Education

Unlocking the Potential of Artificial Intelligence in Learning and Development
A Practical Guide

Editors: Dr. Aastha Tripathi
Dr. Prateek Kalia

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Unlocking the Potential of Artificial Intelligence in Learning and Development

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Short description about the volume:

The book, Unlocking the Potential of Artificial Intelligence in Learning and Development: A Practical Guide, will serve as your comprehensive roadmap to harnessing the transformative potential of AI in L&D. It demystifies AI and its applications in this field, exploring how it can personalize learning, enhance accessibility, drive engagement, automate tasks, and measure effectiveness. Packed with real-world examples and actionable insights, this book equips L&D professionals, business leaders, and anyone interested in the future of learning with the knowledge and tools needed to embark on their own AI-powered L&D journey. From identifying the right AI tools to developing a robust strategy, implementing solutions, and measuring impact, this practical guide empowers you to navigate the evolving landscape of AI and unlock its potential to revolutionize the way we learn and develop.

With the artificial intelligence, this book delves into conducting comprehensive training needs assessments, identifying individual competency gaps, and establishing targeted interventions for key development areas. By doing so, it empowers employees to embark on a journey of continuous professional development, ensuring they possess the skills and knowledge required to thrive in the dynamic business environment.

Coverage:

We request potential authors to consider submitting their scholarly findings to enrich the content of this intended volume. The book will cover the following topics, but not limited to:

INVITED CHAPTERS:

Chapter 1: Introduction to Employee Training & Development with AI Integration

This chapter lays the foundation by defining employee training & development, emphasizing the growing role of AI in enhancing traditional methods. It explores how AI can be used to design effective training programs, personalize learning experiences, and consider how forces influencing learning models are evolving with AI integration. The chapter provides an overview of global training practices that leverage AI and sets the stage for understanding its potential impact on developing a skilled workforce.

Chapter 2: Strategic Training Leveraging AI
This section delves into the evolution of training with AI integration and explores the strategic importance of AI in fostering a skilled workforce. It examines how AI can be integrated into business strategy formulation, considering the influence of organizational culture on AI adoption in training needs. Additionally, it explores the benefits and challenges of in-house vs. outsourced training solutions that utilize AI.

Chapter 3: Conducting Needs Assessment with AI
This section acknowledges traditional training needs assessment methods like observation, interviews, and feedback forms, while introducing how AI-powered tools and techniques can be used to conduct more comprehensive and future-oriented needs assessments. Exploring AI in needs assessment allows for identifying individual learner needs and preferences, leading to personalized training interventions.

Chapter 4: Transfer of Training and Program Design with AI
This chapter explores the cognitive aspects of learning and various learning theories. It delves into the concept of Outcomes-Based Learning (OBL) and explores how AI can support its implementation by analyzing learner data and providing personalized learning pathways. It emphasizes program design principles that incorporate AI-powered elements, including selecting trainers/venues, outsourcing options, and utilizing human capital investment data and big data analytics to measure the effectiveness of training programs and facilitate knowledge transfer.

Chapter 5: Training Evaluation with AI
This section explains the importance of training evaluation, emphasizing the need to measure outcomes and objectives. It explores the benefits of using AI-powered tools to determine Return on Investment (ROI) for cost-benefit analysis and leverages big data and workforce analytics to assess the impact of training on human capital development. This allows for a more comprehensive understanding of training effectiveness and informs future improvements.

Chapters 6: Integrating AI into Traditional-Based Training Methods
This chapter explores how traditional training methods can be enhanced through AI integration. It examines how AI can be used to personalize and adapt presentations, role-plays, group building, and team-building activities, leading to more engaging and effective learning experiences.

Chapter 7: Integrating AI into Technology-Based Training Methods
This chapter explores how technology-based training methods can be further optimized with AI. It delves into AI potential to enhance Computer-Based Training (CBT), online learning methods, social media learning tools, and Learning Management Systems (LMS). It also discusses factors to consider while choosing tech-based learning with AI integration, ensuring optimal learner outcomes.

Chapter 8: Employee Development and Career Management with AI
This chapter explores how AI can enhance employee development and career management. It examines: (1) AI-powered skills gap analysis: Identifying individual development needs based on current skills, future job requirements, and industry trends. (2) Personalized career coaching and mentoring: Leveraging AI to provide personalized guidance and support for career development, including matching individuals with relevant learning resources and opportunities. (3) AI-driven talent management: Utilizing AI to match individual skills and aspirations with future career opportunities within the organization, fostering talent retention and growth.

Chapter 9: Social Responsibility, Diversity, and Ethical Considerations in AI-powered L&D

This chapter explores the concept of work-life balance, assesses workplace inclusivity and diversity, and the role of AI in promoting and protecting these values. It also discusses the ethical considerations associated with using AI in L&D, such as: (1) Bias and fairness: Ensuring AI-powered training is free from bias and promotes inclusivity for diverse learners. (2) Transparency and explainability: Understanding how AI algorithms make decisions and ensuring transparency in training delivery. (3)
Privacy concerns: Protecting learner privacy and data security in AI-powered training environments.

Chapter 10: The Future of L&D with AI: A Collaborative Approach
This chapter concludes the book by exploring the future of L&D with AI, emphasizing the need for a collaborative approach between humans and AI. It highlights the importance of: (1) Continuous learning and upskilling: Equipping L&D professionals with the skills and knowledge to leverage AI effectively. (2) Strategic integration of AI: Integrating AI into L&D strategies in a way that complements and enhances existing practices.

Important Dates:

Initial Proposal/Extended Structured Abstract Submission (400 - 600 words)

Deadline: July 15th 2024

Notification of Acceptance: August 15th 2024

Full Chapter (8,000 - 10,000 words) Submission Due: On or before October 31st 2024

SUBMISSION PROCEDURE:


Researchers and practitioners are invited to submit a one-page chapter proposal or abstract on or before July 15th, 2024, clearly mentioning the title of the paper and author(s) details. Author(s) will be notified about the status of their proposals by August 15th, 2024. Full chapters (15-20 pages) are expected to be submitted by October 31st, 2024. All submitted chapters will be peer-reviewed.

Prospective authors are requested to submit their Extended Structured Abstract/ full-length chapters as an email attachment in a Word file to:

For Indian & International Authors:

Editors:
Dr. Aastha Tripathi & Dr. Prateek Kalia
Email: editors4ai@gmail.com


Please find a few quick points below to adhere:
1. For reference, please follow APA style (from the American Psychological Association) and be consistent throughout the book using recent references. For this purpose, refer to the Publication Manual of the American Psychological Association, 6th Edition. Information can also be found at https://www.library.cornell.edu/research/citation/apa and http://www.landmark.edu/m/uploads/APA-Citation-Guide 6th-ed.pdf.

2. Please use Times New Roman 11-point font with 1.5 spacing for preparing the manuscript.

3. All text, figures, equations, and images should be in open (editable) format, usually in Microsoft Word format, as we may need to perform enhancements on them. Please provide them in at least 300 dpi.

4. A concisely worded title should be provided.

5. Please provide the manuscript in American English with proper proofreading before submitting.

6. Please note that most of the illustrations and tables in the book should be original and have not published elsewhere (including online). If you wish to include figures/tables that have been published prior, proper permission is necessary. You MUST provide permission document of some sort (Copyright Clearance Center document, signed form, email, letter, etc.) that allows reuse at no charge. Open-source publications usually require a reference to the original publication, which is courtesy to the original author as well. You will frequently see how you should indicate source WITH the table or figure also. Please include that note in your manuscript with the figure/table caption or title.

7. The generation or reporting of chapter using a generative AI tool/Large scale generative models is not permissible, as per AAP authorship criteria, the author(s) must be responsible for the creation and interpretation of their work and accountable for its accuracy, integrity, and validity.

8. At AAP, we welcome submissions for consideration which are original and not under consideration for any other publication at the same time. All authors should be aware of the importance of presenting content that is based on their own research and expressed in their own words.

9. Please also provide Turnitin report along with your submitted chapter with us.
10. If chapter gets accepted to publish in this book, we will require signed Copyright Transmittal Forms (along with the figure/table chart) from each lead chapter author, which is already available here.


In addition to above, authors must refer to the following link for detailed guidelines for chapter preparation: https://appleacademicpress.com/download/AAP_MS_INSTRUX.pdf

Note: There is no publication fee for manuscripts submitted to this book publication. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere.


About the Authors / Editors:
Editors: Dr. Aastha Tripathi
Assistant Professor, Centre for Social and Organisational Leadership, School of Management and Labour Studies, Tata Institute of Social Sciences (TISS), Mumbai, Maharashtra, India

Dr. Aastha Tripathi is an Assistant Professor at the Centre for Social and Organisational Leadership, School of Management and Labour Studies, Tata Institute of Social Sciences (TISS), Mumbai, Maharashtra India, in Human Resource Management/Organisational Behaviour. Before this, she worked as a post-doctoral researcher at the Indian Institute of Management, Ahmedabad (IIMA). She also worked as a senior research scientist with the Indian Institute of Technology, Delhi (IITD). She has been recently conferred with the prestigious “Young Woman Researcher in Human Resource Management” award by the Venus International Foundation. Her areas of interest are learning agility, learning culture, employee retention, turnover intention and Quantitative research. She serves as a reviewer in various A and A*category journals. She also serves as an editorial advisory member on the International Journal of Technology & Human Interaction (IGI Publisher), International Journal of Knowledge Management (IGI Publisher) and International Journal of Organisational Analysis (Emerald Publisher). She has published in top-notch journals (such as the American Business Review, International Journal of Organisational Analysis, Innovation: Organization & Management, to name a few.

Dr. Prateek Kalia
Assistant Professor, Department of Business Management, Faculty of Economics and Administration, Masaryk University, Lipová, Brno, Czech Republic

Dr. Prateek Kalia is an Assistant Professor at the Department of Business Management, Faculty of Economics and Administration, Masaryk University, Brno, Czech Republic. He has vast experience of twenty-one years in corporate, government administration, and academics; including a three-year post-doctoral position at Masaryk University; director and professor at a leading university in North India, and deputy general manager at a government organization. He is a specialist in the field of management with a keen interest in digital analytics, electronic commerce, e-service quality, and consumer behavior. His articles are published in leading international journals like the International Journal of Operations & Production Management, Computers in Human Behavior, Journal of Innovation & Knowledge, European Management Journal, etc. He is a reviewer for various A-category journals. He is very well known for his novel smartphone user classification metrics called Cellulographics and holds a copyright for it. He is a recipient of the prestigious Dean Award for excellent publication at Masaryk University.




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