English Language Arts: Publishing Writing (TEKS.ELA.9-12.10.E) Practice Test

Draft: Debates over algorithmic discipline tools often ignore the difference between predictive accuracy and equitable impact. A system that flags students for "risk" may reproduce historical biases embedded in attendance codes, referral patterns, and teacher perceptions. This draft argues that districts should couple any predictive dashboard with bias audits, transparent feature documentation, and restorative alternatives that avoid punitive spirals. It synthesizes recent quasi-experimental studies, highlights gaps in validation across demographic subgroups, and proposes a governance checklist for district adoption that centers due process and data minimization. While acknowledging constraints on staffing and time, it cautions against delegating judgment to opaque models without human oversight and parent notification protocols. The piece recommends district-level reporting of false positives/negatives and third-party replication before high-stakes use. Intended venue: Peer-reviewed education policy journal; Audience: researchers, state policy analysts, district administrators seeking evidence-based guidance.

Intended venue: Peer-reviewed education policy journal. Audience: researchers, district leaders, policy analysts. Submission expectations: APA 7th, structured abstract, keywords, author affiliations, IRB/ethics note, 6,000–8,000 words with tables. Draft (150 words): Texas districts navigating post-pandemic instruction confront an uneven lattice of access, funding, and accountability. In high-poverty campuses, broadband gaps and staffing volatility compound curricular recovery, yet data from matched cohorts suggest targeted tutoring and schedule redesign can narrow disparities without inflating seat time. Our mixed-methods analysis of five districts across the Panhandle and Gulf Coast triangulates course-taking, teacher retention, and household connectivity to model intervention timing. Results indicate that sequencing tutoring before schedule compression yields higher algebra completion and attenuates ninth-grade failure cascades. Interviews also surface leadership practices—micro-scheduling, transparent metrics, and community Wi‑Fi coalitions—that align fiscal constraints with instructional ambition. Rather than prescribing a universal remedy, we argue for adaptive bundles calibrated to local bandwidth, transportation patterns, and labor markets. Policymakers should weight flexibility mechanisms in accountability rules, allowing districts to pivot toward evidence-linked pacing without inviting perverse incentives. Future research should examine rural consortia and sustainable staffing pipelines statewide.