Education Technology | Techlist.io

grammarlyApr 30, 20262 min readCurated summary

Educator of the Year

Grammarly’s inaugural Educator of the Year Award honors teachers nominated directly by their students. The first winner, Dr. Humberto López Castillo of the University of Central Florida, is recognized for teaching precise, accessible communication and applying it to public health, technology, and community engagement. His approach combines audience-aware writing, responsible AI use, and hands-on research. ## Student-Led Recognition - Students nominate educators through short videos describing their impact on academic and professional development. - UCF student Vardhan Avaradi nominated Dr. López Castillo for encouraging students to make their language “precise yet accessible.” - López Castillo is a pediatrician, public health researcher, translator, and four-language polyglot from Panama. - His teaching emphasizes collaboration and the connection between individual health and broader communities. ## Communicating With Different Audiences - Students translate complex public health topics for audiences outside academia. - Assignments have included: - Storybooks about mosquitoes for kindergarteners - Monopoly-style games about living with HIV - Rap songs explaining tuberculosis - Podcasts that personalize epidemiology - His medical experience informs this approach: communication must change depending on whether the audience is a child, parent, or professional researcher. ## AI Requires Human Judgment - López Castillo permits students to use AI for drafting but expects them to verify and critically evaluate its output. - When AI-generated citations referenced nonexistent research, he treated the error as a lesson rather than a punishment. - He compares AI to a calculator: useful and powerful, but dependent on the judgment of the person using it. - He and Vardhan are developing a machine learning project using the NIH All of Us dataset, which contains nearly one million de-identified health records. - Their research explores using AI to classify populations and predict health risks. ## Preparing Students for Broader Impact - Students leave with stronger writing, critical-thinking, collaboration, and communication skills. - López Castillo’s teaching focuses not just on adopting new tools, but on using them responsibly and communicating with purpose. - His students learn to reach people beyond academic audiences while keeping human needs at the center of technology and research. The post’s central recommendation is to pair emerging technologies with critical thinking, audience awareness, and a strong sense of social responsibility.

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Education Technology AI Database Design Machine Learning+3

grammarlyApr 16, 20263 min readCurated summary

The Trust Practice: What Building Credibility Requires

Trust in education is not universal; it depends on stakeholders’ responsibilities and the risks they carry. Research across K–12 and higher education shows that AI systems earn trust when they provide clarity about safety, accountability, autonomy, and professional judgment. Effective AI governance must therefore be context-aware rather than based solely on general principles such as transparency or user control. ## K–12: Trust as Stewardship - Educators and administrators prioritize student safety, parental expectations, and institutional duty of care. - Their central question is whether a system will protect students and the institution when problems arise. - Trust grows through clear guardrails, oversight, data protections, and shared responsibility. - Ambiguity around accountability or student information can quickly undermine confidence. ## Higher Education: Trust as Autonomy and Credibility - Faculty and administrators focus on academic integrity, authorship, intellectual ownership, and professional expertise. - They ask whether AI supports or undermines their role as scholars and educators. - Trust is connected to autonomy and the legitimacy of learning itself. - A tool that feels safe in K–12 may feel threatening in higher education because the stakes and responsibilities differ. ## Why Context Matters for AI Adoption - Transparency, explainability, and user control are necessary but do not automatically create trust. - Systems must align with the actual responsibilities educators manage. - Poor alignment can lead to hesitation, stricter governance, and stalled adoption. - The same AI behavior may build trust in one setting while eroding it in another. ## What Educators Need - Educators consistently ask for clarity rather than generic reassurance: - What is the system doing? - Who is accountable when it fails? - How will it affect students, professional judgment, and authorship? - Do educators retain decision-making authority? - Institutional governance, communication, and even silence signal what an institution values and whom it trusts. - Leaders need partners who can acknowledge uncertainty and complexity instead of oversimplifying them. ## Building Trust Over Time - Trust develops through consistent behavior, honest risk management, and meaningful responses when things go wrong. - AI platforms serving multiple education sectors should be context-aware, role-sensitive, and explicit about responsibility. - Design, governance, and messaging that work in one environment may create friction in another. - Treating trust as a universal feature risks overlooking the people accountable for using the technology. AI in education should be designed around the distinct responsibilities of educators and institutions. Trust is not something that can be built once and shipped; it must be earned through clear accountability, contextual design, and sustained partnership.

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Education Technology Data Privacy Ai Governance System Design+3