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Texas will use computers to grade written answers on this year’s STAAR tests

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The state will save more than $15 million by using technology similar to ChatGPT to give initial scores, reducing the number of human graders needed. The decision caught some educators by surprise.
Students sitting for their STAAR exams this week will be part of a new method of evaluating Texas schools: Their written answers on the state’s standardized tests will be graded automatically by computers.
The Texas Education Agency is rolling out an “automated scoring engine” for open-ended questions on the State of Texas Assessment of Academic Readiness for reading, writing, science and social studies. The technology, which uses natural language processing technology like artificial intelligence chatbots such as GPT-4, will save the state agency about $15-20 million per year that it would otherwise have spent on hiring human scorers through a third-party contractor.
The change comes after the STAAR test, which measures students’ understanding of state-mandated core curriculum, was redesigned in 2023. The test now includes fewer multiple choice questions and more open-ended questions — known as constructed response items. After the redesign, there are six to seven times more constructed response items.
“We wanted to keep as many constructed open ended responses as we can, but they take an incredible amount of time to score,” said Jose Rios, director of student assessment at the Texas Education Agency.
In 2023, Rios said TEA hired about 6,000 temporary scorers, but this year, it will need under 2,000.
To develop the scoring system, the TEA gathered 3,000 responses that went through two rounds of human scoring. From this field sample, the automated scoring engine learns the characteristics of responses, and it is programmed to assign the same scores a human would have given.
This spring, as students complete their tests, the computer will first grade all the constructed responses. Then, a quarter of the responses will be rescored by humans.
When the computer has “low confidence” in the score it assigned, those responses will be automatically reassigned to a human. The same thing will happen when the computer encounters a type of response that its programming does not recognize, such as one using lots of slang or words in a language other than English.
“We have always had very robust quality control processes with humans,” said Chris Rozunick, division director for assessment development at the Texas Education Agency. With a computer system, the quality control looks similar.
Every day, Rozunick and other testing administrators will review a summary of results to check that they match what is expected. In addition to “low confidence” scores and responses that do not fit in the computer’s programming, a random sample of responses will also be automatically handed off to humans to check the computer’s work.
TEA officials have been resistant to the suggestion that the scoring engine is artificial intelligence. It may use similar technology to chatbots such as GPT-4 or Google’s Gemini, but the agency has stressed that the process will have systematic oversight from humans. It won’t “learn” from one response to the next, but always defer to its original programming set up by the state.
“We are way far away from anything that’s autonomous or can think on its own,” Rozunick said.
But the plan has still generated worry among educators and parents in a world still weary of the influence of machine learning, automation and AI.
Some educators across the state said they were caught by surprise at TEA’s decision to use automated technology — also known as hybrid scoring — to score responses.
“There ought to be some consensus about, hey, this is a good thing, or not a good thing, a fair thing or not a fair thing,” said Kevin Brown, the executive director for the Texas Association of School Administrators and a former superintendent at Alamo Heights ISD.
Representatives from TEA first mentioned interest in automated scoring in testimony to the Texas House Public Education Committee in August 2022. In the fall of 2023, the agency announced the move to hybrid scoring at a conference and during test coordinator training before releasing details of the process in December.
The STAAR test results are a key part of the accountability system TEA uses to grade school districts and individual campuses on an A-F scale. Students take the test every year from third grade through high school. When campuses within a district are underperforming on the test, state law allows the Texas education commissioner to intervene.
The commissioner can appoint a conservator to oversee campuses and school districts. State law also allows the commissioner to suspend and replace elected school boards with an appointed board of managers. If a campus receives failing grades for five years in a row, the commissioner is required to appoint a board of managers or close that school.
With the stakes so high for campuses and districts, there is a sense of uneasiness about a computer’s ability to score responses as well as a human can.
“There’s always this sort of feeling that everything happens to students and to schools and to teachers and not for them or with them,” said Carrie Griffith, policy specialist for the Texas State Teachers Association.
A former teacher in the Austin Independent School District, Griffith added that even if the automated scoring engine works as intended, “it’s not something parents or teachers are going to trust.”
Superintendents are also uncertain.
“The automation is only as good as what is programmed,” said Lori Rapp, superintendent at Lewisville ISD. School districts have not been given a detailed enough look at how the programming works, Rapp said.
The hybrid scoring system was already used on a limited basis in December 2023. Most students who take the STAAR test in December are retaking it after a low score. That’s not the case for Lewisville ISD, where high school students on an altered schedule test for the first time in December, and Rapp said her district saw a “drastic increase” in zeroes on constructed responses.
“At this time, we are unable to determine if there is something wrong with the test question or if it is the new automated scoring system,” Rapp said.
The state overall saw an increase in zeroes on constructed responses in December 2023, but the TEA said there are other factors at play. In December 2022, the only way to score a zero was by not providing an answer at all. With the STAAR redesign in 2023, students can receive a zero for responses that may answer the question but lack any coherent structure or evidence.
The TEA also said that students who are retesting will perform at a different level than students taking the test for the first time. “Population difference is driving the difference in scores rather than the introduction of hybrid scoring,” a TEA spokesperson said in an email.
For $50, students and their parents can request a rescore if they think the computer or the human got it wrong. The fee is waived if the new score is higher than the initial score. For grades 3-8, there are no consequences on a student’s grades or academic progress if they receive a low score. For high school students, receiving a minimum STAAR test score is a common way to fulfill one of the state graduation requirements, but it is not the only way.
Even with layers of quality control, Round Rock ISD Superintendent Hafedh Azaiez said he worries a computer could “miss certain things that a human being may not be able to miss,” and that room for error will impact students who Azaiez said are “trying to do his or her best.”
Test results will impact “how they see themselves as a student,” Brown said, and it can be “humiliating” for students who receive low scores. With human graders, Brown said, “students were rewarded for having their own voice and originality in their writing,” and he is concerned that computers may not be as good at rewarding originality.
Julie Salinas, director of assessment, research and evaluation at Brownsville ISD said she has concerns about whether hybrid scoring is “allowing the students the flexibility to respond” in a way that they can demonstrate their “full capability and thought process through expressive writing.”
Brownsville ISD is overwhelmingly Hispanic. Students taking an assessment entirely in Spanish will have their tests graded by a human. If the automated scoring engine works as intended, responses that include some Spanish words or colloquial, informal terms will be flagged by the computer and assigned to a human so that more creative writing can be assessed fairly.
The system is designed so that it “does not penalize students who answer differently, who are really giving unique answers,” Rozuick said.
With the computer scoring now a part of STAAR, Salinas is focused on adapting. The district is incorporating tools with automated scoring into how teachers prepare students for the STAAR test to make sure they are comfortable.
“Our district is on board and on top of the things that we need to do to ensure that our students are successful,” she said.
Source: texastribune.org
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Sainsbury’s aims to be an ‘AI-enabled grocer’ with Microsoft AI technology

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Sainsbury’s, a prominent UK supermarket chain, is set to leverage Microsoft’s artificial intelligence and machine learning tools to elevate its store operations and provide customers with a more engaging and convenient shopping experience.
As part of its strategic initiative, the ‘Next Level Sainsbury’s strategy’, the supermarket will integrate generative AI, powered by Microsoft Azure, to enhance its online shopping platform and optimize customers’ search experience. By harnessing AI capabilities, Sainsbury’s aims to offer a more interactive and personalized online shopping journey for its millions of customers across the UK.
In addition to enhancing the online shopping experience, Sainsbury’s plans to equip its store colleagues with real-time data and insights to streamline in-store processes such as shelf replenishment. Leveraging multiple data inputs, including shelf-edge cameras, AI technology will guide colleagues on prioritizing restocking activities, thereby improving efficiency and productivity.
Over the next five years, Sainsbury’s will deploy Microsoft Azure to implement these initiatives, integrating data assets with Microsoft 365 collaboration tools to drive innovation and operational excellence.
Clodagh Moriarty, Chief Retail and Technology Officer at Sainsbury’s, expressed confidence in the collaboration with Microsoft, emphasizing its role in accelerating the supermarket’s ambition to become the UK’s leading AI-enabled grocer. Moriarty highlighted the strategic investment in transformative capabilities, aimed at enhancing efficiency, productivity, and customer service while delivering value to shareholders.
Clare Barclay, CEO of Microsoft UK, commended Sainsbury’s visionary approach, noting its commitment to placing AI at the forefront of its business strategy. Barclay expressed enthusiasm for the collaboration, emphasizing its potential to revolutionize the retail experience for both customers and store colleagues.
The partnership between Sainsbury’s and Microsoft signifies a significant step towards ushering in the next generation of retail, powered by innovative AI-driven solutions.
Source: technologyrecord.com
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Researchers build AI-driven sarcasm detector

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Artificial intelligence has made remarkable strides, from passing bar exams to reading bedtime stories with emotion. Yet, despite these feats, it still falls short of matching the intricate nuances of human communication—particularly, the art of sarcasm.
However, researchers in the Netherlands are determined to change that narrative. They have developed an AI-driven sarcasm detector that can discern when sarcasm is being used, a feat previously thought to be exclusive to human cognition.
Matt Coler, from the University of Groningen’s speech technology lab, expresses excitement about the project’s progress. He emphasizes the importance of understanding sarcasm, a pervasive aspect of human discourse, to facilitate seamless communication between humans and machines.
Recognizing sarcasm poses challenges due to its subtlety, especially in text-based interactions where cues like tone and facial expressions are absent. To overcome this, researchers trained their AI using a combination of text, audio, and emotional content from popular sitcoms like Friends and The Big Bang Theory.
The AI, trained on annotated data from these shows, demonstrated an impressive ability to detect sarcasm in unlabelled exchanges from the sitcoms, achieving an accuracy rate of nearly 75%. Further enhancements are underway, including incorporating visual cues like eyebrow movements and smirks, to improve accuracy even more.
Beyond enhancing interactions with AI assistants, this technology holds potential for detecting negative language and identifying instances of abuse or hate speech. However, as AI becomes more adept at understanding sarcasm, questions arise about its potential to wield sarcasm itself.
Coler muses about the implications of machines responding with sarcasm, raising concerns about clarity in communication. Nonetheless, advancements in AI-driven sarcasm detection offer promising prospects for improving human-machine interactions and bridging the gap between artificial and human intelligence.
Source: theguardian.com

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AI, bias and experiments: how Women in News is tackling tech’s inbuilt stereotypes

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Issues surrounding bias in AI are deeply rooted in the accuracy, trustworthiness, and quality of data, which, if overlooked, can significantly skew outcomes. Lyndsey Jones, an AI author and transformation coach, delves into these concerns, offering valuable insights for newsrooms on monitoring and reviewing data.
Madhumita Murgia, an AI journalist and the first artificial intelligence editor of the Financial Times, sheds light on how women, migrants, precarious workers, and minority groups are disproportionately affected by the technical limitations of Generative AI. Murgia emphasizes the lack of representation of these groups in the development process of AI technologies, highlighting the need for inclusive participation.
WAN-IFRA Women In News workshops on the Age of AI in the newsroom have brought bias effects to the forefront. Through the Digital ABCs training program, media professionals are equipped with skills to navigate the digital landscape and drive organizational change.
A newly launched module focuses on AI, with over 100 participants in eastern Europe taking part, now extended to journalists in parts of Africa, the Middle East, and Southeast Asia. Instances of bias surfaced during the training, such as generating offensive avatars and misinterpretation of accents in AI tools.
Google CEO Sundar Pichai’s acknowledgment of biased AI tools reflects ongoing concerns in the industry. Timnet Gebru’s dismissal from Google for highlighting biases further underscores the need for vigilance in addressing these issues.
Diverse teams in WIN’s Age of AI program are experimenting with various tools like fact-checking and enhancing staff skill sets in AI usage. Projects under consideration for further EU funding include a video lab for content amplification and an AI avatar for journalist safety.
Media companies must ensure diverse staff collaboration when testing AI tools. Quotas for women in AI research and cross-border partnerships may be necessary for smaller media groups to compete effectively.
Journalists can take steps to improve content quality by examining storytelling practices and ensuring diversity in sources and representation. Consistency of data collection across departments and assessing biases in data sets are crucial for ethical AI usage in journalism. Ultimately, AI tools should be used to enhance journalism’s quality and integrity, rather than generating clickbait or misinformation.
Source: wan-ifra.org

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