{"id":601773,"date":"2023-01-27T06:55:56","date_gmt":"2023-01-27T12:55:56","guid":{"rendered":"https:\/\/news.sellorbuyhomefast.com\/index.php\/2023\/01\/27\/chatgpt-isnt-the-only-way-to-use-ai-in-education\/"},"modified":"2023-01-27T06:55:56","modified_gmt":"2023-01-27T12:55:56","slug":"chatgpt-isnt-the-only-way-to-use-ai-in-education","status":"publish","type":"post","link":"https:\/\/newsycanuse.com\/index.php\/2023\/01\/27\/chatgpt-isnt-the-only-way-to-use-ai-in-education\/","title":{"rendered":"ChatGPT Isn\u2019t the Only Way to Use AI in Education"},"content":{"rendered":"
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Soon after\u00a0<\/span>ChatGPT<\/a> broke the internet, it sparked an all-too-familiar question for new technologies: What can it do for education?\u00a0 Many\u00a0feared<\/a> it would worsen plagiarism and further damage an already decaying humanism in the academy, while others lauded its potential to spark creativity and\u00a0handle mundane educational tasks<\/a>.\u00a0\u00a0<\/p>\n

Of course, ChatGPT is just one of many advances in artificial intelligence that have the capacity to alter pedagogical practices.\u00a0 The allure of AI-powered tools to help individuals\u00a0maximize their understanding<\/a> of academic subjects (or more effectively\u00a0prepare for exams<\/a>) by offering them the right content, in the right way, at the right time\u00a0for them<\/em> has spurred new investments from governments and private philanthropies.\u00a0\u00a0<\/p>\n

There is reason to be excited about such tools, especially if they can mitigate barriers to a higher quality or life\u2014like reading proficiency disparities by race, which the NAACP has highlighted as a\u00a0civil rights issue<\/a>.\u00a0 Yet underlying this excitement is a narrow view of the goals of education. In this framework, learners are individual actors who might acquire new knowledge and skills with the help of technology.\u00a0 The purpose of learning, then, is to master content\u2014often measured through grades and performance on standardized tests.\u00a0\u00a0\u00a0<\/p>\n

But is content mastery really the purpose of learning?\u00a0 Naming reading proficiency as a civil rights issue likely has less to do with the value of mastering reading itself, and more to do with the fact that mastery of reading (or math, or other subjects) can help lay a foundation for what learning can unlock: breaking the intergenerational cycle of poverty, promoting greater self-awareness and self-confidence, and cultivating a stronger sense of agency over one\u2019s destiny and the destinies of one\u2019s communities.\u00a0 Content mastery is part of this equation, but making it the primary focus of education misses the fact that so much of a child\u2019s future is shaped by factors beyond the classroom.\u00a0 Critically, networks, or\u00a0who<\/em> children and their families are connected to, and\u00a0how<\/em>, matter for helping children prepare to live fulfilling lives.\u00a0 This is especially true for networks that cut across socioeconomic, demographic, and other lines.\u00a0 Indeed, a\u00a0large recent study<\/a> highlighted how social capital, defined as friendships across socioeconomic divides, can play a larger role in fostering intergenerational economic mobility than school quality (often measured by the test scores of students who go there).\u00a0\u00a0<\/p>\n

Networks that connect parents to coaches to\u00a0help them navigate<\/a> their children\u2019s schooling can forge new support structures and trusting relationships between families and educators.\u00a0 Networks that connect students to role models and mentors can\u00a0change the course<\/a> of their academic and professional lives.\u00a0 A child\u2019s broader social context, in addition to the knowledge and skills they gain through school, matters deeply for their future outcomes.\u00a0 Left without intervention, however, real-world networks often form and evolve in inherently unequal ways. For example, patterns of\u00a0preferential attachment<\/a>\u00a0can lead \u201cthe rich to get richer,\u201d excluding many from accessing connections that might improve their lives in important ways.<\/p>\n

In practice, each AI needs an objective function that represents what it is optimizing for.\u00a0 Applications of AI for pedagogy and content mastery might optimize for \u201chelping students get the highest possible score on a test.\u201d\u00a0Fostering more inclusive network connections, however, is a more deeply rooted and structural type of change than improving test scores.\u00a0 Using AI to help cultivate these networks might do more for children\u2019s life outcomes than focusing on pedagogy and content mastery alone.\u00a0\u00a0<\/p>\n<\/div>\n

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But some may argue that optimizing network connections is a more nebulous task than optimizing test scores.\u00a0 What, precisely, should the objective function(s) be?<\/p>\n

One framework for exploring this may involve focusing on how the networks that children and families are enmeshed in form and evolve in the first place.\u00a0 In the context of schooling, this involves the wide range of policies that school districts design to determine which schools students can attend (\u201cschool assignment policies\u201d), along with the practices families adopt when picking schools for their children under these policies.\u00a0 Such policies and practices have historically perpetuated harmful features like school segregation by race and socioeconomic status\u2014which, despite nearly 70 years since its formal outlawing, continues to\u00a0define public education<\/a> in the US.\u00a0 Many scholars argue that demographic integration has historically been one of the\u00a0most effective methods<\/a> not only for enhancing the academic preparation of historically disadvantaged groups, but also for\u00a0fostering greater compassion<\/a> and understanding\u2014say, an ethic of\u00a0pluralism<\/a>\u2014across people from different backgrounds.\u00a0\u00a0<\/p>\n

AI can help support the design of more equitable school assignment policies that foster diverse and integrated schools, for example, by supporting district-level planning efforts to redraw \u201cschool attendance zones\u201d\u2014i.e., catchment areas that determine which neighborhoods feed to which schools\u2014in ways that seek to mitigate underlying patterns of residential segregation without imposing large travel burdens and other inconveniences upon families.\u00a0\u00a0<\/p>\n

Existing\u00a0researcher-practitioner partnerships<\/a>\u2014and some of my own\u00a0research<\/a> with collaborators Doug Beeferman, Christine Vega-Pourheydarian, Cassandra Overney, Pascal Van Hentenryck, Kumar Chandra, and Deb Roy\u2014are leveraging tools from the operations research community and rule-based AI like\u00a0constraint programming<\/a> to explore alternative assignment policies that could optimize racial and socioeconomic integration in schools.<\/p>\n

These algorithms can help simplify an otherwise cumbersome process of exploring a seemingly infinite number of possible boundary changes to identify potential pathways to more integrated schools that balance a number of competing objectives (like family travel times and school switching).\u00a0 They can also be combined with machine-learning systems\u2014for example, those that try to predict family choice in the face of boundary changes\u2014to more realistically estimate how changing policies might affect school demographics.<\/p>\n

Of course, none of these applications of AI come without risks. School switching can be disruptive for students, and even with school-level integration, segregation can persist at smaller scales like classrooms and cafeterias due to\u00a0curricular tracking<\/a>, a lack of culturally responsive teaching practices, and other factors. Furthermore, applications must be couched in an appropriate sociotechnical infrastructure that incorporates community voices into the policymaking process.\u00a0 Still, using AI to help inform which students and families attend school with one other may spark deeper structural changes that alter the networks students connect to, and by extension, the life outcomes they ultimately achieve.<\/p>\n

Changes in school assignment policies without changes in school selection behaviors amongst families, however, are unlikely to lead to sustainable transformations in the networks that students are tapped into.\u00a0Here, too, AI may have a role to play.\u00a0 For example, digital school-rating platforms like\u00a0GreatSchools.org<\/a> are increasingly shaping how families evaluate and select schools for their children\u2014especially since their ratings are often embedded across housing sites like Redfin, which can influence where families choose to live.\u00a0\u00a0<\/p>\n<\/div>\n

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Some have argued that school-rating platforms, where ratings largely reflect test scores\u2014measures notoriously reflective of race and income and not as indicative of how much schools actually help students learn\u2014might have historically led white and affluent\u00a0families to self-segregate<\/a> into neighborhoods zoned for highly rated schools, creating a vicious cycle of residential segregation that reinforces patterns of school segregation and ensuing achievement gaps. A recent research project I did in collaboration with Eric Chu, Doug Beeferman, Rebecca Eynon, and Deb Roy fine-tuned large language models to explore how parents\u2019 open-ended reviews on GreatSchools might contribute to such trends.\u00a0 Our results showed that parents\u2019 reviews are strongly associated with school-level test scores and demographics, and\u00a0not<\/em> associated with measures of student progress, suggesting that parents who consult reviews to make schooling choices may be factoring demographics more than actual school effectiveness into their decisions.<\/p>\n

GreatSchools continues to invest in\u00a0new ratings schemes<\/a> that seek to break these feedback loops and offer a more complete view of school quality\u2014as Sisyphean a task as it may seem.\u00a0 What if platforms like GreatSchools also trained and deployed school recommender systems that simultaneously try to expose families to schools that satisfy their desires for their children (for example, rigorous course offerings, language immersion programs, compassionate and nurturing teachers) while also exposing them to schools \u201coutside of their bubbles\u201d\u2014that is, quality schools they might not otherwise consider, perhaps because they have lower test scores, are in neighborhoods they wrote off before ever exploring, or something else?\u00a0This multi-objective AI would not come without challenges of transparency and agency that accompany recommender systems deployed in other settings, but it could help spark new network connections that may not form otherwise.\u00a0\u00a0<\/p>\n

These are just some examples, and they are not mutually exclusive with pedagogically focused applications.\u00a0 For example, while we likely lack the data to do this today, looking ahead, AI might help determine which students would benefit the most from which tutors\u2014those who can not only help bridge learning gaps but also serve as relevant sources of mentorship, guidance, and inspiration.\u00a0 And expanding our focus in AI for education to include networks will not absolve us of the fairness concerns and other risks that existing deployments of AI continue to pose.\u00a0 Designing new applications of AI calls for careful and thoughtful exploration, especially as we as a society continue to respond to our rapidly changing AI landscape with a dynamic blend of fear, hope, concern, awe, and wonder.\u00a0 Of course, as in life itself, all of these emotions are important.\u00a0 Harnessing them to foster more inclusive network connections for the next generation of learners may be our most meaningful response of all.<\/p>\n<\/div>\n<\/div>\n

Read More<\/a>
\n Nabeel Gillani<\/p>\n","protected":false},"excerpt":{"rendered":"

Soon after\u00a0ChatGPT broke the internet, it sparked an all-too-familiar question for new technologies: What can it do for education?\u00a0 Many\u00a0feared it would worsen plagiarism and further damage an already decaying humanism in the academy, while others lauded its potential to spark creativity and\u00a0handle mundane educational tasks.\u00a0\u00a0Of course, ChatGPT is just one of many advances in<\/p>\n","protected":false},"author":1,"featured_media":601774,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[116428,688,46],"tags":[],"class_list":{"0":"post-601773","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-chatgpt","8":"category-isnt","9":"category-technology"},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts\/601773","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/comments?post=601773"}],"version-history":[{"count":0,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/posts\/601773\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/media\/601774"}],"wp:attachment":[{"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/media?parent=601773"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/categories?post=601773"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/newsycanuse.com\/index.php\/wp-json\/wp\/v2\/tags?post=601773"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}