The implementation of mobile learning seems to be an emerging topic in many educational institutions. As recently noticed, mobile technology has employed wireless technologies to communicate, think, learn, and share in order to spread and exchange information. Therefore, using mobile technologies in learning and teaching can create a positive environment in higher education. Hence, the purpose of this study is to evaluate mobile learning engagement among educational technology students. Data from three focus group discussions and 15 semi-structured interviews with students who experienced mobile learning were gathered using a qualitative approach design. A total of seventeen basic themes and four organizing themes were extracted, where the researchers categories of engagement, i.e., social engagement, cognitive engagement, emotional engagement, and behavioral engagement. In the present research, the findings indicate that social engagement themes included social–mobile interaction, building community, developing relationships, and competition. The cognitive engagement themes included attention, cognitive and meta-cognitive strategies, immersion, and cognitive curiosity. Emotional engagement themes included excitement and enjoyment, instructor comforting students, motivation, and emotional safety. Behavioral engagement themes included effort and time on task, attendance, participation, and positive conduct.

Artificial Intelligence (AI) is increasingly prevalent, permeating various aspects of and spreading across education. However, a comprehensive understanding of AI applications and how to define AI literacy is under-investigated. On this note, teaching and evaluating AI literacy necessitating educators to integrate it in course content. The implementation and utilization of AI are reshaping college students’ experiences mannerly. A limited efforts have been made to promote artificial intelligence (AI) literacy for individuals at academic institutions. This study aims to investigate college instructors’ perspectives towards AI integration in curriculum design at a higher education institution, Palestine technical university Kadoorie (PTUK). A mixed study approach is utilized with a pre-existing questionnaire containing 14 items in this study and 17 semi-structured interviews. The data were collected from nine different departments at PTUK. The target population consisted of college 176. The results revealed that college instructors are perceiving AI literacy at a weak degree in the curriculum. Three themes merged from qualitative data: positive perspectives, negative perspectives, and willingness of integration of AI literacy across the curriculum. Recommendations include: there is a necessity to incorporate AI literacy curriculum design and in higher education context in different disciplines.

Introduction: Fostering Artificial Intelligence (AI) literacy and equipping college students with 21^st-century skills in the generative AI era have become a global educational priority. In this context, generative AI offers opportunities for development in higher education institutions. Thus, this study investigates the influence of AI literacy and 21^st-century skills on generative AI acceptance.Methods: For data collection, the study employed a quantitative design with three scales, and the study sample included 260 college students selected randomly.Results: Results revealed that AI literacy and 21^st-century skills are present at a moderate level among college students. AI literacy and 21^st-century skills influence the generative AI Acceptance level.Discussion: Based on the results, the study recommends enriching the curriculum with AI literacy and equipping students with 21^st-century skills while using generative AI applications.

As technology has explosively and globally revolutionized the teaching and learning processes at educational institutions, enormous and innovative technological developments, along with their tools and applications, have recently invaded the education system. Using mobile learning (m-learning) employs wireless technologies for thinking, communicating, learning, and sharing to disseminate and exchange knowledge. Consequently, assessing the learning attitudes of students toward mobile learning is crucial, as learning attitudes impact their motivation, performance, and beliefs about mobile learning. However, mobile learning seems under-researched and may require additional efforts from researchers, especially in the context of the Middle East. Hence, this study’s contribution is enhancing our knowledge about students’ attitudes towards mobile-based learning. Therefore, the study goal was to investigate m-learning’s effect on the learning attitudes among technology education students. An explanatory sequential mixed approach was utilized to examine the attitudes of 50 students who took an educational technology class. A quasi-experiment was conducted and a phenomenological approach was adopted. Data from the experimental group and the control group were gathered. Focus group discussions with three groups and 25 semi-structured interviews were performed with students who experienced m-learning in their course. ANCOVA was conducted and revealed the impact of m-learning on the attitudes and their components. An inductive and deductive content analysis was conducted. Eleven subthemes stemmed out of three main themes. These subthemes included: personalized learning, visualization of learning motivation, less learning frustration, enhancing participation, learning on familiar devices, and social interaction, which emerged from the data. The researchers recommended that higher education institutions adhere to a set of guiding principles when creating m-learning policies. Additionally, they should customize the m-learning environment with higher levels of interactivity to meet students’ needs and learning styles to improve their attitudes towards m-learning.

The COVID-19 crisis affected the world globally in 2020 and caused school clo-sure around the world, which promptly embraced online learning and raised ethi-cal awareness for teachers and students. Online learning that is based on continu-ously gaining relevance in educational institutions, is challenged by lack of doc-umented ethics that maintain rights and encourage applying online learning. Un-fortunately, online learning ethics are still obscure at this moment. This study aims to propose online code of ethics for Palestinian schools. Applying the mixed methods approach: A focus group with teachers and a questionnaire that was built to explore the teachers’ degree of agreement on the proposed online learning ethics. The code was finally being evaluated by online learning experts who have extensive expertise in the field. Results revealed principles of online learning eth-ics that were highly accepted by school teachers. The researchers recommended conducting future research on the impact of this code on learning and teaching.

Introduction: This study aims to investigate AI potentials, ethical use, and challenges at PTUK.Methods: A mixed approach is utilized in this study to examine the perceptions of college instructors from different disciplines. A pre-existing scale of attitudes toward the ethics of artificial intelligence (AT-EAI) was used to assess the attitudes of 88 college instructor towards ethical use of AI. A phenomenological approach as well was conducted to gather information for the qualitative data. Semi-structured interviews with 17 participants were performed with college instructors who use AI in their teaching. One sample t-test was utilized to investigate the attitudes towards ethical use.Results: Results revealed that justice, transparency, determination and no maleficence, and responsibility are statistically significant at a moderate level. Privacy was found at a moderate degree. Qualitative analysis yielded three themes for potential: academic productivity, accessibility, and multimodal teaching. Three themes for challenges: Ai quality services, lack of interaction, and need for teaching philosophy adaptation.Discussion: The researcher recommendsthat further research and collaboration are necessary to maximize the benefits of AI in education and ensure its seamless integration into teaching practices.