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    Half of Higher Ed Institutions Now Use AI for Outcomes Tracking, But Most Lag in Implementing Comprehensive Learner Records

    10/22/24 8:59:00 AM ET
    $INST
    Computer Software: Prepackaged Software
    Technology
    Get the next $INST alert in real time by email

    Survey conducted by Instructure and UPCEA explores the intersection of AI and credentialing in Higher Education

    SALT LAKE CITY, Oct. 22, 2024 /PRNewswire/ -- 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.

    Instructure official logo (PRNewsFoto/Instructure)

    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.

    FORWARD-LOOKING STATEMENTS

    This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended (the "Securities Act"), and Section 21E of the Securities Exchange Act of 1934, as amended (the "Exchange Act"). Forward-looking statements are based on our management's beliefs and assumptions and on information currently available to our management. All statements other than statements of historical facts are "forward-looking statements" for purposes of these provisions, including those relating to future events or our future financial performance and financial guidance. In some cases, you can identify forward-looking statements by terminology such as "may," "might," "will," "should," "expect," "plan," "anticipate," "project," "believe," "estimate," "predict," "potential," "intend," or "continued," the negative of terms like these or other comparable terminology, and other words or terms of similar meaning in connection with any discussion of future operating or financial performance. These statements are only predictions. You should not place undue reliance on our forward-looking statements. These statements are not guarantees of future performance and are subject to future events, risks and uncertainties, many of which are beyond our control, or currently unknown to us. Our assumptions may turn out to be inaccurate and cause actual events or results to differ materially from our expectation or projections. We discuss many of these risks, uncertainties and other factors in greater detail in the Company's annual report on Form 10-K filed with the Securities and Exchange Commission (the "SEC") on February 21, 2024 and as may be described from time to time in future reports we file with the SEC. All forward-looking statements included in this press release are based on information available to us on the date hereof, and we expressly disclaim any obligation to update any such forward-looking statements, except as required by law.

    ABOUT INSTRUCTURE

    Instructure (NYSE:INST) powers the delivery of education globally and provides learners with the rich credentials they need to create opportunities across their lifetimes. Today, the Instructure ecosystem of products enables educators and institutions to elevate student success, amplify the power of teaching, and inspire everyone to learn together. With our global network of learners, educators, partners and customers, we continue to deliver on our vision to be the platform that powers learning for a lifetime and turns that learning into opportunities. We encourage you to discover more at www.instructure.com.

    About UPCEA

    UPCEA is the online and professional education association. Our members are continuously reinventing higher education, positively impacting millions of lives. We proudly lead and support them through cutting edge research, professional development, networking and mentorship, conferences and seminars, and stakeholder advocacy. Our collaborative, entrepreneurial community brings together decision makers and influencers in education, industry, research, and policy interested in improving educational access and outcomes. Learn more at upcea.edu.

    CONTACT:

    Brian Watkins

    Corporate Communications

    Instructure

    (801) 658-7525

    [email protected] 

     

    Cision View original content to download multimedia:https://www.prnewswire.com/news-releases/half-of-higher-ed-institutions-now-use-ai-for-outcomes-tracking-but-most-lag-in-implementing-comprehensive-learner-records-302282854.html

    SOURCE Instructure

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    Q&A

    New
    • What percentage of institutions have adopted AI-driven tools according to the survey?

      The survey by Instructure and UPCEA reveals that nearly half (49%) of institutions have not yet adopted AI-driven tools despite interest in their potential. Among the institutions that use AI, common applications include predictive analytics and feedback mechanisms, with 61% of respondents actively involved in developing learner experiences.

    • What are the main challenges faced by institutions when implementing AI tools?

      The top challenges cited by institutions include concerns about academic integrity (71%), data privacy issues (57%), insufficient training (52%), and the effectiveness of AI tools (52%).

    • How many institutions have implemented Comprehensive Learner Records?

      Comprehensive Learner Records (CLRs) have been implemented by only 3% of institutions, indicating a significant gap in the deployment of these digital resources designed to provide a comprehensive overview of learners' educational experiences.

    • What factors influence the adoption of digital credentials in higher education according to the survey?

      The survey found that 55% of respondents indicated that strategic institutional goals influence the adoption of digital credentials, while 52% highlighted student demand and 45% mentioned employer demand for skills validation as key factors.

    • What does the survey indicate about the gap between interest and actual usage of AI-driven tools in higher education?

      While interest in AI applications is growing, 49% of participants reported that their institutions do not use AI-driven tools at all, suggesting a substantial gap between interest and actual implementation in higher education.

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