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The purpose of the article “Nurturing Human Intelligence in the Age of AI: Rethinking Education for the Future” is to explore the profound impact of Artificial Intelligence (AI) on education and to emphasize the need for a fundamental shift in current education systems. The article aims to provide practitioners with actionable insights on how to navigate the rapidly evolving landscape of AI in education while preparing young people for their crucial role as the workforce of tomorrow. It seeks to highlight the potential of AI to revolutionize education while also acknowledging the importance of preserving the unique human touch in the learning process.

This article explores the disruptive impact of Artificial Intelligence (AI) on education and emphasizes the need for a fundamental shift in current education systems to prepare young people for an AI-driven future. It highlights the potential of AI to revolutionize education through personalized learning experiences, enhanced teacher professional development and automation of administrative tasks while acknowledging the importance of approaching AI implementation with caution and preserving the unique human touch in education. The article argues for a shift in focus from rote learning to fostering critical thinking, creativity and problem-solving skills, emphasizing the development of Learning Mastery and Knowledge Mastery. It underscores the vital role of educators in leveraging AI technologies and preparing young people for the future, along with the need for responsive educational policies and curriculum frameworks that integrate AI literacy and ethical considerations. The article concludes by calling for reimagining the schooling system, prioritizing high-level thinking and nurturing the unique capabilities of human intelligence. The future of education lies in harnessing the power of AI while celebrating and cultivating distinctively human qualities. Educational practitioners play a crucial role in shaping this future by bridging the gap between research and practice, ensuring a positive and prosperous future for society in an AI-driven world.

(1) AI can revolutionize education through personalized learning, enhanced teacher development and task automation. (2) Balance is needed between AI and human touch in education. Current education systems fail to cultivate critical thinking and creativity. (3) Learning Mastery and Knowledge Mastery should be emphasized to foster independent thinking and problem-solving. (4) Educators play a vital role in integrating AI into the learning process. (5). AI can redefine success in education and cultivate future-proof skills. (6). Responsive and adaptable educational policies are necessary. (7) The future of education lies in harnessing AI while nurturing human intelligence.

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(1) Educators should actively engage with AI technologies and explore ways to integrate them into the learning process to enhance personalized learning experiences. (2) Professional development programs should be designed to equip teachers with the necessary skills to effectively utilize AI tools and leverage them to improve instructional practices. (3) Curriculum frameworks need to be revised to integrate AI literacy, digital citizenship and ethical considerations into the educational journey of young learners. (4) Educational institutions should invest in AI-powered assessment tools that provide a holistic understanding of a student’s abilities, capturing their strengths and areas for improvement beyond test scores. (5) Educators should focus on teaching metacognitive strategies, encouraging self-reflection and self-assessment and providing opportunities for students to develop problem-solving and critical-thinking skills. (6) Active learning strategies, such as project-based learning, problem-based learning and inquiry-based learning, should be employed to foster deep learning and knowledge mastery. (7) Educational policies should encourage innovation and collaboration between educational institutions, government bodies and industry stakeholders to ensure responsiveness to the rapidly evolving landscape of AI in education. (8) Educators should strive to create a learning environment that nurtures and celebrates the unique capabilities of human intelligence while harnessing the power of AI to enhance the learning experience.

(1) Workforce preparedness for an AI-driven future. (2) Potential exacerbation of societal inequalities. (3) Fostering human–AI collaboration skills. (4) Addressing ethical concerns regarding data privacy and security. (5) Emphasizing lifelong learning to adapt to changing demands. (6) Redefining success through a holistic view of student abilities. (7) Shaping societal values that balance human intelligence and AI capabilities. The education system must address these implications to ensure equitable access to AI-enhanced learning, maintain public trust and prepare individuals for a society where human–AI collaboration is essential, while promoting a balanced and harmonious coexistence between human intelligence and AI.

The article “Nurturing Human Intelligence in the Age of AI: Rethinking Education for the Future” offers a fresh perspective on the impact of AI on education. While the topic of AI in education is not novel, the article’s emphasis on nurturing human intelligence alongside AI integration sets it apart. The author’s call for a fundamental shift in education systems to prioritise critical thinking, creativity and problem-solving skills is a unique approach. The article’s exploration of Learning Mastery and Knowledge Mastery as key concepts in preparing students for an AI-driven future adds originality to the discussion. Overall, the article presents a thought-provoking and original viewpoint on the future of education in the age of AI.

This paper intends to explore the significant growth and multifaceted benefits of e-learning within the technology sector in Middle Tennessee, particularly in the transformative context of the COVID-19 pandemic. It seeks to highlight the fundamental shift from traditional training methods to e-learning modalities and emphasize the potential of e-learning to revolutionize technical skill development and expand learning opportunities in the post-pandemic era.

The study employs a comprehensive review of existing literature to glean insights into the use and effectiveness of e-learning in the technology industry, particularly within Middle Tennessee. It synthesizes research findings to understand the growing preference for e-learning and online self-directed training as primary methods for technical skill development in the technology sector.

The literature review reveals a growing trend toward e-learning in the technology industry, driven by its flexibility, accessibility, and ability to rapidly update training materials. E-learning is increasingly integrated into academic programs related to technology, preparing students for the evolving job market. The COVID-19 pandemic has further highlighted the necessity for adaptable and resilient training methods, reinforcing the pivotal role of e-learning in the industry.

This paper contributes to the understanding of the expansion and impact of e-learning in the technology industry in Middle Tennessee, especially in light of the COVID-19 pandemic. It provides valuable insights for organizations and educators on the significance of e-learning in addressing the training needs of the technology workforce and its potential to shape the future of education and skill development in the region.

The purpose of this viewpoint paper is to address the privileged position that classroom learning continues to hold over online learning and to consider the nuances associated with space and place in learning design and teaching for online learners.

It is often believed that the learning that is undertaken in the classroom is superior to the learning designed and delivered for online delivery. In many instances online learners have been subjected to learning and teaching designed for the classroom – learning that is designed for a very different delivery mode, one in which space and place have a significantly different impact on learning, and where connectedness with teaching staff and other students is assumed.

No findings as this is a viewpoint paper.

No research implications as this is a viewpoint paper.

This paper has practical implications for learning designers and those involved in the design and development of online learning events.

No originality value as such as this is a viewpoint paper.

To explore the Fundamental Attribution Error (FAE) bias as a potential impediment to organizational learning and to develop a conceptual model for practitioners and scholars to consider.

Our methodology includes a review and adoption of concepts from social cognition, organizational psychology, and learning theory to examine the role of FAE bias in organizational learning.

FAE bias is characterized by providing implicit support for fostering employee cynicism and resistance behaviors and facilitates ongoing cognitive cycles that hinder collaborative learning and knowledge sharing.

By understanding the role of FAE bias in organizational learning, leaders can develop strategies to mitigate the negative impact of FAE bias on organizational learning dynamics and enhance a social cycle that can improve the organization's learning culture.

This viewpoint highlights that FAE bias in the workplace can lead to a breakdown in how individuals process emotions (affect), actions (behavior) and thoughts (cognition) in social scenarios, exacerbating employee cynicism and resistance, which in turn undermines effective collaboration, communication and the overall social fabric essential for organizational learning.

This viewpoint presents a novel perspective by linking FAE bias directly to cognitive cycles that can impede organizational learning processes through cynicism and resistance behavior, which we propose should be proactively considered by organizations leveraging learning as a key management strategy.

The purpose of this viewpoint is to present the insights of how AI is transforming the learning environment and strengthening the potential of learning and development in large tech organizations.

This paper leverages the expert opinions of 4 L&D professionals, whose specialized knowledge and direct involvement in the deployment of AI technologies provide a rich, informed perspective on the evolution of learning environments.

Four key trends in AI-integration in learning environments can be seen - AI-powered personalization in learning environment; enhancing interactivity with AI; fostering collaboration and social learning; and assessment and feedback in AI-powered environments.

The discussion around key trends offers a strategic framework for other tech organizations to consider when deploying AI in their learning environments. This can serve as a guideline for enhancing learner engagement, personalization, and overall effectiveness of learning programs.

The maturity of artificial intelligence technology and the emergence of AI-generated content (AIGC) tools have endowed college students with a human-AIGC tools collaboration learning mode. However, there is still a great controversy about its impact on learning effect. This paper is aimed at investigating the impact of the human-AIGC tools collaboration on the learning effect of college students.

In this paper, a hypothesized model was constructed to investigate the effects of dependence, usage purpose, trust level, frequency, and proficiency of using AIGC tools on the learning effect, respectively. This paper distributed questionnaires through random sampling. Then, the improved Analytic Hierarchy Process (AHP) was used to assign weights and normalize data. Lastly, one-way ANOVA and multiple linear regression analyses were used to measure and analyze variables, revealing the mechanism of influence.

The usage purpose, frequency, and proficiency of using AIGC tools have a significant positive effect on learning. Being clear about the usage purpose of AIGC tools and matching the specific study tasks will enhance the learning effect. College students should organically integrate AIGC tools into each learning process, which is conducive to building a learning flow applicable to oneself, improving efficiency, and then enhancing learning effects. The trust level in AIGC tools is significant, but positively and weakly correlated, indicating that college students need to screen the generated content based on their knowledge system framework and view it dialectically. The dependence on AIGC tools has a negative and significant effect on learning effect. College students are supposed to systematically combine self-reflection and the use of AIGC tools to avoid overdependence on them.

Based on the findings, the learning suggestions for college students in human-machine collaboration in the AIGC era are proposed to provide ideas for the future information-based education system. For further research, scholars can expand on different groups, professions, and fields of study.

Previous studies have focused more on the impact of AIGC on the education system. This paper analyzed the impact of the various factors of using AIGC tools in the learning process on the learning effect from the perspective of college students.

This study aimed to explore students’ higher-order thinking skills development when they engaged in pattern blocks learning activities using Blended Learning Classroom teaching approaches through the Thailand Lesson Study Incorporated Open Approach model.

The researchers utilized a multiple case research design for 47 higher education students from the Non-degree Higher-order Thinking in Mathematics Program using a purposive sampling technique. The researchers used the On-Demand teaching approach for two days and three hours of a combination of Virtual Live and Face-to-Face teaching approaches, making up a total of 70 and 30 percent of student learning time respectively.

The quantitative results from the online survey questionnaire indicated that the majority of the participants perceived positively the phenomena of the Blended Learning Classroom teaching approach ranging from a mean score of 4.44–4.65. The qualitative results revealed that participants used different interpretations, and utilized their creative, imaginative thinking to connect various concepts while they were solving the problem situations using pattern blocks.

The discussions were limited to a study representative of 47 Non-degree Higher-order Thinking in Mathematics Program students.

The use of the pattern blocks in developing students’ higher-order thinking skills was found to strengthen the effectiveness of Blended Learning Classroom teaching approaches.

This study adds new insight to the literature on Higher-order Thinking Skills development.

This study aims to examine the underlying process through which learning organization culture positively influences knowledge sharing. It specifically explored the mediating role of social capital, underscoring its critical impact on enhancing both knowledge sharing and fostering learning organization culture.

To test the proposed hypotheses, structural equation modeling (SEM) analysis was conducted with a sample of 231 employees from a manufacturing firm in South Korea.

The results of this study indicate significant direct effects of learning organization culture on social capital. Also, social capital indicates a positive effect on knowledge sharing. Although learning organization culture had no direct effect on knowledge sharing, it indirectly affected learning organization culture and knowledge sharing by mediating social capital.

This study proposes that a learning organization culture will be interconnected with social capital and knowledge sharing. Organizations that can effectively harness the wealth of knowledge unlocked by social capital, and subsequently integrate this knowledge into their activities, are poised for competitive advantage.

First, this study places a special emphasis on the mediating role of social capital between learning organization culture and knowledge sharing. Despite extensive research exploring diverse knowledge-sharing factors (Wang and Noe, 2010), it is plausible that examining social capital as a mediator could offer insights for facilitating knowledge sharing through its structural, relational and cognitive dimensions. Second, while a plethora of literature examines knowledge sharing, this study also seeks to unravel the multifaceted pathways through which the learning organization culture influences knowledge sharing and how these processes could be optimized in organizations.

The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.

Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.

The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.

The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.

E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.

A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

This study aims to validate a typology of factors previously established by the authors that influence teachers' gameful practices and to investigate these factors further qualitatively.

A focus group interview was conducted with four experienced teachers to gather their views on gameful education. The interview also included a metaphor analysis focusing on their beliefs about the compatibility of school learning and gamefulness. The data were coded using a deductive approach, and qualitative thematic analysis was employed.

Individual factors are more positive influences on gameful practices than institutional or system-level factors. Teachers stated that digital equipment is not essential for gameful practices, but governmental support in reshaping exam-centric education systems might be a key step in promoting their adoption.

In the 21st century, students' learning needs differ from past generations, creating challenging situations for teachers in exam-centric cultures. Gameful education could help teachers by introducing an engaging and motivating learning environment for students. This paper aims to help teachers implement and decision-makers support innovative practices that target lifelong learning.

The empirical findings validated the previously established typology of factors. This research presents best practices for teachers in implementing gameful methods and highlights hindering factors for school leaders and decision-makers aiming to support gameful practices.