In this paper the section needed is the Literature Review. I will be adding some references to be used for the section and also some part of this paper has been done so have to have an overview of what the paper is about.
Optimizing ETI’s Young Innovators Workforce Readiness Program
Team 3
Veronica Aguila
Rori Jackson
Nneka Okobi
Fayetteville State University
School of Business and Economics
BIDA 670, Spring 2024
March 11, 2023
CONTENTS
I. Introduction
A. General Overview of The Contents
B. Motivation
C. Goals
D. Company Background
II. Problem Definition
III. Literature Review
IV. Approach / Methodology
V. Data Collection
1. Introduction
Our analysis encompasses the developing youth STEM programs of the Emerging Technology Institute, a small military and first responder training company. The overarching goal of this research is to optimize its cohort 4 program called the Young Innovators program. The Young Innovators program is a high-impact internship program targeted towards high school upperclassmen and college students and prepares them to enter a technologically driven workforce. The structure of the Young Innovators program is undergoing a restructuring thus, this research is critical in setting the foundation for future cohorts. There are approximately ten cohort 4 participants during the 2023-2024 school year and, the organization aims to increase the participant size and number of internship iterations. To do this, ETI must the dynamics between baseline STEM skills and attitude evaluations, workforce readiness metrics and digital competencies.
1.1. General Overview of the Contents
We will explore ETI’s background and evolution, the challenges it faces, and the motivations and goals of this research. Subsequently, we will navigate through a comprehensive literature review of workforce readiness and digital competency as it relates to technological careers. Following, we will meticulously lay out the approach and methodology adopted for the research to include data collection and survey assessments. The culmination will include a discussion of the implications and significance of the research and transformative options for ETI.
1.2. Motivation
Firstly, the motivation behind this research is driven by ETI’s innate desire to offer a next step solution to youth in STEM who are interested in pursuing technology careers. Secondly, to impart on today’s emerging and young adults the skills to successfully operate in the technology driven workforce. Finally, to generate a positive understanding and increased awareness of career opportunities working alongside the military and federal workforce. The company's primary challenge is identifying which metrics are most useful in determine attitude improvements and skill competencies of their emerging and young adult populations.
1.3. Goals
The goals set forth for this research are designed to be transformative for the future of ETI’s cohort 4 of the Young Innovators program.
1.3.1. The first goal is to establish and validate baseline metrics used to determine participant success.
1.3.2. The second goal is to evaluate the digital competencies of high school students and college students as it pertains to workforce readiness.
1.3.3. The third goal is to compare the digital skills and competencies assessments of cohort 4 against the wider student population to determine ranking and success.
1.4. Company Background
Emerging Technology Institute (ETI) is a small military and first responder professional training and coaching company established around 2018. ETI specializes in unmanned aircraft systems (UAS), robotics and artificial intelligence in addition to offering tactical training at their facilities. Emerging Technology Institute (ETI) is a small military and first responder professional training and coaching company established in 2018. In 2022, ETI established its youth STEM program, broadened to elementary through college students, that offers STEM engagements and curriculum described as Level 1 – 4 services. Services include school-based engagements, intensive clinics, camps, and opportunities for competitions, scholarships, and internships. The goal of the program is to expose students to technology careers and develop the skills needed in Department of Defense and the American workforce.
2. Problem Definition
The company has not established baseline data collection efforts to track participant progress through cohort programs. Current data collection has revolved around observational engagement and attitude perceptions for cohorts 1-3. The company is interested in having the ability to determine if positive changes in skills and attitudes correlate with high-impact services to maximize program participation and output. Further, the company would like to understand which indicators are significant in determining changes in skills and attitudes.
3. Literature Review
4. Approach / Methodology
4.1. Approach
4.2. Methodology
5. Data Collection
Data collection will encompass a small skills and attitude survey aimed at current cohort 4 participants. Further, a larger 82-question digital competency survey will be distributed to a larger high school and college student population. Cohort 4 participants will be evaluated against the larger population to determine rankings in like programs and to determine baseline skills.
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Information Systems Frontiers https://doi.org/10.1007/s10796-022-10308-y
Reskilling and Upskilling the Future‑ready Workforce for Industry 4.0 and Beyond
Ling Li1
Accepted: 23 June 2022 © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, corrected publication 2022
Abstract Industry 4.0 is revolutionizing manufacturing processes and has a powerful impact on globalization by changing the work- force and increasing access to new skills and knowledge. World Economic Forum estimates that, by 2025, 50% of all employ- ees will need reskilling due to adopting new technology. Five years from now, over two-thirds of skills considered important in today’s job requirements will change. A third of the essential skills in 2025 will consist of technology competencies not yet regarded as crucial to today's job requirements. In this study, we focus our discussion on the reskilling and upskilling of the future-ready workforce in the era of Industry 4.0 and beyond. We have delineated top skills sought by the industry to realize Industry 4.0 and presented a blueprint as a reference for people to learn and acquire new skills and knowledge. The findings of the study suggest that life-long learning should be part of an organization’s strategic goals. Both individuals and companies need to commit to reskilling and upskilling and make career development an essential phase of the future workforce. Great efforts should be taken to make these learning opportunities, such as reskilling and upskilling, accessible, available, and affordable to the workforce. This paper provides a unique perspective regarding a future-ready learning society as an essential integral of the vision of Industry 4.0.
Keywords Industry 4.0 · Industrial revolution · Skill sets · Reskilling, upskilling, competencies · Experiential training · Future-ready workforce · Human capital
1 Introduction
Industry 4.0 (I4.0) is in the process of revolutionizing manu- facturing and engineering all over the world. I4.0 is a virtual reality fusion system based on traditional manufacturing and transformed with cyber-physical systems, the Internet, the Internet of Things (IoT), and Industrial Internet of Things (IIoT), artificial intelligence, machine learning, hyper-con- verged infrastructure, deep learning, virtualization, and more to create an intelligent production system (Li, 2018, 2020; Xu et al., 2018; Li & Zhou, 2020; Xu et al., 2014). Work- force, capital, and technology are the three major compo- nents that significantly contributed to the evolution of the past three industrial revolutions. Therefore, it is time to look at the talent required to realize the vision of Industry 4.0 and beyond.
The World Economic Forum projected in its Future of Jobs Report 2020 that half of all employees worldwide would need reskilling by 2025 (Schwab & Zahidi, 2020). This estimation does not include all the people currently not in employment. Before COVID-19, the rise of automa- tion and new technologies transformed the world of work, resulting in an urgent need for large-scale upskilling and reskilling. Now this need has become even more critical. In a 2016 World Economic Forum report, experts projected that 65% of children entering primary school today would ultimately work in completely new job types that do not exist today (Schwab & Samans, 2016). Developing new and diverse education programs and promoting innovative cur- ricula are some of the STEM program's primary goals that provide skills, knowledge, and attitudes needed for an entre- preneurial culture (Li, 2020).
By giving all people opportunities to develop the skills they will need to participate fully in the future workplace, we ought to create more inclusive and sustainable econo- mies and societies where no one is left behind. Industry 4.0 is about creating a unique life-long education system that
* Ling Li [email protected]
1 Old Dominion University, Norfolk, VA 23529, USA
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ensures a future-ready workforce. Universities with a tradi- tion of educating and training the world's most competent designers, engineers, technology specialists, consultants, operations professionals, and data analysts are in an excit- ing era to tackle these challenges quickly and collaboratively.
Life-long learning for all is becoming a reality. New skills and technologies have been introduced much faster than a decade ago. Respondents to the Future of Jobs Survey esti- mate that around 40% of workers will require reskilling for a length of six months. Half of the workforce will need to reskill in the next five years, as the double-disruption of the economic impacts of the COVID-19 pandemic and increas- ing automation that transforms jobs (Whiting, 2020). Ele- mentary and middle school education at a young age remains mandatory and fundamental, and is the first phase of life- long learning. An upward trend of increasing job complex- ity has been observed during the progression of industrial revolutions. Learning throughout life, including at an older age, makes the difference in the higher education domain in the twenty-first century. However, the gap in life-long learning exists among individuals. European Commission (2020) estimated that less than two in five adults participate in learning every year in the EU, which is not enough to sup- port the needs of Industry 4.0 and beyond. All of us should embrace the opportunities to upskill and reskill our profes- sional skill sets and contribute to the economic development of the 21 century.
While many educational organizations and individuals might still wonder how Industry 4.0 could affect the edu- cation system, some are implementing changes today and preparing for a future when artificial intelligence (AI) and cyber-physical systems can connect their business glob- ally. In this study, we focus our discussion on the reskilling and upskilling of the future-ready workforce in the age of Industry 4.0 and beyond. The following sections cover sev- eral key elements that contribute to training a future-ready workforce. Section 2 provides background information about the top skills needed for Industry 4.0. Section 3 discusses reskilling and upskilling of the workforce in different parts of the world. In Section 4, a life-long learning framework offers opportunities to reskill and upskill a future workforce. Finally, Section Five provides conclusions.
2 Background and Literature
Industry 4.0 is a significant transformation to the digitiza- tion of manufacturing and the creation of a cyber-physical system. I4.0 connects production and process technologies, integrates vertical and horizontal value chains, and digital- izes product and service offerings to pave the way for new production and economic value chains. This transition has an enormous impact on higher education which has a role of
training talents, leading scientific innovation, disseminating knowledge, as well as preparing a future-ready workforce.
2.1 What Skills will be in High Demand?
The World Economic Forum has published several reports on the future of jobs and top skills that will play significant roles in future technology advancement (Schwab & Samans, 2016; Schwab & Zahidi, 2020). The authors summarized the perspectives of strategy officers and chief human resources managers from leading global companies about the current shifts in required skills, and recruitment across industries. These reports analyze skills needed for the labor market and track the pace of changes. A quick rate of technology adop- tion signals that in-demand skills across jobs will change over the next five years or longer; therefore, skill gaps will continue to be significant.
Table 1 shows the top 10 skills for 2015, 2020, and 2025 (Gray, 2016; Whiting, 2020). The top 10 skills for 2015 are listed under Column 1 on the right-hand side of Table 1, and the top 10 skills for 2020 are listed under Column 2 on the right-hand side. The middle column, column 3, compares the change of rank of the top skills in 2015 and 2020. For example, complex problem solving is ranked number 1 in 2015 and 2020, while critical thinking is moved up to num- ber two in 2020 from its rank of number four in 2015. The first column from the left-hand side shows the changes in top skills in 2015, 2020, and 2025. For example, “Analytical thinking and innovation” is listed as the top 1 skill but was not on the list in 2015, neither 2020. “Complex problem- solving” is the third most important skill in the 2025 list but was ranked number 1 in 2015 and 2020.
For those workers who stay in their roles, the share of core skills that will change from 2020 to 2025 is more than 60% (Table 1). Seven out of 10 top skills listed under the column “in 2025” are not listed under 2020 and 2015. While between 2015 and 2020, skill requirements overlap consid- erably, eight out of ten top skills are the same for the two periods (Table 1).
Looking forward to 2025 and beyond (Table 1), analyti- cal thinking and innovation skills crown the skill-set list that employers believe will grow in prominence in the next five years. Active learning and learning strategies are a new skill set that trailed behind the top one. Analytical thinking and active learning ranked number 1 and number 2 in 2025, emphasizing cognitive self-management.
Critical thinking and problem-solving skills, which were at the top of the skill list in 2020 and 2015, are now rel- egated to 3rd and 4th places in 2025’s skill list (Table 1). But these two skills, along with creativity, have consistently been viewed as critical skill sets since the first report was published in 2016. With the avalanche of new technologies, new products, and new working processes, employees will
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become more creative to respond to and benefit from tech- nological changes.
Items six to 10 under 2025 (Table 1) are newly emerg- ing skills focusing on technology-related competencies and skills, cognitive reasoning capability, and leadership, with a sharp uptake from 2020. Five years from now, over two- thirds of skills (67%) considered important in today’s job requirements will change. In addition, a third of the essential skill sets in 2025 will consist of technology competencies not yet regarded as crucial to today's job requirements.
2.2 What Skills are Less Focused on?
Negotiation and people management were ranked high on the 2015 skill list. However, these skills began to drop on the 2020 list and do not appear on the 2025 list. As compa- nies and managers increasingly use masses of data and make decisions based on data analytics, negotiation and people management retreat their positions in the decision-making process. Society expects artificial intelligence and machine learning to provide decision support information to a com- pany’s board of directors by 2026.
Similarly, soft skills in the cognitive scope, such as qual- ity control and active listening, and emotional intelligence, considered core skills on the 2015 skill list, disappeared entirely from the top 10 skill list of 2025. Instead, this year's newly emerging items are skills in self-management such as active learning, resilience, stress tolerance, and flexibility.
2.3 Emerging Disruptive Technology in Industry 4.0 and Beyond
The advancement of disruptive technology accelerates the reskilling requirements. The global supply chain, for exam- ple, has already experienced a great deal of change in the
past five years. Online shopping, e-commerce, automated warehouse operations, and digitized seaport shipping infor- mation exchange are a few examples. Disruptive technolo- gies are opening up new possibilities for society, providing innovative technology applications, novel materials, and processes to create products and services that until recently were unimaginable. As a result, those working in the manu- facturing and service sectors will need new skills. Mobile internet, cloud technology, and artificial intelligence are already impacting how we work. While quantum comput- ing and 6G are still in their early stages of use, the pace of change will be fast. Table 2 lists seven disruptive technolo- gies that play an important role in transforming our society in a digital era.
In the next ten years, both manufacturing and service firms will have to adapt to or adopt Industry 4.0 principles and technologies to survive the competition. The vast major- ity of business leaders (94%) now expect employees to pick up new skills on the job (Whiting 2021). They believe that investing in the right people and the right skillsets today ensures a favorable position well into the future. Based on the literature, we discuss seven vital disruptive technologies that require significant skill upgrade for a future-ready work- force. These technology groups are far from comprehensive, but they can serve as a guideline for organizations to formu- late their technology portfolio and invest in reskilling and upskilling their employees and staff.
Artificial Intelligence (AI) Since 2000, particularly after 2015, the development and utilization of artificial intel- ligence (AI) have escalated following the rapid growth of sensors and computer chips, the evolution of algorithms, and big data support. AI has been recognized as a strategic information technology innovation tool to improve com- panies’ competitiveness. AI technologies, such as natural
Table 1 Review of reports of top 10 skills on reskilling and upskilling future-ready work force
Data Source: Gray (2016). The ten skills you need to thrive in the Fourth Industrial Revolution. World Economic Forum, January 19, 2016; and Whiting (2020). These are the top 10 job skills of tomorrow – and how long it takes to learn them. World Economic Forum, October 21, 2020. * 25/20/15: skills in 2025, skills in 2020, and skills in 2015; 20/15: skills in 2020 and skills in 2015
25/20/15* in 2025 20/15* in 2020 in 2015
1 Analytical thinking and innovation 1, 1 Complex problem solving Complex problem solving 2 Active learning and learning strategies 2, 4 Critical thinking Coordinating with others 3, 1, 1 Complex problem-solving 3, 10 Creativity People management 4, 2, 4 Critical thinking and analysis 4, 3 People management Critical thinking 5, 3, 10 Creativity, originality, and initiative 5, 2 Coordinating with others Negotiation 6 Leadership and social influence 6 Emotional intelligence Quality control 7 Technology use, monitoring, and control 7, 8 Judgment and decision making Service orientation 8 Technology design and programming 8, 7 Service orientation Judgment and decision making 9 Resilience, stress tolerance, and flexibility 9, 5 Negotiation Active listening 10 Reasoning, problem-solving 10 Cognitive flexibility Creativity
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language processing, machine learning, and deep learning, bring sophisticated data analysis capabilities to applications across various industries (Chen et al., 2021). For example, AT&T investigates how to use AI algorithms to enable drones to check and repair base stations. SK Telecom in South Korea applied machine learning to analyze network traffic to detect anomalies and strengthen network operations (Chen et al., 2021). Although some AI initiatives have been adopted in leading technology companies, many applications of AI are still at their conceptual stage. As a result, they have not generated much commercial value, particularly in net- work management and predictive maintenance applications.
From data collection to organizational architecture design, the AI development strategy and AI project prioriti- zation are as complex as the technology itself. To success- fully leverage the benefits of AI applications, researchers and industry experts need to build more powerful algorithms, use more significant amounts of data and computing power, and rely on centralized cloud services.
Quantum Computing Quantum Computing is a disrup- tive technology that tries to understand the processing and transmission of information using quantum mechanics principles. It integrates quantum effects in physics into the study of Information and Communication Technology (ICT), including theoretical issues in computational models and experimental topics in quantum physics. As a result, quan- tum technologies are anticipated to create a massive para- digm shift in how Industry 4.0 operates, which incorporates
the digital revolution into the physical world and provides new directions in artificial intelligence and nanotechnology (Kim, 2017).
Current computing technologies have limitations due to the restriction of bits of 0 and 1. The computation must be done with bits in storing or processing data. Quantum infor- mation technology is a new paradigm that can process more than digital data consisting of 0 and 1 (Sigov et al., 2022). If quantum technology is applied to Information and Com- munications Technology (ICT), it will enable rapid compu- tational processing and un-hackable internet systems. It is expected that the next generation of ICT will overcome the limitations of existing digital computers (Sigov et al., 2022). An internet based on quantum physics promises inherently secure communication. In 2020, a research team headed by Stephanie Wehner at Delft University of Technology built a network connecting four cities in the Netherlands entirely through quantum technology. Messages sent over this net- work would be unhackable (Temple, 2020). A team in China used the technology to construct a 2,000-km network back- bone between Beijing and Shanghai. Google has provided the first clear proof of a quantum computer outperforming a classical one, although a full-scale quantum computer has not yet been developed.
5G and 6G 5G is a generation of cellular networks designed to enhance the efficiency of data transmission. 5G networks provide higher data rates, lower latency, massive device con- nectivity, higher capacities, better consistent service quality,
Table 2 Disruptive Technology in Industry 4.0
# Technology for Industry 4.0
1 AI & ML Artificial intelligence is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings (https:// www. brita nnica. com/ techn ology/ artifi cial- intel ligen ce; Chen et al., 2021)
2 Quantum Computing Quantum information technology is a new paradigm that can process more than digital data consisting of 0 and 1 (Sigov et al., 2022). Quantum physics incorporates the digital revolution into the physical world and provides new directions in artificial intelligence and nanotechnology (Kim, 2017)
3 5G & 6G 5G is a generation of cellular networks designed to enhance the efficiency of data transmission. 6G will connect eve- rything, provide full dimensional wireless coverage, and integrate all functions, including sensing, communication, computing, caching, control, positioning, radar, navigation, and imaging, to support full-vertical applications
4 IoT, IIoT IoT and IIoT connect the network of physical objects (https:// www. oracle. com/ inter net- of- things/ what- is- iot/). In a supply chain, IoT links fabrication and material handling equipment, remote sensors for freight transport, and tracking systems for vehicles and other assets
5 Data Sciences & Business Intel- ligence
Data Science requires coding, data mining, analytical skills, and modeling to extract value and meaning from the data. In addition, human–machine interaction, quantitative skills, and understanding of information technology are regarded as essential skills in data sciences and business intelligence (Darmont et al., 2022)
6 Cybersecurity Cybersecurity is a measure to protect a computer or computer system against unauthorized access or attack (https:// www. merri am- webst er. com/ dicti onary/ cyber secur ity). A critical step in preventing cyber threats is finding ade- quate and feasible ways to encourage employees and end-users of various technologies to protect their individual and organizational information assets (Sigov et al., 2022)
7 Green Energy Green energy comes from renewable sources. Green energy is considered clean, sustainable, or renewable energy. A clean energy plan is an essential integral part of Industry 4.0, underscored by global leaders, energy sector admin- istrators, and prominent corporate executives
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and lower cost than 4G networks (Sigov et al., 2022). How- ever, 5G is insufficient for IoT devices to exchange various data types in real-time. 6G as the next generation of 5G is at the corner. 6G will exhibit more heterogeneity than 5G and support applications far beyond anything seen. 6G will con- nect everything, provide full dimensional wireless coverage, and integrate all functions, including sensing, communica- tion, computing, caching, control, positioning, radar, navi- gation, and imaging, to support full-vertical applications.
Networking, IoT, and IIoT Industry 4.0 has dramatically impacted the number of networking professionals in manu- facturing and other critical sectors. Some examples of Indus- trial IoT (IIoT) and networking technologies are intelligent factories, connected fabrication and material handling equip- ment, remote sens