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  • Writer's pictureAmy Hortop

Emerging Technology Trends

Updated: May 11

This post will examine two emerging technology trends from the 2023 Educause Horizon Report: Teaching and Learning Edition (Educause, 2023) as part of the coursework for EDUO 652.


Generative AI

Generative AI is an algorithm that generates new content, ideas, or data patterns (Educause, 2023). A model “learns” by training on large datasets, making it able to generate predictions (McKinsey & Company, 2024) for text, images, music, and more. Generative AI is relatively accessible now and can be used by a wide variety of users: content creators, educators, businesses, and researchers in their professions, as well as anyone using it for personal projects and needs. One of its most significant impacts is offering new ways to automate and enhance creative and analytical tasks. However, a substantial barrier to using this technology is the ethical concerns over protecting content (rights for originality), data privacy, and the potential for the technology to output biased and often wrong information (O'Neil, 2017; Unesco, 2023).


Pictured below is an example of the type of bias that can result from entering a simple prompt into a generative AI tool, such as Chat GPT. One prompt asked GPT to provide a story of an engineer, and a second prompt asked for a teacher's story. The main character of the engineering story was male, and the teacher's story was female, further perpetuating gender stereotypes. However, when I “ask” ChatGPT about these assumptions, it claims it will learn for future requests, generating new predictions.



Figure 1. Screengrab from Chat GPT showing gender of main character in teacher story




Figure 2. Screengrab from Chat GPT showing gender of main character in engineer story




Figure 3. Screengrab from Chat GPT addressing assumptions


There are numerous ways that this technology can be used to enhance educational technology. At the top of the list for potential use in workforce development is the ability to customize learning experiences. In problem-based learning, AI could generate scenarios for learners (Simmens, 2023). For our use in workforce development, it could create realistic, simulated environments where learners interact with virtual manufacturing equipment or virtually install systems for wind turbines or solar panels. Learners could test their critical thinking and problem-solving in a safe, controlled environment. This benefit of being job-ready helps in promoting a skilled and adaptable workforce.

It can also be used to increase accessibility, which is essential for our reskilling and upskilling training in clean energy technologies. It may provide language translation or integrate other accessibility features, which would help Maria and Ryan.


Micro-credentials

Another emerging topic in educational technology is using micro-credentials to demonstrate competencies and skills attained rather than by a traditional degree program (Educause, 2023). Learners can take shorter courses that are more directed to a particular set of skills or industry and typically, in less time and for less money, have a digital badge that shows what skills they have learned through earning the credential.

Micro-credentials often come up as a means to support upskilling and reskilling in workforce development, as micro-credential providers can develop up-to-date content to address specific skill sets rapidly. One of the most significant barriers to using microcredentials is the lack of standardization across different providers or industries and their recognition by industry in place of more traditional degree programs (Varadarajan, et al., 2023). Learners might be affected by this when they complete a micro-credential they expect to help with social mobility (Tinsley et al., 2022) only to find out that not all employees recognize micro-credentials equally, leaving them without the value they thought they were getting. Moreover, without standardization across providers, industry has concerns about microcredentials’ rigor and credibility.

Although a critical feature of micro-credentials that is touted is their accessibility, they can still be out of reach for some people due to costs, the necessity of good internet and hardware, and even prior schooling. On the flip side, their impact lies in their potential to provide flexible, customized, skill-specific, and industry-specific career paths that align directly with the jobs the industry needs to fill. While micro-credentials have become popular as a potential mechanism for workforce development in clean energy technologies, I don’t feel I’ve uncovered enough evidence yet that they wouldn’t cause more harm than good for Maria and Ryan.



References:



McKinsey & Company. (2024, April). What is generative AI? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai#/


O'Neil, C. (2017). Weapons of math destruction. Penguin Books.


Simmens, E. (2023, June 12). ChatGPT scenario generator. E-Learning Heroes. https://community.articulate.com/discussions/building-better-courses/chatgpt-scenario-generator


Tinsley, B., Cacicio, S., Shah, Z., Parker, D., Younge, O. & Luke Luna C. (2022, March). Micro-

credentials for social mobility in rural postsecondary communities: A landscape report.


Unesco. (2023, April). Artificial intelligence: examples of ethical dilemmas. https://www.unesco.org/en/artificial-intelligence/recommendation-ethics/cases


Varadarajan, S., Koh, J.H.L. & Daniel, B.K. (2023). A systematic review of the opportunities

and challenges of micro-credentials for multiple stakeholders: learners, employers, higher

education institutions and government. Int J Educ Technol High Educ, 20(13).


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