If you ask PhD graduates with 21 years of education whether they have ever received distinctive, personalized evaluations and detailed feedback from educators, they will likely say no. Almost all students share this sentiment, indicating that personalized, comprehensive analyses have traditionally been lacking due to educators' time constraints.
With the rise of AI, educators can produce generic responses, but how useful are they when they don't reflect educators' opinions? The nuXight method ensures that educators guide AI-generated responses, providing personalized feedback instead of generic ones. This genuine feedback, expressed in educators' own words and enhanced by AI for efficiency, is something AI alone cannot achieve.
Driven by a passion for education, nuXight emerged from a principal's vision to deliver these results. It can save educators up to 95% of the time required, assuming they even have the time.
This feedback helps students build on strengths, uncover weaknesses, and address bad habits, leading to better performance and development. It also aids parents in supporting their children's academic progress, especially for younger students, but benefits all.
School leaders can set mandatory teaching standards on the nuXight platform, allowing educators to deliver reports to parents with just a few clicks. This gives school leaders a holistic understanding of classroom performance, while parents feel more involved and confident in their child's education. When parents see educators improve through periodic reports, they know your school excels in ways other schools do not.
This revolutionary solution is poised to transform students' educational experiences while requiring significantly less effort from educators than the time currently spent producing superficial feedback.
Firstly, can students independently produce their own essays? The answer is yes. Therefore, relying on AI to create essays is detrimental to their learning. Conversely, educators traditionally cannot provide personalized feedback that is in-depth and finely granular, offering only superficial assessments. For instance, a student may spend hours on an assignment, while an educator has only a fraction of that time for evaluation.
Consequently, if educators provide distinctive, personalized feedback with their own insights, classroom-based suggestions, and emphasis on class materials—something only they, not AI, can offer—it would greatly benefit students. Adequate feedback within the classroom is crucial for learning yet is consistently missing.
