (academic failure or dropout). Thus, academic failure is associated with sociocultural, personal, and academic factors, while dropout is linked to employment and educational trajectories. These differences evidence that, although academic failure and school dropout refer to closely related educational problems, there are remarkable differences between them and between the treatment given to each of them in the scientific literature. Therefore, they should be considered as two different concepts. For all this, keyword analysis has proved to be a relevant element for the study of the structure of knowledge, allowing to clearly establish the differences between the two closely related concepts.

By the spread of COVID-19, the entire world shifted suddenly to e-learning including schools. This study aims to find ways to enjoy teaching. Gamification in education refers to the introduction of game elements in non-game environment. A case study was adopted for this study as a qualitative approach to investigate the possibility of improving motivation. The study was conducted in the first and second semester of the 2020/2021. The sample consists of (6) participants of pre-services teachers studying in special education course for 15 weeks. Data were collected through semi-structured interviews. The result of the interview showed that there is a clear desire among the students to succeed during learning using game elements. Their desire is very clear and higher. Most of them became active during their learning. They enjoyed learning in gamified learning environment. The researchers recommended that the Ministry of Education should train teachers to employ game elements to motivate their students.

This study aimed to explore the implementation and impact of the Flipped Learning Model (FLM) and STEM Approach in elementary education. The advancement of technology and the Covid-19 pandemic has increased the importance of e-learning, including in elementary schools. The literature review analyzed 193 academic works published in the past six years using NVivo, Mendeley, and VOSviewer software. The validity of the data was verified through the analysis of five online databases. The results showed that STEM research has been well-developed with innovative approaches that improve learning outcomes, while FLM research in elementary schools is limited. The study suggested that combining FLM with STEM Approach (FLM-SA) can optimize learning in the technological era. By integrating FLM-SA, students can engage in active learning experiences in class and acquire fundamental knowledge outside of class, offering a solution to e-learning challenges. The study emphasized the strong connection between FLM and STEM Approach and how they can support each other to enhance student learning.

Online learning has become increasingly popular, making the learning process more attractive. One of the most popular learning media is artificial intelligence (AI). However, students do not accept this technology at all. Therefore, this study examined the factors influencing accounting students' acceptance of AI in learning. The survey was conducted with 147 higher-education students who use AI as a learning medium. The data were analyzed using SmartPLS 4.0 with the partial least square approach. The results showed that perceived usefulness influenced behavioral intention to use and satisfaction. However, perceived ease of use was only significant for satisfaction. Similarly, perceived confidence must be consistent with intention. Although it may influence perceived usefulness, other constructs, such as AI quality and personal innovativeness, can increase students' perceptions of the benefits and convenience of adopting AI in learning. Thus, this study contributes to the development of the technology acceptance model (TAM) and the information systems success model and is helpful to scholars, especially in applying AI in learning. They need to pay attention to the quality of AI, such as the accuracy of the information produced. Thus, the need to control the information from the AI only serves as a reference without requiring you to trust it completely.

One of the ways to enhance and improve the quality of learning delivery is through the use of technology, particularly the Internet, which facilitates faster and easier access to information. This research aims to explore the degree to which factors such as digital literacy, metacognitive awareness, meaningful learning, habits of using smartphones, and personal learning competence are related to one another. Both the relationship between metacognitive awareness and personal learning competence, as well as the relationship between smartphone habits and personal learning competence, are moderated by a moderating variable known as the fear of missing out. Fear of missing out is a moderating variable. Structural equation modeling, specifically partial least squares, was employed to analyze data from 597 engineering students. SmartPLS version 4 was the tool used for this analysis. The study found that the moderating variable, fear of missing out, significantly impacts metacognitive awareness, learning personal competence, and smartphone habits, making it a crucial factor to investigate. This result is significant because it is a variable that influences the learning that students go through for their education and because it is an extremely important thing to investigate.