Data analytics in higher education

Dr. Joseph Cazier, Clinical Professor and Associate Director of the Centre for AI and Data Analytics at Arizona State University, delves into AI and data analytics in higher education. The rise of AI and data analytics is transforming our world and workplaces, and education must evolve alongside it to prepare students for this new landscape. Institutions like the Centre for AI and Data Analytics are leading the charge, recognizing the need to equip students not only with the skills to succeed in the workforce but also the knowledge to become leaders in shaping the AI-powered world of tomorrow. Today, Dr. Cazier discusses data analytics in higher education.
About the speaker

Dr. Joseph Cazier

Arizona State University

 is a little camera shy

Dr. Joseph is Clinical Professor and Associate Director at the Centre for AI and Data at Arizona State University

Show Notes

  • 01:55
    The role of the Center for AI and Data Analytics
    The Center for AI and Data Analytics aims to educate students and professionals about AI, preparing them for a rapidly changing world and its ethical implications. They also focus on staying at the forefront of research to keep their educational programs relevant.
  • 04:17
    Addressing the educational needs of midcareer professionals in AI
    Continuous learning is a must, and mid-career professionals tend to hold significant influence in organizations. Consequently, they must gain the knowledge and tools to navigate AI effectively and ethically as more organizations adopt AI into their toolset
  • 07:22
    Integrating critical thinking and problem solving into AI education
    The Centre focuses on real-world projects and simulations to teach students data prioritization and how to guide AI. To elevate student thinking, the center focuses on the leadership elements of AI and analytics and how to execute them effectively in the organization.
  • 11:06
    Leveraging AI for personalized learning pathways
    AI in education allows for personalized learning experiences. AI can be used to identify student strengths and weaknesses, curate exercises, and provide learning paths aligned with each student's interests and career aspirations.
  • 14:02
    Success factors in AI implementation
    Success in AI implementation relies on factors beyond technical skills, such as problem-solving, team management, data management, and execution. Mastering these skills alongside technical proficiency is critical to ensure long-term success and ethical AI usage.
  • 17:21
    AI and the evolution of analytics
    AI has led to data science tools becoming more accessible and user-friendly. While coding skills remain crucial for some, the emphasis has shifted towards teaching students how to add value through analytics and how to leverage analytics tools effectively and ethically.

Quotes

  • "Data science today is becoming more like Excel, accessible to all." - Dr. Joseph Cazier

  • "Tools for analytics are user-friendly, enabling non-experts to utilize them." - Dr. Joseph Cazier

  • "In a world where AI can do the lower level tasks people would get degrees in, we must elevate, learning how to take what AI and analytics can do, guide it, and execute on it effectively in the organization." - Dr. Joseph Cazier

About the speaker

Dr. Joseph Cazier

Arizona State University

 is a little camera shy

Dr. Joseph is Clinical Professor and Associate Director at the Centre for AI and Data at Arizona State University

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