Emerging Technology: AI-Enabled Applications for Predictive, Personal Learning

EDUA 6375 - Foundations of Educational Technology

With the rise of technology and the ever-growing need for personalized learning experiences, AI-enabled applications have become a popular solution for many educators and learners alike. As mentioned in the "2023 EDUCAUSE Horizon Report, Teaching and Learning Edition" (2023), “The promise of AI-enabled applications is that they might facilitate a transition from “one size fits all” technology to scalable implementations of personalized learning experiences.”

As communicated in the Horizon Report, many AI tools are designed to offload the most time-consuming teaching elements, such as writing assessments, providing students with formative feedback, and making minor grammatical corrections. The author further stipulates that eliminating these manual tasks through the use of AI will provide faculty more time to engage with students directly, tackling more challenging pedagogical tasks such as synthesizing and analyzing information and creating new knowledge.

Another emerging technology trend caused by low-code and no-code (LCNC) technologies that simplify application development is enabling more people to create content. As this area of no-code technologies expands, they will continue to enable more people to utilize AI technologies to create content. Recent advancements in generative AI create a potential for a drastic change in creative endeavors for faculty, staff, and students. (2023 EDUCAUSE Horizon Report, 2023)

In the article, AI for Personalize Learning: Potential and Challenges, written by Henry Bell (2021), he encourages the reader to focus on the big picture. “In the past decade, the effectiveness of traditional education has been repeatedly questioned. College dropout rates are at an all-time high, which is a testament to disinterested students and the low morale of the student body. According to industry experts, the main reason behind the schools’ failure to keep students interested is the “one-size-fits-all” methodology.” This has been largely created by personalizing learning experiences based on student’s abilities and preferences. Although current tools are falling short of industry expectations, injecting AI into the process has demonstrated promising results. By analyzing student’s track records, AI solutions can detect their preferences and abilities, and teachers and study administrators can use this data to suggest personalized learning methods. (Bell, 2021)

Important to understand

Different methodologies exist for AI technology to be prepared and/or used in education. Therefore, it is important that whatever form of AI is used, the school and teachers are clear on the outcomes they want to produce. For example, “to raise the effectiveness of AI technology, the software must be trained on large data sets. To ensure the ethical collection of data, administrators must inform the students about the facts. They also need to explain how the data is going to be used.” (Bell, 2021) Also, AI continues to change and advance along with significant student learning; therefore, AI learning systems must continue to be fed large amounts of relevant data, so AI efficiency models depend on their creators.

The article"4 Benefits of AI in Personalized Learning" by Mauri (2021) involves passing some control to learners, giving them a way to manage how they progress through their L&D activities:

1. With AI, instead of pre-determined pathways, the learner takes more control over the direction of their learning.

2. AI gathers data to determine a learner's knowledge of specific skills, then creates a constantly evolving learning pathway for him/her to take.

3. AI enhances the learning platform and makes it responsive to learner needs by adapting intelligently to their request.

4. Launch online learning resources whenever and wherever they are needed.

Barriers

AI technology and its applications have again raised privacy concerns. For example, Bell (2021) states, “Before we can utilize the full potential of AI for personalized learning, we need to ensure that the data collection methods are safe, secure, and transparent. As previously mentioned, most of the educators’ problems can be solved by AI. To do this, AI solutions need to be fed large volumes of student data.” Therefore, there must be standards on how data is used and protected so that artificial technology uses only relevant data for its high-function tasks.

Colleagues whisper “unsustainable” and “burnt out” due to a system focused solely on financial expansion. Therefore, with these changes and the circumstances arising, mechanisms must be in place to address burnout and focus on the individual’s mental health and well-being. Faced with ongoing shifts and the end of a journey that seems further away each year, many faculties struggle to keep up, and not for lack of trying, especially after the past three years of teaching in a pandemic. Each new semester brings a new crisis, and faculty have little choice but to adapt, upskill, and pivot. We feel like “victims of the future” instead of having the autonomy to control it. (2023 EDUCAUSE Horizon Report, 2023)

For future reference:

References

2023 EDUCAUSE Horizon Report. (2023). 2023 EDUCAUSE Horizon Report Teaching and Learning Edition.

Artificial Youtube. (2023, June 28). AI In Education [Video]. YouTube. https://www.youtube.com/watch?v=qI9cXMsqtdQ

Bell, H. (2021). AI For Personalized Learning: Potential And Challenges. eLearning Industry. https://elearningindustry.com/ai-for-personalized-learning-potential-and-challenges

Mauri, J. (2021). 4 Benefits Of AI In Personalized Learning. eLearning Industry. https://elearningindustry.com/benefits-of-artifcial-intelligence-in-personalized-learning