The Digitized Campus : Artificial Intelligence and Big Data in Higher Education.

Format:

Book

Author/Creator:

Fernandez, Frank.

Language:

English

Subjects (All):

Artificial intelligence--Educational applications.

Artificial intelligence.

Education, Higher.

Physical Description:

1 online resource (212 pages)

Edition:

1st ed.

Place of Publication:

Albany : State University of New York Press, 2026.

Summary:

Introduces readers to the rationale and risks of using AI and big data in higher education and shares novel applications for improving educational practice.Colleges and universities collect--and own--more data than ever before.These data can be analyzed with powerful new tools to support student learning and faculty research.

Contents:

Intro

Contents

1. The Rise of Artificial Intelligence and Big Data in Higher Education

Historical Origins of Artificial Intelligence

Defining Artificial Intelligence and Big Data

The Roles of Artificial Intelligence and Big Data in Higher Education

Potential Impact of Artificial Intelligence and Big Data on Higher Education

Organization of Volume and Overview of Chapters

References

Part I: Legal, Ethical, and Philosophical Considerations

2. Algorithmic, Autonomous, and Artificial: How Big Data and Mediated Actions Reshape the Legal and Ethical Landscape of Academic Research

Privacy

Education Records

Protected Health Information

Records Impacting International Reach

Algorithmic Biases and Other Errors

Data Biases

Legislative Responses

Administrative Responses

Intellectual Property

Ownership or Inventorship

Fair Use or Infringement

Security and Controls

Federal Data Security

International Export Controls

Safety Measures and Anticorruption

Individual Safety and Harms

Unfair and Deceptive Practices

Products Liability

Conclusion

Notes

3. The Impact of Artificial Intelligence on Higher Education: Opportunity, Risk, and Responsible Governance

The Opportunities and Risks of AI

Key Legal Issues

Student Data Privacy

Use Case: AI and the Privacy of Student Mental Health Records

Use Case: Student Surveillance and Exam Taking

Discrimination and Bias

Buying Down Risk Through Responsible Campus AI Governance

A Risk-Based Campus AI Governance Framework

4. Desiring Machines: The Sociotechnical Production of Datafication in Higher Education

Desiring Machines: Creating Social Impulses in Higher Education

Desire, Machines, Desiring Machines.

The Sociotechnical Apparatus of Datafication

Desiring Productions

Truth: Human Capacity Is Measurable

Truth: Preemption

Truth: A Limit of Datafication Might Be Student Cheating

Interlude: Datafication Works Only When It Breaks

Truth, Continued

Truth: Datafication Is Never Enough

You've Gotta Fight for Your Right to Indeterminate Futures

5. Making a Digital Record of Campus Life: The Student Data Warehouse and the Datafication of Student Records in U.S. Higher Education

What Is a Student Data Warehouse?

A Very Brief History of Recordkeeping in U.S. Higher Education

Contemporary Debates on Student Data Systems

Understanding the Student Data Warehouse

Relationships

Effects

Acknowledgments

Part II: Potential Uses to Inform Practice

6. Putting AI into Practice: Applications for Serving Students and Campuses

Elements of an Effective Holistic Learning Ecosystem

Client Relationship Manager and Learning Management Systems

Student Profiles

Enrollment Patterns and Engagement Metrics

Administrative Tasks and Time Allocation

Communication Channels

Surveys and Feedback

Enhancing Student Engagement and Success

Chatbots and Virtual Student Support

Facilitating Peer Connections

Dining Services

Mobile Ordering: A Student-Centric Revolution

Autonomous Food Delivery: The Future of Dining Services

Other Critical Considerations

Ethical Considerations and Data Privacy

Accessibility, Inclusivity, and Student-Centric Design

Faculty and Staff Empowerment Through Training

Continuous Improvement and Quality Assurance

Research and Evaluation

7. Predictive Policing in American Schools and Universities

Predictive Policing in Schools and Universities

Policing and Surveilling K-12.

Policing and Surveilling Higher Education

Implications and Conclusion

8. Artificial Communication and Media Realism for College Admissions

Program Strands in the College Admissions System

The Muppet Model Show

Research on Admissions in the Age of Generative Reproduction

9. Understanding Challenges Repaying Student Loans: An In-Depth Study Utilizing BERT Models for Emotion Recognition and Issue Classification

Analysis of Student Loan Complaints

Text Analysis of Student Loan Complains with LLMs

Ongoing Need for Novel Approaches to Understand Student Loan Complaints

Method

CFPB Data on Student Loan Complaints

Preprocessing Narrative Textual Data

BERT Model

Tokenization

Pretraining and Fine-Tuning in BERT

Semantic Analysis with BERT Emotion Recognition Model

Classifying Topics of Complaints with BERT

Results

Emotion Recognition of Student Loan Complaint Narratives

Classifying Complaint Narratives by Topics

Discussion

10. Promising Applications for Promoting Disaster Resilience on College Campuses

Literature Review

Methodology

Creating a Database of Campus-Built Environmental Data

Web Interface Development

Designing the Web-Based Interface to Collect Data from Campus Stakeholders

Workshop and Data Analysis

Ethical Considerations and Participatory Design Approach

Additional Perceptions of Campus Safety

Characteristics of Safe Places:

Characteristics of Not Safe Places:

Discussion and Conclusion

11. Connecting Theory, Ethics, and Practice: Future Directions for AI and Big Data in Higher Education

Align AI Implementation with Institutional Mission and Values

Upon Careful Consideration of Institutional Values, Develop, and Implement a Governance Plan.

Monitor Emerging Trends in AI and Higher Education and Recognize Opportunities and Limitations

Promote Collaborative Empirical Research to Propel Innovation in the Field of Higher Education

See the Implementation of AI in Higher Education as a Continually Evolving Process

List of Contributors

Index.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

ISBN:

979-88-558-0771-4

OCLC:

1591606020