writing-assessment
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- PinnedNewsEdSurge15 Jul 2026
How My School Used Common Sense and Collaboration to Confront AI
This news article describes how an Indigenous school's instructional technology coordinator helped teachers confront the challenge of AI-generated student writing through collaboration and common sense. They addressed the phenomenon of 'unproductive success' where students use AI to complete assignments without learning. The piece highlights the need for pedagogical shifts and teacher training in response to AI tools.
Original abstract
<p>We’ve all had some version of the nightmare: You’ve been inexplicably thrown back into high school, and now you’re standing in front of the class. You’re about to give a speech, but you can’t remember a word. The panic is exacerbated by the faces of students staring at you, some hiding snickers and others openly laughing. Everyone knows what’s going on but you.</p><p>I was reminded of this bad dream over the past few years. As my Indigenous school’s instructional technology coordinator, I have seen my office transform from a routine integration hub into a digital confessional. Colleagues and teachers who are trying to navigate destabilizing technology changes slip inside and close the door. Some are looking for practical technology triage, or just a safe space to vent their frustrations, only to recount a similar nightmare. </p><p>For these educators, the experience triggers a sharp wave of panic, a sudden realization that the pedagogical ground has shifted beneath their feet and they can no longer trust their own instincts or traditional technology guardrails. But what follows the panic is a deep, stinging embarrassment. </p><p>With open and hopeful hearts, these teachers publicly praised student writing, extolling the hard work and growth they believed the student had demonstrated, only to find themselves surrounded by the giggles of classmates who already knew the truth: the writing had been fully generated by an AI tool.</p><p>The students had technically succeeded while learning very little, a phenomenon Micah Miner describes as <em>unproductive success</em> in “<a href="https://minerclass.github.io/dissertationquestionsbeta/dissertation-sites/"><u>Beyond Secondary Orality</u></a>.” As a result, teachers and administrators are left trying to respond to tools and behaviors they don’t yet fully understand and have never been trained to address. </p><p>These individual instances of unproductive success were not isolated classroom frustrations; they were early s
- PaperLanguage Teaching Research16 Jul 2026
Comparing Teacher and Artificial Intelligence Scoring in Writing Assessment: A Generalizability Theory Analysis
Burak Asma
Compared teacher and AI scoring of middle school essays with and without rubrics using generalizability theory. AI tools showed higher consistency and better differentiation of individual differences, while teachers were influenced by biases and mood. Teachers acknowledged the potential of rubrics and AI feedback for more consistent results.
Original abstract
This study examined the use of artificial intelligence tools, which have garnered significant attention in recent years, in the assessment and evaluation processes of language education. For this purpose, student essays were scored by Turkish middle school teachers and artificial intelligence tools both with and without the use of a rubric, and the findings were evaluated based on generalizability theory. Additionally, the research findings were shared with participants to gather qualitative data, which were analysed using the inductive thematic analysis method to support the research results. The findings revealed that in evaluations conducted without a rubric, teachers were limited in their ability to distinguish individual differences and demonstrated low scoring consistency. In contrast, artificial intelligence tools were more effective in distinguishing individual differences and exhibited high consistency. In evaluations conducted using a rubric, scoring consistency increased in both groups, although, as in the first evaluation, artificial intelligence tools demonstrated a higher level of consistency. Regarding the research findings, teachers expressed that individual biases, mood, and professional experiences influenced their scoring processes and emphasized the potential of rubrics and artificial intelligence-supported feedback systems for achieving more consistent results. Artificial intelligence tools, on the other hand, highlighted their independence from subjective factors but stressed the need for more diverse and generalizable datasets to further enhance their evaluation capacities.