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.

Students in mathematics classes do not understand the importance of sociomathematical norms in learning mathematics. This causes sociomathematical norms not to be teachers' focus when learning mathematics. Besides, there is no standardized instrument for assessing this norm, so developing this instrument is necessary to measure socio-mathematical norms in learning mathematics. This study aims to create and verify the psychometric validity of the sociomathematical norm scale. This research used a survey method with 505 senior high school students from Jakarta and West Java as respondents. The results showed that 25 items had convergent validity, with a loading factor value of > 0.700, meaning they could be declared valid. Concurrent validity indicates that each sociomathematical norms indicator is valid as a whole. Discriminant validity shows that the average variance extracted value on the diagonal is higher than the other values, so each item is declared valid. It was concluded that each item of the sociomathematical norms instrument has accuracy in its measurement function. The reliability test shows that each sociomathematical norms item is declared reliable. The reliability value of the sociomathematical norm item is .99, and the person's reliability is .86. Thus, the instruments developed can measure sociomathematical norms in learning mathematics.

This study arises from the need to scientifically investigate how university students deal with their emotions in school situations. Therefore, the objective was to develop an instrument that measured university students' level of emotional regulation during academic activities and evaluate its validity and reliability. After a thorough literature review of the definitions of the constructs, the Emotional Regulation Scale in Academic Activities (ERAAS) was developed. The first version of ERAAS consisted of 18 Likert-type items. A total of 1975 university students in various departments responded to the instrument. Two groups of experts evaluated its content validity. Validity and reliability analysis was performed. According to the EFA, three factors were found: emotional regulation, psychologic inadequate emotional regulation, and physiological insufficient emotional regulation. The final version of the scale consisted of 11 items, the validity and reliability of which could be demonstrated for further research purposes.

Situational interest is an important factor that has a great influence on learning success in both in-school and out-of-school learning situations. Although there has been extensive research on interest in its diverse forms for decades, an evaluated measurement instrument for situational interest that covers the three theoretically defined components of interest (emotional, cognitive, value-related) is still missing. Therefore, in this study, based on person-object theory of interest, a short scale was developed that can be used in a variety of learning programs independent of content or methods. In study 1, eight suitable items were selected and their structure was examined using exploratory methods. In study 2, the results of study 1 were verified using confirmatory factor analyses. Study 3 shows an example of a practical application of the newly developed scale in two different learning settings. The findings provide evidence that the scale developed here is a practical instrument to measure situational interest taking into account all its components. On the one hand, the scale can help teachers evaluate their educational programs; on the other hand, it can be used by researchers to empirically investigate the construct of interest. Thus, the scale makes an important contribution to research and practice.

The present study explores the Quality of Life (QoL) of young people with intellectual disabilities engaged in a social farming initiative, known as ‘‘Tuttincampo: Social Farming and Inclusivity’’. The project stands as an innovative approach to improving social inclusion and providing vocational education and training. The initiative seeks to offer a viable alternative to traditional rehabilitation day centers by establishing a network of both public and private institutions. To explore the QoL of the young people we analyze data from the Personal Outcome Scale (POS), a tool that investigates the perception of QoL through self-assessment and hetero-assessment. Data were collected at the beginning and at the end of the social agriculture project. The results obtained confirm the importance of planning pedagogical actions to support social inclusion and vocational training for people with intellectual disabilities, highlighting, as well, the potential of social farming as a new “space” to achieve a higher level of QoL.

In an era where diversity and digitalization significantly influence higher education, understanding and adapting to various learning preferences is crucial. This study comprehensively analyzes 394 scholarly articles from 1984 to 2022 using bibliometric methods, providing a dynamic overview of the research patterns in learning styles within higher education. We identified four stages of development during this period: 1984–1995 (Low-interest), 1996–2005 (Early development), 2006–2018 (Development), and 2019–2022 (Intensification). Our analysis highlights that the United States, the United Kingdom, and Australia were the top three leading publishers of research on learning styles in higher education. The results reveal three main topics of publications: educational technology, learning environments, and subject behaviors. This research not only identifies emerging research topics but also underscores the importance of adapting instructional strategies to diverse learning styles to enhance educational outcomes in higher education.

The wide use of the Internet of Things (IoT) in all spheres of life has led to a surge of cyberbullying among learners worldwide. That is why it cannot be denied that underlying factors, manifestations, consequences, and preventive measures of cyberbullying improve the welfare and overall mental development of students. This systematic literature review examines the causes, effects, and preventive measures of cyberbullying based on empirical studies conducted on learners in various situations. The review will focus on existing material published between 2015 and April 2024. For the inclusion and exclusion of literature, the Scopus online database was employed, along with the guidelines of the PRISMA model. Of 1004 studies, 51 were closely reviewed to determine the responses to the objectives of this study. NVIVO-12 was used for both thematic and content analysis in this study. The results show that there are 29 causes, 12 forms, 31 effects, and 41 different preventives for cyberbullying. The results of this study will not only enhance the comprehension of various concerns for parents, guardians, policymakers, educators, and governments but also provide valuable insights to researchers for addressing this issue.

School dropout intention and reduced academic achievement are two crucial indicators of school dropout risk. Past studies have shown that school performance plays a mediating role in the models explaining dropout intentions. School burnout and test anxiety have been identified as predictors of both academic performance and school dropout. However, their combined effects on the intention to leave school have not yet been investigated. We aimed to address this gap by exploring the predictors of school dropout intention in a sample of 205 French secondary school students. Structural equation modelling analyses have revealed the specific facets of school burnout (devaluation) and test anxiety (cognitive interference) that explained the school dropout intentions and academic performance. Grade Point Average (GPA) was a mediator of the effects of these variables on the intention to drop out of school. The findings highlight the need to acknowledge assessments as a school stress factor that could contribute to health problems and intentions to drop out of school.