When you have a user base of more than 30 million students worldwide, it’s pretty safe to say your data indicating higher edtech trends is pretty strong. I was fortunate enough to steal a few minutes with Ryan to tap his brain, which included (what else?) the impact of AI on higher education and its potential to save educators time by automating tasks, integrating data, and supporting students—from theoretical concepts to practical applications, with a focus on using AI tools to streamline administrative processes, visualize data, and personalize learning experiences. Have a listen and click through for more Instructure news:
Key themes from the conversation:
- AI’s Role in Education: AI is increasingly being adopted to reduce workloads for educators, streamline administrative processes, and enhance student learning. However, pockets of resistance remain, particularly in K12, due to fears of job replacement and the additional burden of adopting new technologies.
- Applications in Data and Visualization: AWS’s Bedrock large language models and their ability to visualize data, such as breaking down course catalogs into skill clusters, is highlighted as a powerful tool for educators to better understand and improve course delivery.
- Technology Adoption in Higher Ed vs. K12: Higher education is embracing AI and tech integration faster than K12, where resistance remains, but there’s a growing recognition that technology can help manage disruptions and support student mental health.
More news from Instructure:
Half of Higher Ed Institutions Now Use AI for Outcomes Tracking, But Most Lag in Implementing Comprehensive Learner Records
Survey conducted by Instructure and UPCEA explores the intersection of AI and credentialing in Higher Education
Instructure, the leading learning ecosystem and UPCEA, the online and professional education association, announced the results of a survey on whether institutions are leveraging AI to improve learner outcomes and manage records, along with the specific ways these tools are being utilized. Overall, the study revealed interest in the potential of these technologies is far outpacing adoption. Most respondents are heavily involved in developing learner experiences and tracking outcomes, though nearly half report their institutions have yet to adopt AI-driven tools for these purposes. The research also found that only three percent of institutions have implemented Comprehensive Learner Records (CLRs), which provide a complete overview of an individual’s lifelong learning experiences.
Among institutions using AI, typical uses include predictive analytics and feedback mechanisms. Yet, persistent issues like academic integrity, data privacy and inadequate training pose significant challenges. Implementation of digital comprehensive learner records is still sparse across institutions, though some are starting to adopt them. In contrast, digital credentials are increasingly issued and influenced by strategic objectives, student demand and employers’ need for skills validation.
Below are some of the key findings:
- 45% of respondents work in academic technology, 42% in learning design, 16% in information technology and 12% in student support roles. The breakdown by institution size is: 40% from small, 30% from medium and 30% from large institutions.
- 61% of respondents are highly involved in developing learner experiences and tracking outcomes; 36% are somewhat involved.
- 49% of participants report their institution does not use AI-driven tools; 31% do use them, and 21% are unsure.
- Among users of AI tools: 52% use predictive analytics, 52% use AI-driven feedback systems, 39% use adaptive learning platforms and 39% use simulated classroom experiences.
- Top challenges with AI tools include academic integrity concerns (71%), data privacy (57%), insufficient training (52%), and tool effectiveness (52%).
- Among those who said their institution issues digital credentials, 55% said strategic institutional goals have influenced the adoption of these credentials, 52% said student demand for digital credentials and 45% said employer demand for skills validation.
“This research indicates institutional staff recognize the potential benefits AI technology offers, especially for improving student success,” said Melissa Loble, chief academic officer at Instructure. “To address academic integrity or quality concerns about AI-driven tools, institutions can invest in training for staff and faculty on AI-powered tools, enabling education professionals to use them effectively and ethically. Institutions need internal champions who have the freedom and latitude to test the limits of these systems and their impact on learner outcomes and records.”
The Challenges and Benefits of AI in Higher Ed
The implementation of AI-driven tools in higher education is still in its early phases. It’s clear that institutional staff either are still learning how to incorporate the tools into the learning process or are encountering obstacles in optimizing their use. Incorporating AI into academic processes is a recent development, and like any new technology, it often faces initial reluctance and doubts about its efficacy. The introduction of AI in higher education has generated varied reactions, with users seeing both benefits and obstacles. On the positive side, AI can enrich personalized learning, deliver data-driven insights and provide academic support. Yet, challenges such as accuracy, intellectual property concerns, copyright issues and a lack of transparency remain significant considerations.
“Digital comprehensive learner records could act as a passport for learners, allowing them to travel through the course of their educational lifetime, obtaining stamps of knowledge sets and skill bases,” said Bruce Etter, senior director of research & consulting at UPCEA. “As a community, we have work to do to eliminate barriers to creating digital CLRs, such as resource limitations, staff readiness and resistance to change.”
Comprehensive Learner Records (CLR) & Learner Outcomes
Higher education has experienced significant changes over the past few years as institutions have adopted new types of credentials and online learning methods, including integrating AI technologies into their curricula and administrative processes. More students are now opting for badges, certificates and alternative credentials, allowing them to pursue higher education without enrolling in full degree programs. Although traditional bachelor’s and associate degrees declined last academic year, certificates saw a 3.9% increase from the 2021-2022 academic year to 2022-2023.
Survey Methodology and Objective
The survey was conducted by UPCEA and Instructure to better understand how institutions are leveraging AI to improve learner outcomes and learner records. The survey aimed to understand respondent perspectives, challenges and obstacles associated with these systems and the adoption of AI-driven tools. The survey took place from May 13 to June 26, 2024. It was sent to members of both UPCEA and Instructure. Overall, the survey was sent to 4,407 individuals. Eighty-six participated in the study, and 70 completed the entire survey.
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