Relating to the use of artificial intelligence to score certain portions of assessment instruments administered to public school students.
The bill requires that any AI scoring method employed must be trained on representative samples that include students from various backgrounds, such as educationally disadvantaged, bilingual, and special education students. Furthermore, any such method must meet standards of validity and reliability, as well as be evaluated by an independent entity to ensure that it does not exhibit bias. This restriction on AI could impact how educational assessments are developed, encouraging more traditional methods of scoring unless technological solutions can meet the clearly defined benchmarks outlined in the bill.
House Bill 5282 proposes amendments to the Texas Education Code concerning the use of artificial intelligence in scoring constructed responses on assessment instruments for public school students. The legislation specifically prohibits the use of AI-based methods, including algorithms and automated scoring engines, for evaluating constructed responses, making an exception only under certain conditions that ensure fairness and reliability of the scoring method. This legislation reflects a move towards maintaining rigor and integrity in student assessment processes as well as a cautious approach to the implementation of technology in educational evaluations.
While the bill aims to protect students' rights and ensure unbiased evaluation processes, there may be concerns about its implications for the future integration of technology in education. Advocates posit that maintaining high standards in student assessments is vital, yet some stakeholders may argue that the restrictions could hinder innovation in educational practices. Detractors may fear that an unfavorable evaluation of AI methods could limit opportunities to modernize assessment approaches, thereby affecting the adaptability of educational systems to current technological advancements.