Abdulsalam K. Alhazmi

This chapter explores the transformative role of Artificial Intelligence (AI) in reshaping educational landscapes, emphasizing its applications across teaching, learning, assessment, and research. AI-driven innovations—including adaptive learning platforms, collaborative tools, and intelligent Learning Management Systems (LMS)—enable personalized instruction, real-time feedback, and data-informed classroom management. These technologies optimize content delivery, address diverse learner needs, and empower educators with insights to individualize support. In research, AI enhances methodologies through predictive analytics, machine learning-driven data analysis, and longitudinal studies, uncovering patterns in student performance and enabling proactive interventions. AI also revolutionizes assessment via automated grading, peer evaluation frameworks, and performance-based tools that objectively evaluate soft skills like critical thinking and collaboration.

The integration of AI in education introduces profound ethical and operational challenges, particularly in legal compliance, regulatory frameworks, and institutional accountability. This chapter how AI-driven systems are associates with data privacy laws, intellectual property rights, and evolving regulations governing AI-generated content. It underscores the necessity for institutions to ensure transparency in student consent and align internal policies with legal mandates. The discussion emphasizes institutional accountability in mitigating algorithmic bias, addressing surveillance risks, and bridging gaps in ethical guidelines. Regulatory challenges, including compliance with fragmented global standards and resolving ambiguities in AI deployment, are analyzed alongside the role of institutions in fostering innovation while safeguarding equity and autonomy. By prioritizing legal adherence, regulatory agility, and institutional responsibility, this chapter advocates for frameworks that harmonize AI's potential with ethical imperatives in education.

Generative artificial intelligence (GenAI) is driving a technological revolution, significantly impacting education, with universities as primary beneficiaries. This study explores the varied use of GenAI among university users in Malaysia, examining its challenges and effects across different demographic groups. A mixed-methods approach, including literature review content analysis, and a survey of 290 respondents, was used, analyzed with tools such as SPSS 27, and NVivo. The findings show widespread GenAI use, particularly among younger users (under 25), as revealed by one-way ANOVA testing, which rejected the null hypothesis that age does not affect engagement. No significant gender differences were found, though users with a bachelor’s degree were more engaged than those with higher degrees. The study also found no strong link between the duration of AI experience or weekly usage hours and engagement, although a trend suggests increased usage leads to higher engagement. The study highlights six negative impacts of excessive GenAI use, including weakened interpersonal communication skills, potential declines in academic performance, increased stress from dependency on technology, the undermining of traditional educational methods, encouragement of academic dishonesty, and loss of learning motivation and engagement. To address these issues, the research introduces practical guidelines and recommendations including promoting self-regulation, establishing GenAI policy frameworks, and enhancing AI literacy and community engagement.

Rapid economic developments have led to the excessive consumption of environmental resources. Consumption patterns play a crucial role in deteriorating environmental conditions and influencing consumers to seek sustainability features while purchasing different products. The purpose of this paper was to analyze the sustainability factors that have prompted consumers in Malaysia to buy green products. The primary elements of this research focused on environmental concern, green product awareness, government support, perceived ecological value, community green practice, purchase intention, and green product purchase behavior. Additionally, to explain the relationship between the independent and dependent variables, this research employed the theory of planned behavior as a theoretical framework. A total of 300 questionnaires were collected and examined using smart PLS-SEM. The findings of the research suggest that all factors, including environmental concern, green product awareness, government support, perceived ecological value, community green practice, and purchase intention, influence consumers in Malaysia to purchase green products. Finally, this research discusses the contribution, limitations, and suggestions for future studies related to purchasing behavior towards green products.

The COVID-19 pandemic has forced many organizations around the world to make full use of a variety of emerging online communication platform technologies. Universities are among the organizations that have asked students, tutors, and lecturers to use a number of different online communication platforms to ensure the education process remains uninterrupted. However, the COVID-19 pandemic has generated considerable challenges for the global higher education community while using such emerging technologies. This research has two main goals. First, this paper will begin by investigating whether the online learning platforms used by university students during the COVID-19 period have presented any challenges to their learning. Second, the paper will then go on to address proposed solutions by developing a conceptual model to reduce the impact of such challenges. This research uses an exploratory qualitative research approach, supported by literature content analysis techniques. The data set for this study was collected during the first peak of the pandemic period in Malaysia, between the 16th of May 2020 and the 5th of June 2020. We used SPSS to conduct a descriptive analysis and NVivo12 to analyse data collected from 486 students from different universities in Malaysia. These students disclosed various obstacles they encountered when they used IT platform applications for online learning. These obstacles include (a) work and information overload received from instructors, (b) inadaptability and unfamiliarity of the new online learning environment, and (c) personal health challenges related to stress and anxiety. Based on previous relevant research, this study introduced a set of motivational factors and developed a conceptual motivational model for sustainable and healthy online learning.