Critical Insights for ETS® AI Labs™
The work in the ETS® AI Labs™ is driven by user needs. And, while the future of teaching and learning is nearly impossible to predict, the labs design our visions around the following critical insights.
Learners can be supported through efficiencies in how they access, engage with, and complete educational and workforce readiness programs and the instructional assessments required as part of those programs. Educators can be supported through efficient methods for diagnostic and holistic assessment of learner engagement, progression and performance.
Modes of learning vary as face-to-face environments transition to a mix of less standardized in-person, remote and blended experiences guided by some combination of teacher, parent/guardian and self-facilitation. To meet user needs, learning experiences will require solutions that offer choice, personalization, adaptation, self-pacing and integration capabilities.
Educators, parents and learners can be supported through automated tools when translating rich data captured in digital solutions to actionable insights. Live service models that support data interpretation will be replaced by real-time feedback with recommendations and interactive reporting platforms with bold user interfaces and intuitive user experiences that help guide learning.
Users and decision makers will continue to seek information about what solutions work, for whom and why. Reliance on relationships between use and high-stakes outcomes like summative assessment scores will diminish, however, with decisions being based instead on meaningful evidence that a solution is supporting engagement, persistence and learning progressions.
Policymakers and administrators will continue to grapple with EdTech equity issues such as the digital divide, nonuniform data standards and differential efficacy among subpopulations of students. Information about how learning and assessment vendors are addressing these issues will be expected.
Expectations and regulations around the responsible use of data, specifically how it is collected, handled, stored and applied to technology-enhanced solutions will increase. Transparent communication of data policies will become table stakes.