What are Students Achieving Goals in Higher Education and Emerging Technology Curriculum?
A Qualitative Research Study
by
Carnegie Caesar
Faculty Member
An Institutional Research
Submitted to [School of Education]
[Geotech University]
In Partial Fulfillment of the Requirements
for Ranking [Under Review for Accreditation Process]
[2024]
(Researcher uses Pen Name)
Acknowledgements
A grateful heart of appreciation for the professional and personal support through the research pathway. The professors, my chair committee, and my defense committee who extended their knowledge and expertise for the fulfillment of the research are the best in preparation for scholarly, peer review or institutional review. I am thankful for librarian assistance, and the learning network who have inspired me to understand how to prepare infographics for the conceptual framework of my research. I would like to seize this opportunity to acknowledge my collegial network for professional development and support. The assistance and support from family and friends are the most appreciated. I am truly grateful for the collaboration and the feedback from the peers to help me stay focused. The focus on the scholarly lifestyle of staying on task, meeting deadlines, peer reviews. The people who believed in me and motivated me to this completion, I will always cherish the time for caring. I would have been helpless; but with faith, beliefs, and all my possibilities are in the hands of the almighty, the Holy one of the Highest authorities.
Abstract
This is a qualitative research inquiry to examine elements of privatization in higher education. It is noteworthy to understand how students and faculty members interact with technology resources for learning. The research methodology is designed for data analytics and user experience in learning management.
In addition, the perspectives on the emergence of artificial intelligence in higher education, and
social streamlined as an integral part of shaping instruction for career readiness and professional development. There are many ways of incorporating reinforcement in education successfully. Burnett, (2021) conducted research on learning for earning with undergraduate student affairs employment and postgraduate employability outcomes to demonstrate their professional success post-graduation. Moreover, researchers have shown inadequacy of academic and industry specific knowledge to secure graduates an occupation and meet the demands of the contemporary job market.
In an effort to produce work-ready graduates, institutions are compelled to enhance student workforce and professional development. Curriculum development to provide a context for the development of postgraduate employability by offering students job opportunities in the operation is pivotal; in particular, productivity software improved in various industry workplaces. This is a shift in career readiness for skills development that higher education addresses in preparing students. In turn, these academic experiences such as ChatGPT AI and social stream tools are adaptive in supporting students’ academic, personal, and professional development. Using students' experiences with AI social stream tools can contribute to student professional development through on campus jobs, internships, and field experiences. However, the effectiveness of school reinforcement success encompasses other aspects of social networking influencer to fit criteria for job fitness.
Social media is a platform to stream various features of social skills and cultural trends. This research accounts for students' perceptions of what higher education experiences best curriculum for their propensity in academic success. In this qualitative research students' perspectives on artificial intelligence in higher education, social streams as an integral part of shaping instruction for career readiness and professional development experience to be relevant.
Definition of terms
These are special definitions of terms alphabetized to coherently convey theories and its theoretical constructs to present the findings:
Acceptable/Responsible Use Policy (AUP/RUP): Stipulation of students' school or organization’s official policy about the use of the Internet or computer networks.
Algorithm: A technological use as a problem-solving operation for calculation.
Alphanumeric: A technique of creating a strong password using both the alphabets and numbers.
Anonymity: A research condition in which no one, including the researcher, knows the identities of research participants.
Assumption: A thing that is accepted as true or as certain to happen without proof.
Authentic Problem: A genuine, real or original
problem to be solved.
Beliefs: Refers to ideas, doctrines, tenets, etc. that are accepted as true on grounds which are not immediately susceptible to rigorous proof.
Benchmarking: A systematic frame of reference to measure or compare outcomes of organizations, systems or processes against agreed upon.
Bias: This means that the research findings will not be representative of, or generalizable to, a wider population. It can appear at any stage of the research as a loss of balance and accuracy.
Blogging: A writer sharing thoughts, ideas of a content to be relevant online.
Case Study: A qualitative data collection and presentation of detailed information about a particular participant or small group, frequently including data derived from the subjects themselves.
Cloud Computing Metaphor: Refers to network services entirely managing a group suite of hardware and software that can be thought of as an amorphous cloud.
Confidentiality: A research condition in which no one except the researcher(s) knows the identities of the participants. The information has been disclosed in a relationship of trust and with the expectation that it will not be revealed to others in ways that violate the original consent agreement, unless permission is granted by the participant.
Construct: Refers to any theoretically not directly observed such as a concept developed to describe relations among phenomena or for other research purposes; or, a theoretical definition in which concepts are defined in terms of other concepts.
Construct Validity: Seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
Credibility: A researcher's ability to demonstrate that the content of a study is accurately identified based on how the study was conducted.
Cloud Computing: Refers to software and services hosted on remote servers, rather than on local servers, machines, or endpoints.
Cookie: Codes or data usage to reveal, to track users' patterns and preferences by a web server.
Creative Commons: Refers in part to copyright law; as with an authorization by a licensed user or designated to facilitate and encourage more versatility and flexibility.
Cryptography: The practices, processes, and approaches used in cybersecurity of encryption and decryption techniques that scramble and unscramble code according to a cipher, rendering information unreadable to outside parties to protect information, such as emails and files from being read by people outside the sender and recipient.
Cybersecurity: Security measures from unauthorized access to technology equipment, devices or network; securely managing and protecting confidentiality, integrity, and availability of devices, environments, assets, and data from bad actors.
Cybersecurity Framework: is an organized, formalized set of processes, tools, policies, procedures, best practices, and requirements designed toolkits for incidents, antivirus software is used to detect, alert, block, and remove these kinds of malicious programs, such as viruses, ransomware, and more.
Cyber Resiliency is the ability of an IT system to remain operational and provide services in the event of unexpected disruptions, outages, or other unforeseen circumstances. It is the capacity for a system to recover from a disruption quickly and effectively and return to normal functionality.
Cyber Threat Intelligence (CTI): Refers to the process of collecting, analyzing, and integrating data about existing or potential threats to an organization’s digital infrastructure.
Data: Information used as a basis for reasoning, discussion, or measurements.
Data Accessibility: By means of the internet, iCloud, Google Cloud, OneDrive and Dropbox; stored for sharing within designated users.
Delimitations: The action of fixing the boundary or limits of something.
Design Process: In educational technology, it requires the color, layout, fonts, format, editing; in part, printing based on the software solutions.
Decryption: Refers to the process by which organizations make data readable after it has been encrypted. Decryption is only possible with access to the cipher originally used to scramble the data.
Digital Footprint: Data on cyberspace by a person that exists on the Internet; or networked identity adopted or claimed in, organization or electronic device.
Digital Portfolio: A compiled or selection of electronic activities, tasks managed by a user; also known as electronic portfolio.
Digital Stories: Stories that are accessible in portals or learning management platforms or via online.
Digital Tools: Technological equipment use, install with database and processing.
Domain Name System (DNS): Refers to the internet provider used for network location; a known pc/windows data processor.
Ebook: An electronic version of a published book that can be accessed by technology equipment for reading.
Encryption: Refers to coding of data to an unrecognizable conversion, unauthorized, unreadable electronic data; to protect data from unauthorized parties. Organizations encrypt data with a secret code that dictates how the data is scrambled, also called a cipher. Data can only be decrypted or unscrambled and made readable again with that cipher.
Firewall: Technology to fend off cyber attackers and is a fundamental security control. A firewall creates a barrier between an endpoint (such as a laptop) or network and the outside world by restricting access in or out of the network.
Focus Groups: Usually consist of 4-12 participants, examining specific topics or problems, including possible options or solutions, guided by moderators to keep the discussion flowing and to collect and report the results.
Framework: The structure and support that may be used as both the launching point and the on-going guidelines for investigating a research problem.
Grounded Theory: A practice of developing other theories that emerge from observing a group. Theories are grounded in the group's observable experiences, but researchers add their own insight into why those experiences exist.
Hardware: Refers to physical devices like servers, computers, data centers, switches, hubs, and routers, or the tangible part of the IT infrastructure, essential for executing critical tasks and storing important data
Hypothesis: A tentative explanation based on theory to predict a causal relationship between variables.
Implication: A conclusion that can be drawn from something although it is not explicitly stated.
Infographic: An illustrative data in the form of charts, diagrams.
Learning Management System (LMS): An application learning solution or cloud-based system, to allow online users to access curriculum instruction by institutions and instructors. Management of the program is met to be interactive and integrated systems.
Limitations: A limiting rule or circumstance; a restriction.
Makerspace: A designated space for students to gather to create, explore, discover technology using tools and materials.
Malware: Refers to malicious software that attackers use with the intention of harm, exploitation, theft, and other damaging activities. It is ransomware, spyware, and viruses, worms, trojans, keyloggers, zombie programs, software-based attack tools and
Methods: A particular form, steps of procedure, application of techniques, systems of reasoning or analysis, and the modes of inquiry employed by a discipline for accomplishing or approaching something, especially a systematic or established one.
Microcontroller: A hardware integrated circuit to perform one task and one specific application; such as, a processor, memory and input/output peripherals on a single chip.
Multimedia: Commonly used in education to integrate or create interactive responses; normally to motivate or stimulate engagement not limited to sound, colors, text, PowerPoint presentation.
Network: A shared accessibility to internet or computer usage, by a user and an observed (controlled) provider.
Network Resources: This includes the connectivity and network management tools such as internet connections, firewalls, and security protocols, which are crucial for secure and efficient data transmission.
Observation: An act or instance of regarding attentively or watching.
Participant: Individuals or respondents of a research study
Peer-Review: The process in which the author of a book, article, or other type of publication submits his or her work to experts in the field for critical evaluation, usually prior to publication. This is standard procedure in publishing scholarly research.
Phishing: Refers to bad actors sending emails or other message types with malicious links or harmful content to an organization’s users.
Policy: A course or principle of action adopted or proposed by a government, party, business, or individual.
Policy Analysis: Systematic study of the nature, rationale, cost, impact, effectiveness, implications, etc., of existing or alternative policies, using the theories and methodologies of relevant social science disciplines.
Podcast: A digital media file that is shared or stored as data retrieval, portable ipod player or via the URL address of a web page.
Pop-ups: Typically, the user of the primary web browser may be distracted by a secondary web browser window of unwanted advertising, which opens outside of the primary web browser window.
Practices: Perform or exercise regularly in order to improve or maintain one's proficiency.
Principal Investigator: The primary researcher with responsibility for the design and conduct of a research project.
Qualitative Method: Research approach relating to measuring the quality of something rather than its quantity.
Questionnaire: Structured sets of questions on specified subjects that are used to gather information, attitudes, or opinions.
Random Sampling: A process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance.
Ransomware: Refers to a form of malware that infects an organization’s devices and/or systems and locks legitimate users out of their accounts.
Reliability: The degree to a prerequisite for validity in which a measure yields consistent results.
Research: The systematic investigation into and study of materials and sources in order to establish facts and reach new conclusions.
Rigor: Degree to which research methods are meticulously carried out in order to recognize important influences occurring in an experimental study.
Sample: The population researched in a particular study.
Semantic Approach: This involves analyzing the explicit content of the data.
Social impact is a significant change that positively addresses a pressing injustice or challenge, such as climate change, human rights, or the education gap.
Social Media: Social interaction via online, applications by users not limited to (e.g., Facebook, Twitter, LinkedIn, Google+, Instagram, Pinterest, Snapchat, Tumblr and
Reddit).
Social Theories: Theories about the structure, organization, and functioning of human societies.
Software: Refers to programs and applications that empower users and IT personnel to perform tasks efficiently; including CRM systems, productivity tools for operating systems and management tools.
The National Institute for Standards and Technology (NIST): Includes continuous monitoring as part of a six-step risk management framework.
Theory: An idea used to account for a situation or justify a course of action, a general explanation about a specific behavior or set of events that is based on known principles and serves to organize related events in a meaningful way.
Triangulation: A multi-method used to check the validity of findings from any one method, using different methods in order to focus on the research topic from different viewpoints and to produce a multi-faceted set of data.
Validity: The degree to which a study can be reliable, consistently measuring the same thing, but not valid.
Viral: A viral in the form of an email blast sends out a message, advertising, a reminder to take action.
Virtual Field Trip: Typically a visual exploration via the web-based, PowerPoint presentation.
Virus: A damaging programming code inserted, transmitted by email, in many forms, when opened, may erase data or cause damage to your hard disk. Some viruses may affect people in your list of contacts.
Table of contents
List of figures 5
List of tables 5
List of abbreviations
Abstract 6
Glossary 7
Introduction 8
Literature review/theoretical framework 9
Methodology 10
Results 11
Discussion 12
Conclusion 13
Reference list 14
Appendix 1: [Interviews and Survey Questions] 15
Appendix 2: [Title] 16
Introduction
Emerging Interest of AI in Education
Whether or not the existing technology can be added to structures with the goals of making them marginally, more efficient and flexible; research on how technology catalyzes towards significant reforms to educational structures, practices, opportunity and betterment of society is success by and large. Constituents in higher education might have been involved in improving teaching and learning; this involves provost, educational leaders, faculty members, and researchers; policymakers; advocates and funders; technology developers; community members and organizations; and, above all, students and their families. Institutional leaders are facing the challenges regarding students who have been historically underserved by an education system. For example, students who are categorized as economically disadvantaged include students from students with disabilities, low-income families, first-generation and English language learners. In an effort to meet the needs of these types of learners, innovative digital learning resources may be incorporated and providers of education may begin to emerge in partnership with institutions, exploring social media platforms, AI integration, offering new internships, models of learning opportunities aligned with industry, job-based training programs. As a result, institutions may incorporate workforce development and occupational training providers, libraries, community organizations, and online learning providers to collaborate and to meet the needs of a broader needs of students. Perhaps, strategic planning for related subjects on social impact is crucial for change that positively represents an underserved population facing a pressing injustice or challenge, such as climate change, human rights, or the education gap. Whether or not technology such as AI may significantly impact the social stream through the media, institutions are compelled to offer academic support that prepare students for the betterment of lifestyle and workplace. Today, the emerging technology in higher education has used innovative approaches they believe deemed to be safe, effective, and scalable. Such innovations as AI-powered services including voice assistants in homes; tools that can correct grammar, complete sentences, and write essays; and data management. Educators have explored the opportunities to use AI-powered capabilities in speech recognition to increase the support available to students with disabilities, multilingual learners, and learning resources that can easily be adapted into their digital teaching tools.
Whether the risk involved in using the technology outweighs its usefulness, powerful functionality can also be accompanied with new data privacy and security risks. For example, it's been reported that automations created by AI may amplify unwanted biases to produce output that is inappropriate. Undoubtedly, harnessing the good to serve educational priorities while also protecting against the dangers that may arise as a result of AI integrating its features is a shared responsibility. Nevertheless, the ongoing updates and changes in technology also require new competencies and new skills, institutions may accommodate significant progress in providing resources respectively. Features of new generative AI chatbots have been explored for an array of learning and teaching features including writing essays, creating lesson plans, producing images, creating personalized assignments for students, and social media. This research study focuses on the facets of AI, technology use, how different perspectives, opinions and ideas contribute to students' learning and work readiness. As such, AI policy experts may use research findings to recommend adequate resources and appropriate use of these educational solution tools in technology education.
Understanding Reasons to Address AI in Education
Perhaps perceptions, opinions and ideas from educational constituents may be a good way to gather pertinent data related to understanding AI in education. “I strongly believe in the need for stakeholders to understand the cyclical effects of AI and education. By understanding how different activities accrue, we have the ability to support virtuous cycles. Otherwise, we will likely allow vicious cycles to perpetuate” (Lydia Liu, 2021). Apparently, to articulate concerns and viewpoints that built-in knowledge for best practices and incorporate the tools as a solution to bridge gaps and disparities in education; particularly the underserved students population. Perhaps, execution of the open source to improve communication and collaboration for a more sustainable approach to prepare students for their career and explore opportunities.
Automation is a featured usefulness, facilitating to streamline class assignments and instructional planning more efficiently. Personalized instructions by customized curriculum resources can be easily adaptable for timely task completion; allowing more time spent on effectiveness of teaching. Ultimately, AI operated by humans can create a balance of assisting in human errors while programming machine learning to perform tasks based on specific frameworks. The capacity to do and undo, problem solving and decision-making remains a collective effort to strategic planning on what matters. In conclusion, it remains crucial to review the need of assessment for adequate use of AI in education to realize learning objectives that are beneficial for students' learning growth; while measuring any potential risk.
The Background of the problem
The likelihood that leaders in higher education should play a role in producing work-ready graduates, institutions have accounted for ways to enhance student workforce and professional development. Cloud computing has been a widely known approach used by institutions, and must periodically update their software and services hosted on remote servers, rather than on local servers, machines, or endpoints. As globalization led to increased need for distribution teams, a reason for global higher education leaders to develop collaboration to increase productivity, business success, and employee effectiveness; thus, further exploration was needed on effective aspects of collaboration in distributed settings from the employee and leader points of view (Ogren, T. A. (2016) .
This is an awakening for institutions and instructors using the Learning Management System to be well informed of policies guiding online users to access curriculum, update the learning solution or cloud-based program to be interactive and integrated to the current needs of students in higher education. Another imploring learning platform is social media to stream information and network for opportunities.
It is pertinent to note that artificial intelligence is a tool that is adapted in higher education. AI has been categorized as a transformative technology for higher education and the workforce in our society today. Whether or not it may be expensive to maintain remote learning accessibility for students, it may be cost effective to be equipped with updated cybersecurity defense against malware. Cybersecurity analysts use data analytics, digital marketing, automation, IT support, search engine optimization, design; to maintain the confidentiality, integrity, and availability of their internal systems; and information to safeguard against threats like fraud and phishing; and unauthorized access and to create and implement solutions should a threat get through. In higher education using a robust learning management system to analyze and track students' performance of task submission and grading minimizes human error. The automation of data computation and scheduling propels effectiveness in time management. Cybersecurity prones students to trust in ensuring privacy and minimizing potential cyber bullying. The institution has an obligation to ensure adequate resources for Security Information and Event Management (SIEM) tools, Intrusion Detection Systems (IDS), communication, collaboration, analysis and problem solving. It is imperative to protect digital contents and data and tackle potential security breaches. Adequate measures to be equipped and be proactive in evolving threats. Such investing in robust cybersecurity measures may be a comprehensive way to adapt to technological solutions with organizational policies and procedures. Likewise, training and updates are crucial to keep faculty members informed about the latest threats and equipped to recognize and respond to security incidents effectively.
Recently, there has been a paradigm shift in how faculty members use technology in the university classroom, despite expanded access and implementation there has been little attention paid to student data privacy concerns.
The problem is that faculty members are expected to use the latest educational technology, but technology standards are not current for preparing students for the 21st century workforce.
In this qualitative case study, measurements of the individual's perspectives on the emergence of artificial intelligence in higher education, and social streams as an integral part of shaping instruction to influence relationships building for job readiness are accounted for.
In today's world, remote accessibility for projects using collaborative software or groupware is application software that facilitates teamwork on a common task to attain their goals. For example, interactive editing platforms allow multiple users to engage in live, simultaneous, and reversible editing of a single file document. It is a version control or revision control and source control platforms, which facilitate for users to make parallel edits to a file, while preserving every saved edit by users as multiple files that are variants of the original file.
Artificial Intelligence (AI) is noteworthy to understand that it has the capacity to captivate the imagination of humanity for decades, certainly with extensive innovative research has lent to more development of boosting productivity in business and capable of understanding workload to be seamlessly attainable. Unequivocally students in higher education preparing for their career may be intrigued to understand their career paths exploration of AI social stream tools for professional development and adapt to emerging technology curriculum requirements. These questions are structured specifically to gather information about attitudes, opinions and perspectives about using technology in higher education.
Perhaps, it begins with the awareness that many people who have not explored the advancements of AI, "the interplay between myth and reality has led to misconceptions about AI's true nature and role in our lives." The provision of adequate utility of technology in higher education may be a good alignment in curriculum development in higher education. For example, instructional research and exploration of utility to dismantle some myths surrounding AI, shed light on the facts that may align to performance in higher education, and underpinning this transformative technology. Respectively, social media is a platform individuals have used to network and explore the job market; as such, incorporating technology for career exploration may be valuable in improving professional relationships building for interns.
Research has addressed the misconceptions to prove AI's potential, limitations and ethical implications. For instance, research accounts for its impact on employment to its diverse applications across industries, has shown to be evidently that "AI is a versatile tool that when wielded responsibly, can enhance human capabilities and drive progress in ways previously unimagined." Perhaps this is in part the reason for this research to consider these highlighted features of AI in the workforce in the context of better preparing students for their career.
The subject matter of social stream media is the focus of the research study. In the design of a qualitative case study, this research intended to conduct an investigation on the use of technology with a focus on social media platforms. The findings of the research study established that using social media platforms may be an influencer for promotion and building relationships.
Prior to the revolutionary era of social media, the social way of interaction was traditional and with innovation, creativity and digital creators shifted how people seek to communicate and develop relationships. It is notable to discuss transparency and collaboration as a reference of the media and social stream. It is crucial to decipher and lay out the key elements of trendsetter and the emerging technology in our society.
The logistics of time spent on using its platform defined the scope of the research question of What are the perspectives of social media users and influential relationships. In a collegial relationship approach, key stakeholders may minimize any resistance to adaptation to innovative digital tools and boost their enthusiasm for embracing the upgrades. Of course, a gradual introduction of the new adaptation allows for seamless transitions, while addressing any issues as they arise and ensuring a more controlled and manageable upgrade process. Ultimately, fulfillment of tasks in updated IT requirements and strengthening a foundation for future growth and innovation means a collaborative planning and a strategic approach for secure, efficient, and scalable data management and cyber security measures. Currently what social researchers have revealed about technology is that it is categorically often used as a solution, business tools, and creative resources. Existing research depicts a broad spectrum of images, sounds, text and advanced features to provoke and stimulate people to attend to the entertainment.
This research on integration of technology into the higher education curriculum has been thoroughly researched; the breadth and depth of prior work in how teachers demonstrated knowledge of the content area support the notion that students' instruction is expected to be rich, interactive and relevant to meet the standards. This is crucial to the quest of understanding the answers to the research question. As noted in Stein and Jean (2021) articles about solving problems in education have been solved by eradicating the roots of the problem being studied, its scope, and the extent to which previous studies have successfully investigated. Substantially, where gaps exist this current study attempts to address the needs.
Given the trends, rapid growth, and development of solutions and tools, additional research would offer insights and add on to the content knowledge of its impact on audiences and participants.
Significant of the study
This is significant to understand the implications of AI in higher education respectively to streamline data for social tools geared towards career readiness. It is noteworthy, the solution of a digital transformation must encompass the foundation of specific goals, needs, and interests of the impact on students' learning and success. Burnett, C. A. (2021). research revealed that college students have not graduated with capabilities beyond academic competency that facilitate their professional success post-graduation. First, it's important to understand students' career readiness in respect to the curriculum and emerging technology as shown here in this qualitative research examination of students' experiences in higher education preparing for their career and adapting to emerging technology curriculum. In fact, researchers posited that academic and industry specific knowledge alone is inadequate to secure graduates an occupation and meet the demands of the contemporary labor market Burnett, C. A. (2021). Second, AI offers a number of tools that are adapted across authoritarian governments, ranging from smart spyware, face recognition and voice recognition, enabling widespread surveillance (2021). It's known to make authoritarian centralized decision-making and problem-solving.
AI researchers have implemented and integrated vast problem-solving techniques, not limited to search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics. Second, AI capabilities lead to this query on ways students in higher education interact with AI social stream tools for professional development, as noted by students' perceptions of AI social stream tools usefulness for professional development in higher education. AI also impacts upon philosophy, psychology, linguistics, neuroscience and many other fields.
For a number of years, movies projected AI in derogatory ways to lead us to believe that AI was evil. Likewise, there's been reports about machines replacing numerous jobs from people, resulting in unemployment, poverty, and periods of crisis, reminiscent of the industrial revolution. There is a belief among educators that effective teaching strategies require planning; perhaps, involving students to participate may enlighten the approach to the rigor.
In quest to understand the responsibilities of higher education leaders in focusing alumni perceptions of what higher education experiences best prepare them for the workplace is also crucial data. Presently, with remote accessibility students and faculty members can collaborate on tasks remotely. For example, interactive editing platforms allow multiple users to engage in live, simultaneous, and reversible editing of a single file document. It is a version control or revision control and source control platforms, which facilitate for users to make parallel edits to a file, while preserving every saved edit by users as multiple files that are variants of the original file.
This current research seeks to understand the myths about AI to shed light on the facts that may eradicate misconceptions and bring to awareness of its potential, limitations and ethical aspects of its usefulness in higher education. It is relevant to note that artificial intelligence is a tool that is adapted in higher education. Likewise, there's been realization that AI tools are available "to assist teams in performing tasks faster, easier, and more accurately, thus enhancing productivity, efficiency, and overall performance." Consequently, it became evident that AI may be an integral part of the workforce.
A qualitative case study research method is designed to measure the perspectives on the emergence of artificial intelligence in higher education, and social streams as an integral part of shaping instruction to influence relationships building for career readiness. A recent report showed that AI creates jobs as companies invest in new roles to manage, maintain, and develop AI technology. This is relevant to align with this research to better prepare students in higher education, curriculum development and internships may begin to address new job opportunities, such as data scientists and machine learning engineers.
Artificial Intelligence has evolved to specialize in various field industries, academic enrichment activities, and scenarios, augmentation performance, development, efficiency for a wide range of structures of organization. Therefore, appropriate alignment with career exploration using AI needs to be referenced for its AI autonomously applications utility and solutions, simplifying complex scenarios and predicaments, as programmed with machine learning specifically for the industry in line with specific fields. For example, AI that is used in healthcare helps medical practitioners in diagnosing diseases, predicting patient outcomes, and personalizing treatment plans. Students in higher education must be prepared and offered a rich content based on how medical images can be analyzed by AI-powered systems to detect abnormalities. In retrospect, the implications of task performance using technology is an integral part of the curriculum.
Key elements of transforming learning in higher education are crucial for this research regarding students' career readiness experiences in higher education and emerging technology curriculum. An interactive media platform with AI utility may be incorporated. This is simply because AI is known for communication capabilities such as answering questions related to content specific features, analyzing the intent and sentiment of the conversation response and connecting interactive modes as virtual assistants. It is not known if students who perceive AI social stream tools as productivity for professional development while studying in higher education to better adapt in the workplace.
As AI continues to evolve and advance towards more accessibilities, its adoption across diverse industries is expected to continue to expand for their own unique solutions. Presently, AI is known for its potential to streamline processes, researching, actively utilized in numerous sectors, ranging from healthcare to financial services and retail provide valuable insights for informed decision-making. In an effort to create equilibrium and ensure the credibility of the research, in the design of the research questions, and data analysis, the researcher will limit biases.
Purpose of the research study
The purpose of this research is analyzing remote learning accessibility to team collaboration task performance, and is in part because contrary to common belief, AI is known as a technology to access, to use responsibly and managed by humans within regulatory or organization frameworks of ethical practices to mitigate negative applications. Human oversight governs the actions of the AI bot, which can also be deactivated by its human operator. AI may be automated for the systems that use face emotion recognition, which plays a pivotal role in detecting human emotions of tiredness, and frustration.
Faculty members and educational management in higher education have the responsibilities of acknowledging the evolution of AI as an ongoing narrative, and by separating fact from fiction, and be poised to script a future that balances innovation, ethics, and human ingenuity in unprecedented ways. Within this frame the examination of the questions that are structured on these central aspects are relevant to note that artificial intelligence is a tool that is adapted in higher education. This transforms AI into a valuable tool, in this qualitative case study research study is designed to measure the perspectives on the emergence of artificial intelligence in higher education, and social streams as an integral part of shaping instruction to influence relationships building for career readiness. These elements offer a multitude of advantages and options for improving curriculum development in higher education across various domains, whether it's internships, career planning, administration, or other needs of employees or clients, it is important to understand criterias to students' career readiness experiences in higher education and their adaptation to emerging technology curriculum.
In an era filled with innovation and creativity of technological marvels, AI emerges as a beacon of both promise and intrigue for students in higher education to use as a learning tool. Many researchers have unraveled myths and offered facts to illuminate and underscore the paramount importance of research and diligent stewardship when navigating the AI solutions. As AI continues to appear in various facets of our existence, it’s imperative that we embrace its potential while also remaining vigilant against its potential pitfalls. For the betterment of our society, educational management harnesses its capabilities, recognizing AI as a tool of empowerment rather than an adversary to better students in higher education.
Further communication functionality of AI revealed that conversational AI-based chatbots use natural language processing (NLP) to understand sentence structure, analyze knowledge, and enhance their capacity to respond to questions effectively. AI is the proficiency of an ability to program responses based on a comprehensive understanding of an organization, its participants, and the context in which inquiries are made. Rather than relying on pre-programmed responses, these AI-powered chatbots first understand the user's intent before providing relevant answers. This process is based on available data and reflects the education and training that framework AI utilization and practices, enriching user experience and oversight in AI-generated content.
Recent studies by IBM, (2022) shows that AI as part of their foundational sustainability efforts. Students point of views about AI social stream tools for professional development in higher education is a component of this research.
AI's role in organizational sustainability initiatives is growing with two-thirds of businesses currently using or planning to use environmental pressures and the inherent advantages make AI adoption appealing across many organizations. AI is a tool for any team to use to increase results, its utility encompassing techniques, applications, and limitations of computer systems emulating human intelligence.
Conclusion
As divisions of student affairs at most postsecondary institutions across the country support students’ academic, personal, and professional development; it is noteworthy to facilitate student professional development through on campus jobs, internships, and field experiences. In fact, AI is categorized in types of AI target specific tasks, such as data entry or customer service automation. Hence, it's important to integrate AI's multifaceted applications and capabilities to gather data from the internet, offering incredible potential across numerous applications, spanning various industries, including healthcare, finance, and the arts.
While AI lacks independent thinking and the ability to make decisions; it requires human judgment and cannot replace human labor in sectors where caregivers, psychologists, and lawyers operate.
Literature review
This is the literature review presenting research on the topic of emerging technology in higher education. Based on IEEE-USA Board of Directors (2017) AI related to theory and development of computer systems able to perform tasks normally requiring human intelligence such as, visual perception, speech recognition, learning, decision-making, and natural language
processing. Artificial intelligence (AI) refers to the intelligence of machines or software operated, as opposed to the intelligence of humans or animals (Jean, L. 2021). This accessibility operates remotely and draws to this research development. According to Bloomberg (2017) low-skilled jobs are at risk of automation; and require many industries to invest in the emerging growth of technology. As such, it's reported that AI is capable of revolutionizing the workplace in an entire new class of knowledge workers, preparing for the digital transformation of reskilling imperatives. Computer scientists develop and study intelligent machines to perform human-like tasks, and these machines are known as AIs. A wide range of industry, government, and science throughout the internet use AI technology.
Friedman, L., et al. (2021) emphasizes AI from the perspective of an algorithm that pursues a goal related to a computational method, and made to act independently towards a goal based on inferences from theory, or patterns in data.
This is prevalent in systems and tools that identify patterns and choose actions to achieve a given goal based on pattern recognition capabilities and automated recommendations. Such features may be integrated in various ways to perform advanced features not limited to applications of advanced web search engines, understanding human speech, self-driving cars, generative and creative tools. Overall AI is capable of research including reasoning, knowledge representation, planning, learning, natural language processing, perception, and support for robotics.
The reviews analyze remote learning accessibility platforms and cloud based to gain insights and understand the answers to the research questions based on the perspective of intelligence augmentation denoted that “augmented intelligence is a design pattern for a human-centered partnership model of people and artificial intelligence (AI) working together to enhance cognitive performance, including learning, decision making, and new experiences Gartner (n.d.). First, it gathers in-depth knowledge pertinent to higher education curriculum, emerging technology, and its contributions in preparing students for the workforce. Nishimura, J. A. (2014) conducted an assessment of college and career readiness through the senior project program. This study provides an in‐depth review to gain a deeper understanding of College and Career Readiness suggests that there is an intersection among individual perceptions of College and Career Readiness and College and Career Readiness skills. This is a quest to understand whether or not students' career readiness experiences in higher education are aligned with emerging technology curriculum.
Second, it offers an analysis of how students in higher education interact with AI social streams for job readiness and professional development. This is the second part of the inquiry of students' precepts of AI social stream tools for professional development in higher education. On the one hand, there's been reports about the disruption of machines replacing numerous jobs from humans, resulting in unemployment, poverty, and periods of crisis, reminiscent of the industrial revolution. On the other hand, there's a new understanding of the myth that AI is controlled by humans to eradicate misconceptions and bring to awareness of its potential, limitations and ethical aspects of its usefulness in higher education. These research offer knowledge and expertise for the enlightened of this current research.
AI may assist teams in performing tasks faster, easier, and more accurately, thus enhancing productivity, efficiency, and overall performance. This is a qualitative research method that analyzes the potentials of AI social stream interaction with students in higher education and career development. In doing so, a standard procedure in publishing scholarly research is selected and reviewed for adequate resources because it is evident that AI is an integral part of the workforce.
Research measures that AI creates jobs as companies invest in new roles to manage, maintain, and develop AI technology. In a peer-review process of which scholarly articles have been submitted, research on the topic of technology education has shed understanding (Skidmore and Jean, 2021). This current research measures students' perspectives, and interactive AI social media to increase job opportunities. This emergence of artificial intelligence in higher education and social streams as interns are structured in part as an instruction to influence relationships building for job readiness. intelligence.
Numerous research from the subject matter contributed to present research on what will add more to what we understand about this particular issue of preparing students in higher education for a better workplace. The many literature reviews focus on shaping the theories about students in higher education, curriculum development and internships may begin to address new job opportunities, such as data scientists and machine learning engineers are denoted in this qualitative research. Several Theories drawn from social sciences discipline to narrow down to a constructive theoretical framework with appropriate alignment of career exploration using AI.
This literature review also intends to be a coherent structure of arguments from a vast approach to gather in-depth knowledge of the subject matter of the "What" and "how" future recommendations are shared. It draws interest for AI autonomously applications, utility and solutions, simplifying complex scenarios and predicaments, as programmed with machine learning specifically for the industry in line with specific fields as solutions in higher education. This is an important justification to gather in-depth knowledge of students' career readiness experiences in higher education and emerging technology curriculum.
Innovative features of technology prone to the advancements of AI as a social stream tools in the media platforms for the capabilities of communication such as answering questions related to content specific features, analyzing the intent and sentiment of the conversation response and connecting interactive modes as virtual assistants. Many businesses have adapted the technology to operate more efficiently. Meanwhile, these tools are controlled by humans and require knowledge acquisitions that may be offered at the higher education level. Congruently, it is crucial to decipher the quest to identify the level of students' awareness for AI social stream tools and professional development in higher education.
The vast number of researchers consider the implications of the findings which may be in alignment with the current research are sustainable. Meanwhile, the literature review presentation may shed new understanding and evolve as a milestone. AI continues to evolve and advance towards more accessibilities, its adoption across diverse industries is expected to continue to expand for their own unique solutions. Consequently, students in higher education engaging in social media may stream video lectures, documentaries, social stories and other forms of remote learning accessibility with the integration of AI for its known potential to streamline processes, researching, actively utilized in numerous sectors, ranging from healthcare to financial services and retail provide valuable insights for informed decision-making.
Other matters related to this literature review consider elaborative and descriptive data on the number of previous research demonstrating the results, and decipher key findings from relevant studies. For example, in higher education it is crucial to disseminate information offering how to use AI responsibly and managed by humans within regulatory or organization frameworks of ethical practices to mitigate negative applications. In turn, students may improve social interaction in the media, and transform AI into a valuable tool.
This qualitative case study research study is designed offering a multitude of advantages and options for improvement curriculum development in higher education across various domains, whether it's internships, career planning, administration, or other needs of employees or clients, it lends to the better understanding of the research question. As AI continues to evolve in many facets of human professional workplace, and personal existence, it’s vital that we harness its benefits while staying abreast with its limitations. There are several research evaluations which clearly show the strengths and weaknesses of previous research based on the current research question of how higher education curriculum and emerging technology may better prepare students for the workforce. For the betterment of our society, educational management should harness its capabilities, recognizing AI as a tool of empowerment rather than an adversary to better students in higher education.
It is noteworthy to understand capabilities as an interactive learning solution. AI-based chatbots use natural language processing (NLP) to understand sentence structure, analyze knowledge, and enhance their capacity to respond to questions effectively. In addition, as interactive learning resources, AI-powered chatbots first understand the user's intent before providing relevant answers. This is instrumental in understanding AI as a social stream tool for students in higher education for job readiness and professional development.
Open source education is a compelling emerging marketing strategy for universities across the globe to consider as a highlight of any gaps or limitations in existing research. Many people have relied on social media and streamline the news as a source of trends and norms for society. The influence to reach an engaged audience based on demographics, not limited to age, gender, and socio-economic status also are significant data to integrate in a gap in the literature.
Students in higher education may benefit from familiarization with AI as a tool for any team to use to improve performance, its utility encompassing techniques, applications, and limitations of computer systems emulating human intelligence. These examinations of the impact technology further acknowledge AI as categories, target specific tasks, such as data entry or customer service automation. However, AI lacks independent thinking and the ability to make decisions requiring human judgment and cannot replace human labor in sectors where caregivers, psychologists, and lawyers operate.
This current methodological study approach on students in technology higher education offers insights on perspectives of how educational administrators may create an educational infrastructure for students' success in the workforce and career development. An example of research validity may be built on and strengthen existing knowledge with new data. Logistically, an unbiased research approach offers perspectives as data source in problem solving to reach sound decisions. Hence, the findings may be valuable to the proposed solution to an unresolved problem.
The quest to understand how to offer an effective education framework may be open to a theoretical debate. A personalized approach in education may be prevalent in the traditional approach. The way that technology may improve education is considerable in time for adequate assessment. This researcher demonstrates both the benefits and the weaknesses of existing literature; suggests research priorities; and outlines specific implications for higher education policymakers, and faculty members.
The review of literature as the main data sources for the development of the theoretical framework; segments of relevant theory, experiences of participants given for the basis of research methods. These theoretical assumptions as well, leads to the research study into the questions of what and how of the details of the investigation.
Theoretical framework
The theoretical framework of this research is structured to support the relevant theories to add on to the knowledge of technology utility in higher education in this revolutionary era of AI. First, pertinent theories addressing what higher education curriculum and emerging technology contribute to students in their career readiness. Second, the theories explore how students in higher education interact with AI social streams tools for professional development. This framework will draw from review of individual perceptions of College and Career Readiness and College and Career Readiness skills (Nishimura, J. A. 2014). These theoretical frameworks provide a particular perspective, or lens, through which to examine higher education curriculum and emerging technology contributions to students' career readiness.
Moreover, how students interact with AI social media platforms for professional growth. There are many different lenses to account in the construct of the theoretical framework. For example, psychological theories, social theories, educational theories and economic theories to define these research concepts and explain phenomena. It is important to analyze the qualitative case study as the framework of measuring participants' perspective, opinions and insights. In other words, an in-depth explanation of the theories that define the study within a constructed theoretical framework to demonstrate the overall research.
The grounded theories for conducting this investigation of the research including the preliminary elements guiding the current theoretical framework as illustrated herein: (1) This research theoretical framework is based on identifying the construct of key concepts that underpins this research; (2) Organization of the theoretical framework construct based on previous assessment of relevant theories to understand the scope of this theoretical framework; (3) Illustrative diagram to demonstrate how this research fits into existing research
The theoretical framework is research-based, including enlightenments of previous knowledge herein: (1) the nature of the research question; (2) the grounded theories for conducting an investigation of the research. These two main factors form the basis of a theoretical framework section of the research proposal. This research analyzes these potential social stream tools that may be incorporated in higher education from curriculum development to career readiness.
AI at a glance: What is AI in higher education?
AI Knowledge based systems: a human-computer interface, a knowledge base, and an inference engine program.
Machine learning: supervised, semi-supervised, unsupervised deep learning,and reinforcement.
Domains of AI: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science.
Components of AI learning, reasoning and decision making, problem solving, and perceptions.
Optimization improve: decision-making, efficiency, and resource allocation
AI Automation planning and scheduling using computers to automatically plan and schedule actions or events.
Natural language processing is a machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language.
Robotics: Operator interface, Mobility or locomotion, Manipulators & Effectors, Programming, Sensing & Perception,
Computer vision: a field of computer science that focuses on enabling computers to identify and understand objects and people in images and videos.
Based on identifying these key developmental concepts constructed that underpins this research: (1). career readiness; (2). experiences; (3). higher education; (4). emerging technology; (5). curriculum; (6). perception; (7). Social stream AI tools; (9). professional development, a developed research theoretical framework. These are the key terms developed to understand this research study on students' career readiness experiences in higher education and emerging technology curriculum; as well as their perceptions of AI social stream tools for professional development in higher education.
Organization of the theoretical framework constructed based on previous assessment of relevant theories to understand the scope of this theoretical framework: The theories that offer in-depth knowledge shared for better understanding based on the nature of the research of students' career readiness experiences in higher education and emerging technology curriculum. In addition, students' values of AI social stream tools for professional development in higher education is built-into this research.
Boldman and Deal theory of organizational management is an example that informs this current research.
These key terms define and explain relevant concepts of this current research on the demands of strategic transition to a technological, innovative and performance-driven model for higher education learning.
This researcher presents these relevant models that help interpret the findings on elements of effective approach to teaching and learning in higher education.
Illustrative diagram to demonstrate how this research fits into existing research, the theoretical framework is research-based for students' career readiness experiences in higher education and emerging technology curriculum; and their opinions of AI social stream tools for professional development in higher education.
Career readiness
Technology can support career readiness in various industries. For example, google classroom offers a cloud classroom for teacher professional development, enabling educators to create online instructional practices and students may join. In addition, scholarly peer review articles are available to stay updated with the latest educational research and methodologies. Most of all, ethical considerations include ensuring that technology is used to support effective teaching practices and student well-being.
Higher education
In higher education technology can support inclusive education by providing accessibility features for students with disabilities and reaching diverse learning styles. In fact, technology can address potential barriers, biases, and ensures equal access to ethical use. The institution has the responsibility to use industry-leading security measures to keep students' data safe, including advanced malware protections that regularly undergo independent verification of their security, privacy, and compliance controls.
Emerging technology
Technology has the capability to boost productivity in education, ethically. In the 2010s, productivity software began to be more integrated and consumerized than it already was, as computing evolved from daily personal life. In the United States, some 78% of "middle-skill" occupations require the use of productivity software. The emergence of technology may be vast. The primary means of delivering instruction in remote learning in higher education are video presentations digitally within the context of: (1). Collaboration; (2). Communication; (3). Creativity; (4). Collegial. The advancement of AI and deep learning or machine learning that deals with algorithms inspired by the structure and function of the brain is currently the competitive edge for information. Digital literacy is therefore important to adapt as a prerequisite for remote learning in higher education.
Productivity software
Institutions exploring remote learning platforms consider technology to boost productivity in education ethically, may provide tools and resources that enhance learning experiences, uphold ethical considerations and adapt learning management systems. Retrospectively, execution in higher education technology with priority for student well-being, privacy policy, inclusivity, and responsible digital citizenship, educators harness its potential to boost productivity ethically.
Curriculum development
Curriculum development is supported with digital navigating accessibility of vast, instant and filtered information to ensure that it is ethical, accurate, reliable, and from reputable sources. Technology education stimulates and encourages critical thinking skills and teaches students how to assess data sources. Here are some types of videos that instructors may incorporate into their curriculum:
An educational video is a video that is designed to teach viewers about a specific subject or topic.
Video lecture is a pre-recorded video of a teacher or expert delivering a lesson or presentation on a particular topic.
A how-to video (also referred to as a tutorial video or instructional video) teaches leads, users, or customers a concept or skill.
An IT training video is a type of educational video that provides instruction on how to use various types of software or hardware.
An informational video is a video that provides information about a specific product, service, or topic.
An instructional video is a video that provides step-by-step instructions on how to perform a specific task or complete a project.
A synthetic video that is generated using computer algorithms and AI, rather than being filmed with a camera.
A training video that is used to train employees or customers on how to do something.
A tutorial video that provides step-by-step instructions on how to do something. They can be helpful for learning new skills.
Social stream (AI) tools
Social streams with built-in intelligence assistive features like smart compose and autocorrect may enhance collaboration and communication enabling students to interact with peers and educators regardless of physical location. Institutional policies enforcement encompasses fostering inclusive and respectful online communication, promoting digital citizenship, and ensuring privacy and data protection and ethical use of technology.
AI refers to the ability of a computer or machine to learn and perform tasks that would typically require human intelligence.
An AI avatar is a digital representation of a human in the online space. ‘AI’ indicates that the avatar is powered by artificial intelligence.
An AI avatar generator is a tool that uses AI algorithms to create digital avatars that can be used in videos, games, and other applications.
An AI presenter is a computer-generated character that replaces real-life presenters in videos and presentations.
An AI tool is a software application that uses artificial intelligence algorithms to perform specific tasks and solve problems.
AI video is a video that’s been created by artificial intelligence — from scratch, or using an existing video clip as a starting point.
An AI video editor is a type of software that uses artificial intelligence to process and edit video footage.
An AI video generator is a tool that allows users to create video from scratch using AI.
An AI video maker is a type of software that uses artificial intelligence to automatically generate videos.
AI generated-text is a type of text that is produced by artificial intelligence.
Generative AI is a type of artificial intelligence that focuses on generating new data rather than simply analyzing and categorizing existing data.
A generative AI video is video content that is created using generative artificial intelligence models.
ChatGPT is a large language model developed by OpenAI that is capable of generating human-like text.
Machine learning is a field of artificial intelligence that deals with making computers better at understanding and working with data.
Digital creators in higher education may present quality, interactive and engaging educational content, such as multimedia presentations, simulations, and virtual reality experiences. Meanwhile, ensuring that the content is age-appropriate, culturally sensitive, respects diverse perspectives and ethical use.
Assessment of technology in higher education can streamline processes and provide timely feedback to students. For example, algorithms for automated grading systems facilitate ethical considerations including ensuring fairness, transparency, and avoiding biases. Personalized learning may be built into students' experiences tailored to individualize instruction. In addition, the institution has the responsibility to obtain proper consent, privacy policy, ensuring that student data is used responsibly and transparently.
An AI influencer is a social media personality that has been created by AI. They can be designed to look like anyone, and programmed to say and do anything.
An interactive video is a video that allows viewers to interact with the content, such as by clicking on different elements or making choices affecting the outcome.
Video chatbot is a computer program that uses video to interact with users.
Professional development
Digital literacy and online safety is part of enforcing institutional policies to ensure ethical use of technology in higher education. Creating a learning platform designed to teach students digital literacy skills, including responsible online behavior, cyberbullying prevention, and online safety practices.
An internal communication video is a type of video used by organizations to share information, updates, or messages with their employees within the company.
A screencast video recording of a computer screen, typically used for demonstrating software or online tools.
Methodology
Introduction to Research Method
This qualitative case study research method analyzed the research design, participants, data collection, data analyst and the role of the researcher. An in-depth approach to understand what the underlying factors of the research reveals, the value of human existence that reflects a person’s values, ideals, emotions, and intentions.
This researcher considers all conditions related to confidentiality; not limited to identities of the participants remaining anonymous, information shared with the researcher in a relationship of trust and not shared with others, as noted in the consent form.
This chapter describes exactly how this researcher collected data and analyzed the data, facilitating the assessment of the validity of the research findings. First, it provides the research design including pertinent data related to participants. The data collection is provided, followed by the data analysis.
Research design
The research design allows ample time for subjects to attend a series of observational sessions. During that time, the researcher remained neutral and allowed participants to reflect, detail and note their experiences, in a way of introspection, sharing thoughts and compelling ideas that are evocative. This qualitative research design is a case study to add on to previous research on the issue of technology in higher education.
For the purpose of this research, these specific terms were developed (1). career readiness; (2). experiences; (3). higher education; (4). emerging technology; (5). curriculum; (6). perception; (7). Social stream AI tools; (9). professional development; to examine these research questions and to gather in-depth knowledge of: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?"
Participants
Participants of this study are aware of the anonymity and assuring that their identities would remain unknown. This is a case study designed to select eight participants; of which, this small group were invited for a voluntary, non-threatening session. This researcher collected the data through open-ended survey questions to gain a better perspective into higher education curriculum, emerging technology contributions to students' career readiness and students' interaction with AI social stream tools for professional development, semi-structured interviews were conducted with 8 remote learning students. Publicly available documentation was also analyzed to confirm and clarify findings derived from the survey.
For the purpose of this research, an online higher education student was defined as an individual enrolled in a university online. Sample of this research is conducted online involving eight survey participants. Participants of this study are aware of the anonymity and assuring that their identities would remain unknown. Interviews conducted online to gain insights and lasted approximately 20 minutes each. Responses were recorded by note-taking, and eight interviews were also video recorded with consent. This experience is a systematic participation, observation, reflection, introspection, and self-reflexive writing, to achieve rich, detailed, evocative, compelling accounts of human social experience online. This method offered a window into how students' plan their career while studying.
Data collection
The design method of the survey is a series of 10 questions. The data collection related to research questions Entitled: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?" seeks to answer research questions and the participants' experiences, opinions and perspectives. The data collection offers ideas on how students make sense of their social stream experience in the context of their academic and social worlds. It is especially well-suited to exploring experiences perceived as highly significant, such as career milestones, job interview, and relationship approach.
A number of researchers described this method of study as a step-by-step guide to a research method that investigates how people make sense of their lived experience in the context of their personal and social worlds. It lends answers to the queries and about students' academic experiences, which is highly significant to this research and relationship building. A wide range of qualitative data sources are gathered and analyzed to answer research questions that seek to share perspectives, experiences and opinions about higher education academic goals.
Data Analysts
This analysis is a step-by-step guide to the research method that investigates what higher education curriculum and emerging technology contribute to students' career readiness; and how students in higher education interact with AI social stream tools for professional development.
A thematic analysis approach facilitated, analyzing interview and focus group transcripts, qualitative survey responses, and other qualitative data. The information collected from the participants at the interview were transcribed, analyzed, coded, and responses were double checked to ensure accuracy of the data.
It is notable as a four key theme to a research method that investigates how students make sense of their social stream experience in the context of career readiness and professional development; not based on generalizations. Each theme was examined to gain an understanding of participants’ perceptions and motivations. In the social realm, social sciences often categorize data in the context of their personal and social worlds. "...a qualitative method that investigates how people make meaning of their lives and experiences in both social and cultural contexts," facilitated the data collection of this analytic into coding and themes. In doing so, it is organized for future researchers to access or use for the advancements of the field studies. Thereafter, the data is analyzed within this qualitative framework.
The measurements required basic material such as online accessibility to the online survey questions through the designated URL. Publicly available documentation was also analyzed to confirm and clarify findings derived from the survey. The participants completed the questionnaire anonymously and their identities are not disclosed to ensure confidentiality. It is noteworthy to account for the challenges of conducting the research and how it became possible to complete the process. Overall, this approach was enlightening. The participants were informed that the completed research would be available and notified of the publication.
Role of the researcher
The role of the researcher is primarily to investigate and examine pertinent information related to cloud based approach and remote learning within the framework of understanding the information of the research questions of (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?" As an analyst of this qualitative research, it required examination of the actions and interactions that take place in web video conversations, phone calls, texts, media files and various forms of media. In an effort to create equilibrium and ensure the credibility of the research, in the design of the research questions, and data analysis, the researcher limits biases.
Assumption of the study
The researcher makes an array of assumptions based on the directive, theories and pertinent data sources; including ensuring the reliability and validity; all of the terms defined accurately and are relevant to the study; as an in-depth examination of the research problem. For example, this researcher made assumptions that the public documents analyzed were accurate and updated to confirm data from the survey. This was the best approach to answering the research sub-question: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?" Hence, the assumptions of the research is not limited to variation of demographics data, ensures confidentiality of participants, and opinions shared as not generalized.
Limitation of the study
The limitation of this study may vary in consideration of the circumstances, not limited to: non circumvent events such as illness, relocating or finance; inadequate time to revisit unresolved issues; language barrier, culture, gender differences. Here are two main limitations of the research: First, whether or not participants are genuine respectively to the higher education curriculum and career readiness. Second, students in higher education interaction with AI social stream tools for professional development.
Results
This introduction of the result is a formal presentation to equally share and ensure the credibility of the research, in the design of the research questions, and data analysis, the researcher will limit biases. When asked about recommendations for ethical use of digital learning and for career opportunities, the respondents tended to believe that career opportunities themselves are not inclusive in higher education curriculum, but agreed that students completed internships are involved in job exploration and professional development. It is an add on to the present outcome of this research; a qualitative approach that examines the actions and interactions that take place in this qualitative case study as various forms of media.
The criteria used to identify career readiness included curriculum adaptation to technology emerging, and students' interaction with AI social streams. One respondent (female, 25) explained a difference in higher education curriculum to offer job exploration opportunities:
“The recommendations I would make for ethical use of digital learning and for career opportunities are inclusive skills and project development in industry specific. Mainly, students would have better adaptation when entering the workforce as professionals and perform better."
This points out how individuals’ stories are shaped by the categories they inhabit, such as gender, race, class, and sexual identity, and it preserves the voice of the individual through a close textual analysis of their storytelling. Responses suggest career exploration in higher education technology is a significant integration for students' preparation for the workplace.
Findings
The results of the findings of this research are reported concisely and objectively, without interpreting their meaning. The survey responses transcripts are discussed respectively, and the report of the results is relevant to the research sub-questions to (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?"
In consideration of the enormous data presented, this researcher would conclude based on the results of the inquiry. The findings of the research on the subject matter students' career readiness and innovative digital uses for professional development in higher education has added to the existing knowledge about the process of integrated social stream tools in higher education curriculum.
Tables 1: list of tables Social Stream tools and promoting professional relationships for job readiness are used to help understand the results in a concise overview.
Graphs and charts 2:list of figures auto-generated Technology in higher education and students workforce readiness is designed to visualize patterns and relationships.
Summary of significant findings
Summary of significant findings presented in this research examination delve into the meaning of social stream tools, career readiness and relevance in higher education technology curriculum for students' professional development. These are relevant sources to put this result in the context of social stream AI tools utility in alignment with professional development. It is relevant to note that artificial intelligence is a tool that is adapted in higher education curriculum development. This is a brief account based on key elements of the research and this researcher's own interpretations of the previous literature reviews of research on the subject of emerging technology in the workplace, and as utility of productivity tools.
Research question
These are the questions structured specifically to gather information, attitudes and opinions about this qualitative research sub-questions: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?"
conducted remotely, involving anonymous students in higher education. It gives accounts for how previous research methods are applicable to current qualitative research. Overall, the result relates to the question as an add on to the knowledge of previous research on the impact of technology in higher education.
The results encompass underlining research questions by key themes. In other words, a thematic analysis to indicate the approach of analyzing the qualitative survey responses, and other qualitative data into legible format to be able to decipher its constructs. This researcher analysis of data approach included:
Make general observations about what the data showed.
Mention recurring points of agreement or disagreement, patterns and trends.
Highlight individual responses that were particularly noteworthy.
Support with direct quotations.
The goal of this researcher is to present this thematic analysis applied to interpreting the data, and facilitate an approach to large data sets more easily by sorting them into broad themes. The interpretations were based on themes broader than codes and to combine several codes into a single theme. This is in accord with the research sub-questions. (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?"
A series of six steps developed by Braun and Clarke is followed. The first step is the researcher familiarized with data to get a thorough overview of all the data collected. The second step is to code the data by highlighting sections of the text. The third step is generating themes by looking over the codes created, identify patterns. The fourth step is to review the themes that are useful and accurate representations of the data. The fifth step is defining and naming themes with a succinct and easily understandable name for each theme. (1). Students' career readiness experiences; (2). Higher education curriculum; (3). Emerging technology and professional development; (4). Perception of AI social stream tools. The sixth step is writing up the analysis of the data.
As illustrated in this thematic analysis drawn from the research questions: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?"
Theme 1. Students' career readiness experiences
Technology can support career readiness in various industries. For example, google classroom offers a cloud classroom for teacher professional development, enabling educators to create online instructional practices and students may join. In addition, scholarly peer review articles are available to stay updated with the latest educational research and methodologies. Most of all, ethical considerations include ensuring that technology is used to support effective teaching practices and student well-being.
Research question (2). "How do students perceive AI social stream tools for professional development in higher education?"
Theme 2. Higher education curriculum
In higher education technology can support inclusive education by providing accessibility features for students with disabilities and reaching diverse learning styles. In fact, technology can address potential barriers, biases, and ensures equal access to ethical use. The institution has the responsibility to use industry-leading security measures to keep students' data safe, including advanced malware protections that regularly undergo independent verification of their security, privacy, and compliance controls.
Curriculum development is supported with digital navigating accessibility of vast, instant and filtered information to ensure that it is ethical, accurate, reliable, and from reputable sources. Technology education stimulates and encourages critical thinking skills and teaches students how to assess data sources. Here are some types of videos that instructors may incorporate into their curriculum:
An educational video is a video that is designed to teach viewers about a specific subject or topic.
Video lecture is a pre-recorded video of a teacher or expert delivering a lesson or presentation on a particular topic.
A how-to video (also referred to as a tutorial video or instructional video) teaches leads, users, or customers a concept or skill.
An IT training video is a type of educational video that provides instruction on how to use various types of software or hardware.
An informational video is a video that provides information about a specific product, service, or topic.
An instructional video is a video that provides step-by-step instructions on how to perform a specific task or complete a project.
A synthetic video that is generated using computer algorithms and AI, rather than being filmed with a camera.
A training video that is used to train employees or customers on how to do something.
A tutorial video that provides step-by-step instructions on how to do something. They can be helpful for learning new skills.
(3). Emerging technology in productivity software and professional development
Emerging technology has the capability to boost productivity in education, ethically. In the 2010s, productivity software began to be more integrated and consumerized than it already was, as computing evolved from daily personal life. In the United States, some 78% of "middle-skill" occupations require the use of productivity software. The emergence of technology may be vast.
The primary means of delivering instruction in remote learning in higher education are video presentations digitally within the context of: (1). Collaboration; (2). Communication; (3). Creativity; (4). Collegial. The advancement of AI and deep learning or machine learning that deals with algorithms inspired by the structure and function of the brain is currently the competitive edge for information. Digital literacy is therefore important to adapt as a prerequisite for remote learning in higher education.
Productivity software in institutions exploring remote learning platforms consider technology to boost productivity in education ethically, may provide tools and resources that enhance learning experiences, uphold ethical considerations and adapt learning management systems. Retrospectively, execution in higher education technology with priority for student well-being, privacy policy, inclusivity, and responsible digital citizenship, educators harness its potential to boost productivity ethically.
Professional development in digital literacy and online safety is part of enforcing institutional policies to ensure ethical use of technology in higher education. Creating a learning platform designed to teach students digital literacy skills, including responsible online behavior, cyberbullying prevention, and online safety practices.
An internal communication video is a type of video used by organizations to share information, updates, or messages with their employees within the company.
A screencast video recording of a computer screen, typically used for demonstrating software or online tools.
(4). Perception of AI social stream tools
Social streams with built-in intelligence assistive features like smart compose and autocorrect may enhance collaboration and communication enabling students to interact with peers and educators regardless of physical location. Institutional policies enforcement encompasses fostering inclusive and respectful online communication, promoting digital citizenship, and ensuring privacy and data protection and ethical use of technology.
AI refers to the ability of a computer or machine to learn and perform tasks that would typically require human intelligence.
An AI avatar is a digital representation of a human in the online space. ‘AI’ indicates that the avatar is powered by artificial intelligence.
An AI avatar generator is a tool that uses AI algorithms to create digital avatars that can be used in videos, games, and other applications.
An AI presenter is a computer-generated character that replaces real-life presenters in videos and presentations.
An AI tool is a software application that uses artificial intelligence algorithms to perform specific tasks and solve problems.
AI video is a video that’s been created by artificial intelligence — from scratch, or using an existing video clip as a starting point.
An AI video editor is a type of software that uses artificial intelligence to process and edit video footage.
An AI video generator is a tool that allows users to create video from scratch using AI.
An AI video maker is a type of software that uses artificial intelligence to automatically generate videos.
AI generated-text is a type of text that is produced by artificial intelligence.
Generative AI is a type of artificial intelligence that focuses on generating new data rather than simply analyzing and categorizing existing data.
A generative AI video is video content that is created using generative artificial intelligence models.
ChatGPT is a large language model developed by OpenAI that is capable of generating human-like text.
Machine learning is a field of artificial intelligence that deals with making computers better at understanding and working with data.
Digital creators in higher education may present quality, interactive and engaging educational content, such as multimedia presentations, simulations, and virtual reality experiences. Meanwhile, ensuring that the content is age-appropriate, culturally sensitive, respects diverse perspectives and ethical use.
Assessment of technology in higher education can streamline processes and provide timely feedback to students. For example, algorithms for automated grading systems facilitate ethical considerations including ensuring fairness, transparency, and avoiding biases. Personalized learning may be built into students' experiences tailored to individualize instruction. In addition, the institution has the responsibility to obtain proper consent, privacy policy, ensuring that student data is used responsibly and transparently.
An AI influencer is a social media personality that has been created by AI. They can be designed to look like anyone, and programmed to say and do anything.
An interactive video is a video that allows viewers to interact with the content, such as by clicking on different elements or making choices affecting the outcome.
Video chatbot is a computer program that uses video to interact with users.
This is a thematic analysis to establish the research questions, this researcher collected data from a group of participants in higher education and then analyzed it. First, this researcher applied judgment based on data collection to reflect the interpretations. Second, use deductive approach to the data analysis with preconceived themes based on theory and existing knowledge of curriculum technology in higher education. Third, an applied semantic approach involved analyzing the explicit content of the data.
Interpretation of the results
The results are significant and indicative that technology resources and enforcement policies may lead to new understanding that may develop into further examination and not be limited to new questions or unexpected insights.
The results provided insights on pertinent data findings for consideration of social stream AI tools as resourceful in higher education with provisions of institutional policies.
An alternative explanation for this research findings, including hands on experience in productivity software.
Discussion
Research on the impact of emerging technology and automation have many implications for tomorrow's workforce. “AI brings educational technology to an inflection point. We can either increase disparities or shrink them, depending on what we do now” (Russell, S., 2021). More training is required for skilled workers to meet the job demands. In fact, technology has transformed the workforce in many ways. A number of jobs may have been obsolete as machines get smarter and able to take on more tasks. Unequivocally, more skills are required, and improve work flow through an analytical dashboard.
The Internet and automation have contributed numerous changes to how humans perform tasks. A new survey-based study to encourage leaders to prepare for automation to benefit based on how automation is changing the workplace (Lynn Wu, 2024). Research on advanced technology and automation demonstrates how it leads to more hiring overall, and reduces human error, managers of high-skilled workers may not be required as much. For students in higher education the internet has been a widely used platform for research and using critical thinking to identify credible online sources.
In spite of popular beliefs, other research has shown how automation is reshaping the workplace in unexpected ways. For example, it was found that robots can improve efficiency and quality and reduce costs. Another imploring technology is generative AI known potential benefits as vast and varied, and its applications are limited only by our imagination. The key concern about generative AI is accountability for its creation and the potential for it to be used in harmful ways.
Perhaps, understanding the potential benefits and risks of generative AI, ensuring the responsible and ethical way to use it, may be a greater good for society as a whole. This summary key findings presented in the context of the research questions: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?"
It would be beneficial, through an alternate approach and different theoretical lens, to continue exploring ways that students' career readiness experience or social stream AI tools are integrated for assessment of learning into their professional development.
A number of previous research are consistent, related and validate the current regarding the contributions of higher education towards Career readiness. The results support a major part of the existing theory which stipulated use of curriculum to assist students with career exploration and technology in higher education. Although much of the research conducted emphasizes productivity software in higher education as a dominant tool; particularly, ChatGPT AI has emerged in students' approach to learning.
Not all approaches of using educational technology resulted in equally good performance without adequate guidance and policies. Even though, "educational disparity has been a long-standing social and political concern," and is a grand challenge for social work because of its implications for equal opportunity and social justice; not all students learning with educational technology learned better than those learning without educational technology under all conditions. These results met the expectations and are significant because they identify patterns, and relationships among data and contextualize findings within previous research.
The unexpected results are related to insignificant data about influencing elements of successful networking which offers opportunities for students in higher education. Possible alternatives may be more collaboration between higher education and industries creating opportunities for students.
Acknowledgements of potential limitations
Technology's full potential depends on collaboration across institutions, educational providers, and other key stakeholders to ensure, engage and empower learning, with new types of transformative learning experiences and delivery systems that better serve students of different circumstances. Based on the limitations of technology resources and the enforcement policies new understanding may develop into further examination and not limited to new questions or unexpected insights. Educational leaders and managers are compelled to follow procedures and protocols that are non-threatening, confidential and safe for the entire staff and students. The era of educational technology as one of most revolutionary techniques to employ in modernization and adherence to the codes of conducts; an advanced understanding of the malware approach and intervention, a strategic plan must be readily accessible to be executed for the well-being of the organization. These terms are important to understand and the accountability and decision-making on the best solutions though unique based on the needs of assessments; the awareness of appropriate practices are executed. A cybersecurity framework is an organized, formalized set of processes, tools, policies, procedures, best practices, and requirements designed toolkits for incidents, antivirus software is used to detect, alert, block, and remove these kinds of malicious programs, such as viruses, ransomware, and more. Cybersecurity, securely managing and protecting the confidentiality, integrity, and availability of devices, environments, assets, and data from bad actors. At regular staff conferences the leaders and managers must bring measurements of precautions to awareness and follow the chain of commands developed uniquely designed for the setting; the accountability measures must also include the students proactive participation in social stream geared towards the fulfillment of academics and overall a school which foster progress in the overall community, for the betterment of society. The following practices may be delineated and not limited to other explicit action; rather common knowledge and experience of the safety plan in the event of these potential threats and problems:
Ransomware is a form of malware that infects an organization’s devices and/or systems and locks legitimate users out of their accounts.
Malware is ransomware, spyware, and viruses, software-based attack tools and refers to a huge range of malicious software that attackers use with the intention of harm, exploitation, theft, and other damaging activities.
Phishing is a form of social engineering when bad actors send emails or other message types with malicious links or harmful content to an organization’s users.
In the acknowledgement of the limitation of the sampling size, the researcher generalized the conclusion vis-a-vis the shared data. The limitations of technology may be slow system response causing delays loading times, or lagging applications for workflow. Data processing becomes increasingly time-consuming, it's often a sign that your current infrastructure can't handle the workload efficiently. The network may become congested, causing slow or interrupted internet and intranet connections, it may be a sign that your network infrastructure needs an upgrade.
Regular occurrences of system crashes or server failures may indicate that the infrastructure is struggling to support current demands. An increase in the time and resources required for maintenance, along with the frequency of hardware or software breakdowns, signals that your system is overstretched. Frequent data loss or corruption can be a symptom of inadequate or outdated storage and backup solutions.
Difficulties with integrating new technologies or systems due to software compatibility Issues. Operating system lacks the scalability to grow with your business. Legacy systems may not support new applications or meet modern security standards is a clear sign that an upgrade is overdue. In addition, assessment of the impact limitations had on the research reveals potential and relevant data that accounted for the results validity for the research answers to the questions. In conclusion, using generative AI responsibly may be stimulating, engaging a rapidly evolving field in technology higher education that has the potential to create opportunities and various positive changes in our society.
Implication of Theory
The practical implications derived from the theory of this study is drawn as a conclusion of the theories which are explicitly stated. Based on the research approach that seeks an in-depth, embodied understanding of subjective human existence that reflects a person’s values, purposes, ideals, intentions, emotions, and relationships; it is deemed insinuate that this study may validate the results of the findings. The discussion of career readiness experiences of these students in higher education implied that technology emerged into curriculum and AI social stream tools are an integral part of productivity for professional development. This is related to the results previously discussed in the literature reviews as existing knowledge. As an add on, this research provides sustainable and practical resources for students in higher education to engage within institutional policies in place.
Implication of Practice
This research examined the implications of practices, understanding policymakers in decision-making, researchers, educators and investors' approach to digital learning. Many people embracing technologies for innovation and adaptability want to stay ahead of market shifts, ensuring competitive and cutting-edge. Ideally, proactive planning is absolutely vital to ensure that adequate technology resources are set up as a powerhouse that empowers the institution's growth and evolution of solutions for learning management systems encompassing hardware, software, cloud essentials, data management software, cybersecurity tools, human resources, training, outsourced resources support, maintenance costs, and academic research tools.
In particular, educational technology developers should build learning management systems with easily integrated plug-ins that enable analytics dashboard, diagnostic insights into student learning, progress notes, and generate real-time, actionable data while enabling feedback from students, instructors, and other stakeholders to improve learning outcomes. In practice, an institutional framework often based on a plan for resources has seamless integration capabilities to smoothly incorporate new tools and systems as the organization expands. A focus on prioritizing upgrades based on the impact on achieving institutional goals, even if it is not simultaneously rather allowing for continuous improvements and adjustments as needs evolve. It's important to conduct market research on trends of technology tools that supports their current operations but also propels towards future success. Periodic check-ups assessment to optimize the systems and applications, identifying areas that need updating, uncover potential security risks, and find opportunities to benchmark the infrastructure against industry standards and involve stakeholders, including faculty members, end-users, and management, to ensure upgrades align with real needs and experiences. In education Wiggins, G. (2015) implied formative assessment as a benefit of using AI for the capacity that teaching and learning real-time instructional feedback can be beneficial when it helps learners and teachers to improve. As a measure of accountability, institutions are responsible to encourage instructors and department leaders to review courses with large failure and withdrawal rates, especially large first-year required courses, and employ technology-based applications, tools, and resources to redesign these courses to support student success. One example is Automated Essay Scoring (AES) to become strong writers, which is a good skill for students who need regular and specific feedback. Identifying the cutting edge technology in higher education for transforming learning and workforce preparation is ideal to craft into the internal organizational framework. Productivity and efficiency and cybersecurity tools like data breaches and malware, are crucial in operating digital learning and perhaps, higher education institutions should invest in researching the gaps in leveraging off the benefits of the effective management of technologies to improve teaching and learning. It facilitates streamlined class assignments, automated processes, and efficient data management and analysis.
The tools and capabilities facilitate effortlessly collecting, storing, and analyzing massive amounts of data. Olivier, V. (2011). research on managing mobile learning in a higher education environment demonstrated a general framework to implement and manage mobile technologies in a higher education environment. M–learning is part of a new mobile conception of society, with the mobility of the technologies impacting on the mobility of the students, the lecturers and ultimately on the mobility of higher education (Olivier, V.,2011). Also, the competitive higher education needs to be diligent in maintaining the complex technology infrastructure that supports a thriving mobile culture that will meet and exceed the expectations of both lecturers and students.
Eriksmo, A. (2016). pointed out that understanding the effects of digital technology is important for higher education institutions in order to make good investments in digital technology, and a strategic map of an infrastructure is helpful. It's efficient, making data manageable, improving engagement, and sparking innovation. In addition, implication of practice can be drawn from the demonstration of active engagement of faculty members to contribute to policies relevant to the use of AI and career opportunities for students appropriateness and adequate resourcefulness.
Whereas, a research method that investigates how people make sense of their lived experience in the context of their personal and social worlds implies social norms, it may simply be subject to biases. Alignment of the curriculum should value students' culture and accessibility within the scope of open sources. The institution may seek partnership opportunities to Co-Managed IT Services for Assessment Services, Strategy & Consulting, Procurement task not limited to:
• Systems and Data Integration
• Backup and Disaster Recovery
• Cybersecurity Risk Assessment Services
• Managed Cybersecurity Services
• Server Administration and Management
• Network Monitoring and Management
• Professional Dark Web Monitoring
• Managed Cloud #Infrastructure#Security
• Microsoft 365 Services #Teams#Azure#OneDrive#SharePoint
• Cloud & Data Migration Services
• Mobile and Web App Development
• Managed IT Services
• IT Help DeskSupport
• Virtual CISO Services & Solutions
Implication of policy
The implication policies for AI in higher education as well as an increase of research on ethics, including issues of fairness and transparency, diversity, inclusion and open source are addressed to better understand practices and problem solving methods in higher education. Perhaps, AI may augment students' learning and be more productive in teaching practices in an ethical way. Realistically, technology assists humans within reasons of expectations. Sources such as Blueprint for an AI Bill of Rights (Blueprint) offers guiding principles and practices to reach this objective of initiating AI-related policy activities and use of AI throughout all sectors of society. Similarly, in Europe, the European Commission provides ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Higher education may add these policies into their institutional framework.
The results are indicative for cybersecurity and policies for the governance of the day-to-day operations in higher education. As such, students are likely to establish professional relationships for growth. Open source and open data is crucial for building policies with credibility. Their perceptions would be based on trust and safety for improved social interactions. Furthermore, its implication of policy are inferred based on the principles, organizational framework which governs or stipulates the regulations of adherence; not limited to the daily operation of the institution.
Here's a strategic plan for introducing AI policies
A clear set of guidelines for AI policies must be created for teachers and students. In doing so, research and recommendations for using AI is important to adapt AI policy, and relevant data using infographics must clearly define a strategic plan for the entire organization. It is important to begin with introducing AI policy tools to raise awareness related to pertinent questions addressing how the faculty and students are using the tools, the impact of ChatGPT AI on teaching practices and students performance, concerns of its usefulness and limitations, integration of ChatGPT AI tools into academic policies. For example, posters displayed on bulletin boards as a way of communicating with the entire school community, and interactive assembly of disseminate information and debates in a collegial approach promotes transparency of technology communication related to implement effectively by stakeholders in education.
AI use of technology policy may be implemented in these steps as the established AI foundation, developing faculty, sharing the information with students and parents, reviewing and measuring the process for its efficacy.
1. Establish a Network
Host an introductory conference creating common ground, and reviewing current practices of using technology in educational practices, and AI professional development for key partnering stakeholders including school leaders, teachers, students, and community members in the learning community to draw an AI academic guidelines addressing issues relating to the safety, privacy, reliability and efficacy of their to ascertain if they are fit-for-purpose for the institution
2. Developing faculty members
Host a professional development on how it can support teaching practices and students learning based on AI impacting our lives, how it works, its capabilities and limitations. GenAI tools do not respond to say 'I don't know,' and results in hallucinations or biased results. AI may be overly used by students to do their work and affect their learning experience. Unfortunately, AI tools may not be friendly use for non- native speakers for language assessment, because the Gen AI detector may create positives or negatives to penalize use. AI grading may not always be reliable in assessment due to hallucinations of bias implications of generative AI tools.
Present staff in a professional development session exploring the ramifications of technology in the form of drafted guidelines; and exploring how AI impacts our lives, how it works, its capabilities and limitations, and how it can support teaching practice and students learning ethically as per organizational framework. For example, consider appropriate usage of the technology by identifying assignments and assessments of using the tools; appropriate citations of AI by teachers and students; and address data privacy and security concerns. Feedback on students' learning and teaching practices are likely to be useful for a collaborative setting. This approach facilitates awareness for the instructor to adapt students learning needs including artificial intelligence integration into the teaching plan.
3. Inform students and the learning community
Provide learning resources for students and the community. A collegial approach to share the academic programs and support of the alignment of technology usefulness must be encouraged to revise any changes in a transparent way to ensure that biases will be limited. Ideally, launching a review of the basic literacy and skills necessary for activities on tasks board offer students the opportunities for a better chance to succeed academically. Simultaneously, the instructor benefits from an update of training and learning to effectively implement curriculum.
4. Assess progress for best practices
Adequate accessibility to updated review and reevaluation of curriculum guidelines foster professionalism; and students are likely to engage and advance to meet their academic expectations. Ample time must be considered in the assessment of AI tools, staying abreast with changes, and ongoing training to effectively employ best teaching practices. The entire learning community is equally responsible for the engagement of technology education emerging and trends.
Future research (Recommendations)
There's an immense amount of work in the field of study, experts have collaborated to continue to add on to the future needs. Concerted effort on diversity and inclusion in higher education is an ongoing process and revisited for effectiveness of management. Recommendations are for practical implementation of: These are concrete ideas for future research that higher education institutions more than ever will be accountable to institute policies offering adequate technology and open sources to engage students and better prepare them for the professional societal norms. Roschelle, J., et al. (2006) recommended the use of AI to study the diversity, the multiplicity of effective learning methods and different models to help educators understand what meaningful engagement might look like across various contexts. The institution has an obligation to allow students an adequate learning program that leverages technology and in equity that's deemed to be safe and effective for students.
Concerted effort to modernize society and meeting the academic experiences of students in higher education demand greater involvement of alumni network, meetings, conferences and social events, academic support outreach for all matriculated students not limited to enrichment programs and clubs, creative center to support professionals, continued education and advancements, managerial development of the University. This means data management must include algorithmic discrimination protections, protect data privacy, provide notice and explanation.
Recommendations for AI in higher educational practices: Privacy and data security; Transparent, accountable & responsible use; align to vision for teaching & learning, minimize biases and promote fairness.
Research recommendation phase to transition into studies of AI for Education
Today more institutions are adapting to hybrid learning as a means of flexibility, convenience and a mix of online and in person. Evidence-based technology practices may be reasonable for transparency and tracking instructional progress with technology. For example, cloud collaboration is user friendly for communication, includes dissemination of information and favorable for institutions to implement policies that reward excellent technology-based teaching and invest in professional development by incorporating up-to-date digital learning resources including AI, more inclusive, and in ways that more actively engage learning. Enabling a collaborative and flexible learning environment. Policymakers may support institutions in partnership data sharing agreements and programmatic partnerships, and provide Open Source educational opportunities relevant learning experiences to students, ensuring the privacy and security of student information, to the extent permissible under applicable state and federal law.
Institutional leaders strengthen ways to delegate tasks, collegial relationships with decision-making processes and involvement of equal accountability among stakeholders in education. Teaching practices encompass data analytics, instructional designers, researchers, learning engineers, integration of applications, and learners. Implement collaborative assessment solutions, interdisciplinary research expertise across related disciplines, and improve instruction adaptive in supporting diverse learning styles.
Digital learning assessment tools, consider interoperability elements that allow for secure exchange of student data, evidence-based with communities should provide support around integration of high-quality formative and summative assessments into instructional design. Respectively, practices of adequate data management may require updating for optimization. Technology is known to provide immediate feedback on the effectiveness of course components and the relevance of learning resources, and can help instructors personalize instruction and content of their courses accordingly. AI has been explored as a tool to seamlessly access information, an innovative approach to students' learning experience to support their quest or needs.
Some recommendations are demonstrated here into phases to facilitate awareness and understanding of how to best transition students' cognitive abilities to artificial intelligence. An important recommendation for the Safety Plan and Cybersecurity Goals is critical to be Cyber resiliency or the ability of an IT system to remain operational and provide services in the event of unexpected disruptions, outages, or other unforeseen circumstances. It is the capacity for a system to recover from a disruption quickly and effectively and return to normal functionality.
In the process of integration, students and faculty members must have already been exposed to the basic skills necessary for the literacy of technology to understand the prompts, and literally concepts of its use. In addition to a strong foundation, developing an AI policy, developing the staff and updating educational materials, training the students and larger school community, and continuously reviewing how the implementation plan is going to be able to address and progress.
The ChatGPT Plugins for teachers may help in personalized learning, conduct research, boost productivity with tools, create lesson planning and support students' learning engagement. Empowerment through planning and workshops for the entire school community on the AI policy plan may gear and align with better expectations.
These recommendations are a means for ethical practices in education that written policies for implementation of artificial intelligence are addressed in the organizational framework and consideration for future research.
Framework for practical suggestions, not instructions.
This present research contributed to new understanding of the sub-questions of: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?" It is a revolutionary era for greater understanding of its utility. This is significant research and opportunities for prospective remote learning accessibility to understand the basis and benefits of their education online.
Summary
The investigation of how individual perspectives contribute to the revolutionary era of technology presents facets of the cognitive processes. It is relevant to note that artificial intelligence is a tool that is adapted in higher education. In other words, AI's adaptability has been recognized as a prime reference in which technology can improve learning (Aleven, V., et al., 2016). A qualitative case study research method is designed to measure the perspectives on the emergence of artificial intelligence in higher education, and social streams as an integral part of shaping instruction for career readiness and professional development.
The survey questionnaires focused on examining attention span, retention, engagement and feedback on influences for a 21st century society. It lends itself to answering research questions related to social streams through the use of media in the quest to identify participants' experiences, opinions, and perspectives and motives of engagement. Thus, this qualitative research encompasses a frame to collect in-depth data, embodied understanding of subjective users existence that reflects their values, purposes, ideals, intentions, emotions, and relationships while engaging.
This qualitative research method, designed to select participants to share experiences, values, opinions to understand patterns of behavior and beliefs system. The case study considered three phases to ensure validity of the study.
Institutions should develop a clear vision and strategic plan for the use of technology to enable learning that encourages participation by instructors, students, technology providers and external stakeholders such as community organizations, economic development boards, and workforce system entities. Presidents and senior academic and technology decision-makers should work together to set a clear vision and goals that views technology as an opportunity to augment learning, evaluate and enhance current systems and processes, and establish funding models for sustainable technology acquisition. This could include ensuring interoperability of systems, transparency of outcomes, frameworks for verifying learning outcomes, and providing opportunity for use of openly licensed resources. Institutions should take a systematic approach to technology-enabled innovations, by supporting opportunities for pilot programs with investment in rigorous evaluation of both the technology and the effectiveness of the innovation. Institutions should create strategic networks with leaders at other institutions. Institutions should recognize that learning occurs beyond the walls of a single institution and create partnerships of shared expertise, content, and resources, so that students can take advantage of all the opportunities that are relevant and available. These partnerships will allow institutions to share and scale promising practices and evidence-based strategies for use of technology that improves student learning and outcomes. Institutions should create strategic networks with external systems to develop systems that support lifelong and lifewide learning for students. In a truly all-the-time, everywhere learning ecosystem, learning occurs across multiple institutions and institution types, throughout a student’s life occurring not just in an educational setting, at multiple kinds of organizations, such as non-traditional providers of education, at their places of employment, and in other settings enabled by mobile and portable technology. Leaders at institutions should reach out to a network of local and national stakeholders in the education ecosystem, such as the secondary education system, economic development boards, workforce system entities, community organizations, and nontraditional education providers. These collaborations, including appropriate data and service sharing, will ensure that students can transition fluidly between education systems and from education to workforce, throughout a lifetime of learning
Conclusion
The conclusion that has brought a final answer as technology continues to emerge from the viewpoint of higher learning, more than ever educators and leaders have the responsibilities of offering adequate features of technology and resources to engage students and better prepare them for the professional societal norms. A modern and robust remote learning system is of utmost importance to improve cloud instruction to ensure a competitive edge of efficiency and security of your operations. This study contributes to positive social change by dissemination of information and sustainable provision to support and benefit those in need. Particularly, this research offers updated standards and requirements that can improve pedagogies that will ultimately prepare students for the 21st century skills and competitive global workforce.
This research analysis has answered these research sub-questions: (1). "What are students' career readiness experiences in higher education and emerging technology curriculum?" (2). "How do students perceive AI social stream tools for professional development in higher education?". Educators could benefit from studies that consider the integration of specific technological tools on specific training initiatives. As information on these integration of specific social stream AI tools on specific training initiatives, as information on these issues could help direct appropriate teaching methods and strategies.
As technology continues to be updated, students in higher education settings are accountable for staying abreast with the trends for productivity and professionalism. Also, whether or not AI social stream tools for professional development in higher education may be adjusted with institutional policies, students can be informed of its pros and cons. Based on the main findings and recommendations, no new information or arguments provided in the conclusion. Some pertinent findings of the data showed the extent to which the approach was effective in answering the questions. Based on the limitations of technology resources and the enforcement policies new understanding may develop into further examination and not limited to new questions or unexpected insights.
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Appendix 1: [Interview and Survey questions]
Questions worth asking about AI for teaching: As leaders or faculty members in higher education settings, how AI can improve teaching (along with policymakers, developers, and researchers), encouraging constituents in the ecosystem to reflect on these questions:
This is a short survey questionnaire rating from a scale of 1 to 5. It is intended to examine these research questions: With due diligence, your confidentiality and privacy is respected. There's no need to reveal identity and there's no right or wrong answers.
How would you rate the ethical, accurate, reliable, and from reputable sources of your learning experience?
How would you rate the digital learning experience to boost productivity in higher education ethically?
How would you rate technology inclusion accessibility features for students with disabilities, and reach diverse learning styles, address potential barriers, biases, and ensure equal access?
How would you rate the digital learning experience to present interactive, engaging educational content, such as multimedia presentations, simulations, and virtual reality experiences ethically?
How would you rate the digital learning experience to streamline processes and provide timely feedback to students ensuring fairness, transparency, and avoiding biases?
How would you rate the digital learning experience to personalized learning, ensuring that student data is used responsibly and transparently?
How would you rate the digital learning experience to teach students digital literacy skills, including responsible online behavior, cyberbullying prevention, and online safety practices?
How would you rate the social streams experience to be inclusive and respectful of online communication, promoting digital citizenship, and ensuring privacy and data protection and ethical use of technology?
How would you rate the remote learning management system to boost productivity in education ethically?
How would you rate your overall social stream AI tools for professional development?
How would you rate AI improving the quality of a faculty member's day-to-day work?
How would you rate faculty members experiencing less burden and more ability to focus and effectively teach their students?
How would you rate AI reduces one type of teaching burden to teachers in a manner that negates the potential benefits of AI?
How would you rate classroom AI use providing instructors with more detailed insights into their students and their strengths while protecting their privacy?
How would you rate instructors have oversight of AI systems used with their learners?
How would you rate exercising control in the use of AI-enabled tools and systems appropriately or inappropriately yielding decision-making?
How would you rate AI systems being used to support instructors or to enhance instruction, are the protections against surveillance adequate?
How would you rate instructors able to exercise voice and decision-making to improve equity, reduce bias, and increase cultural responsiveness in the use of AI-enabled tools and systems?
How would you rate AI formative assessment bringing benefits to the student learning experience?
How would you rate the efficacy of classroom instruction?
How would you rate trust in an AI-enabled assessment system, feedback loops, and data generated?
How would you rate users understand the legal and ethical implications of sharing data with AI enabled technologies and how to mitigate privacy risks?
How would you rate AI technologies enhancing rather than replacing human control and judgment of student learning?
How would you rate technology to account for the complex social dynamics of how people work and learn together, or is technology leading humans to narrow or oversimplify?
Short interview questions
Are you currently using AI social stream tools?
Are you currently a higher education student?
Do you think that AI has the capability to replace humans in the workforce?
Do you think all AI are the same?
Do you think AI is bad?
Are you exploring career opportunities?
Are you familiar with productivity software?
Which career platform are you using?
Do you have any recommendations for the use of technology in higher education?
What recommendations would you make for ethical use of digital learning and for career opportunities?
^ Accessibility is subject to specifications and formats.
¡ Content is subject to editorial standard review or collegial review.
¤ Subject to limitations, implications and analytical interpretations.
