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Artificial Intelligence, Authentic Impact: How Educational AI is Making the Grade

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Adoption of artificial intelligence is on the rise: According to research firm Gartner, 37 percent of organizations have now “implemented AI in some form,” and adoption is up 270 percent over the past four years. 

Schools are following suit: Technavio’s “Artificial Intelligence Market in the US Education Sector 2018-2022” report predicts a nearly 48 percent growth rate for AI tools over the next three years. 

The challenge? Separating market interest from authentic impact. As noted by MIT Technology Review, the rapid development and uptake of AI solutions has created an environment where companies may “obfuscate and oversell” AI abilities even as organizations race to implement new solutions and keep up with the competition.

The key to AI success is specificity. It is crucial to define key needs AI tools can meet and shortcomings it can address. This is especially true for K–12 institutions faced with limited time and budgets.

5 Roles AI Solutions Have in K–12 Classrooms

There’s no rulebook for deploying artificial intelligence in schools. While solutions such as IBM’s Watson Education and Google’s recently announced Google Cloud Platform storage and AI initiativeoffers the potential for schools to deliver personalized learning strategies and offer analytics-based performance insight; how K–12 institutions leverage these tools is entirely up to them. 

Some of the most common concerns are around human bias and overall accuracy. As RAND senior policy researcher Robert Murphy notes in a post for Education Week, “maybe 10 percent, 20 percent, 40 percent of the time [the system] will get it wrong,” making AI in schools an excellent supplemental tool, but no replacement for teachers. 

As noted by Education Technology, the increasing use of AI in schools also brings ethical questions to the fore. Organizations must now consider what type of data is being collected, how this information is being used and what controls are in place to safeguard student privacy. In addition, administrators are worried about how increasing AI adoption will impact human staffing.

The best bet for schools adopting AI is to define how these solutions can drive positive outcomes before allowing them access to student data. While individual usage may vary, effective AI in education can be grouped into five general roles:

  1. Automation: The simplest application of AI often provides the most immediate benefit: By automating straightforward tasks such as grading, digital asset categorization or timetable scheduling, educators can increase the amount of time they spend actively engaging with students.

  2. Integration: AI solutions can integrate with other IT initiatives such as smart technology and IoT-driven networks to provide personalized learning solutions for students.

  3. Acclimation: Technology is now an integral part of both educational and business environments. Recent Pew Research data shows that 95 percent of teens have access to a smartphone and 45 percent are online “almost constantly.” AI in schools can help acclimate students to the pace of technological change.

  4. Delineation: Students’ needs and curriculum priorities are constantly shifting, making it difficult for educators to ensure the content they deliver remains relevant and actionable. AI-driven analytics in education can help spot critical trends and delineate key markers to help teachers design the most effective classroom experience and drive digital transformation.

  5. Identification: Data analytics informed by adaptative AI solutions can help identify critical areas for student and teacher performance. Combined with robust security and access controls, AI can help spot and remedy potential problems in their formative stages.

How K–12 Schools Are Using AI Tools Now

So, what does this look like in practice? 

In Florida’s Putnam County School District, educators are leveraging new content monitoring software to both automate the process of flagging potentially sensitive internet searches and add critical context to flagged requests. 

And in New Jersey, Slackwood Elementary School is using an AI-assisted teaching assistant called Happy Numbers to identify where students are struggling with math benchmarks and provide personalized assistance.

Solutions such as the Presentation Translator — a free PowerPoint plug-in — provide real-time integration of multilanguage subtitles to help students better understand instructions in class or provide remote access for those dealing with illness or other family concerns.

Put simply, the current climate of AI in schools one of hopeful hesitation. While technology is rapidly advancing, educators are taking a step-by-step approach to ensure the solutions they adopt deliver specific outcomes to address existing needs.

What Does the Future Hold for AI in the Classroom?

As artificial intelligence solutions inch ever closer to replicating the basics of authentic human thought patterns, what’s the impact for education? Broadly speaking, next steps for AI in school take three key forms:

  1. Personalizing performance: Increased processing power and sophistication will empower AI solutions to better collect and extrapolate information, in turn helping educators create personalized learning plans for each student. New solutions such as Brightspace Insights are designed to capture, aggregate and analyze data from multiple sources, allowing teachers to gain student insight “based on the entire ecosystem of learning tools” according to Nick Oddson, senior vice president of product development for D2L, the creator of Brightspace.

  2. Breaking bias: Human bias remains a stumbling block in education — and, as noted above, is also an emerging concern for AI tools. The future of AI in schools will leverage solutions capable of grading papers and evaluating exams using established rubrics and benchmarks to both automate completion and eliminate bias.

  3. Aggregating assistance: Educators are typically masters of their craft; many have multiple degrees and often specialize in niche areas of student development and performance. The problem is that necessary administrative work often frustrates teacher efforts to engage with students. Here, the future of classroom intelligence takes the form of AI-driven assistants that deliver essential data to help teachers do what they do best: connect with students.

Schools Must Balance AI Effectively with Security

AI in education has reached a tipping point. Adoption is on the rise, but concerns around bias, privacy and human-machine partnerships necessitate a methodical and measured approach. 

Current applications leverage machine learning and real-time data integration, but the future of AI depends on broader applications capable of adaptively applying practical intelligence to empower the critical emotional connections that drive student performance.

posted Aug 29 in EdTech by Sopanha

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According to a Northeastern University/Gallup poll, most Americans are optimistic about artificial intelligence’s (AI) impact on their futures while, at the same time, expecting the net effect of AI to be an overall reduction in jobs. If we manage AI effectively, I believe it can be a net benefit to both society and the economy.

Is AI (Artificial Intelligence) a game-changer for higher Education?

The question is: How will higher education manage AI?

Unfortunately, higher education does not have a reputation for managing change effectively. Our experience is much more one of coming late to the party—and not of our own accord. We cannot and should not do this with AI.

First, much of the expertise to develop AI is coming from university laboratories, with AI hot spots in university centres such as Boston, San Francisco, Chicago, and the Research Triangle of North Carolina. If we can develop AI for businesses at home and abroad, why can’t we do the same for ourselves?

Second, many creative applications of AI have already been developed to solve problems within the university. Certainly, enrollment-management processes, as well as today’s learning management systems, look nothing like those of 20 years ago. These changes are clear applications of AI. At the end of the day, however, the application of AI within the university is quite limited.

Where are the higher-ed AI opportunities?

To find opportunities for AI growth within the university, we need to distinguish between activities that are uniquely human as opposed to those that can be computerized. Individuals excel at defining problems, distinguishing between “good” and “bad,” at idiosyncratic tasks such as detecting false positives, and in developing novel combinations not anticipated by previous experience. Computers excel at tasks that involve well-understood rules and procedures.

Furthermore, human decision making is enhanced when it occurs in groups. Social facilitation, cooperation, division of labour and the collecting of different perspectives, knowledge, and experience all combine to enhance decision making by groups.

Of course, neither individuals nor groups are without their problems. Individuals can be slow and inefficient in their decision making, to say nothing of the limits a single individual’s knowledge and experience. Likewise, groups can be guilty of premature closure, becoming too risky or too conservative because of preconceived expectations and groupthink. Much of the work of organizational psychology has focused on how to manage individual and group decision making so as to keep the good and minimize the bad.

Thus, if AI is seen not as a way to replace the individual but as a way to make individuals and groups more effective, both the impact of AI and its acceptance will be greatly improved. Today, augmented reality has greater potential for changing how we do things in higher education. Interesting examples of this concept can be found in the business world, where AI is used to facilitate human fraud detectors for banks and human translators and editors in publishing.

How can this distinction yield applications within higher education?

While MOOCs have not yielded the disruptions that many expected, they have had a significant impact on the way we deliver course materials. Lectures on most introductory topics are readily available on the web and the push for flipped classrooms is ubiquitous. These applications facilitate what individual instructors do.

Where AI can make its mark

The real impact on learning can come through learning management systems (LMSs). We have known for quite a while that we can use technology to manage classroom participation. There is much research, including my own, that shows that anonymous input systems, when added to regular or online classrooms, increase the participation of individuals who would normally shy away from raising their hands or volunteering comments.

Applications are being developed to use AI to track student questions asked in a class and direct them to answers and to other students with the same questions. The Minerva Project is so convinced of the power of such technology that class discussions occur only online—despite students living together in the same building.

Furthermore, the massive amount of data generated by LMSs has the potential to increase the effectiveness of learning. Researchers at a school where I previously worked used data on students’ online participation to identify within the first two weeks of a class which students were likely to perform poorly. They were then able to change these students’ participation patterns and thus their outcomes.

Getting faculty buy-in
The question, however, is whether such applications will be embraced by the faculty members who fear that change will result in their demise. And at their core, many faculty members believe that learning is a uniquely individual process. Until professors see AI as a means of enhancing their effectiveness, resistance will continue.

Disruptors are on the horizon. The entrance of Arizona State and Purdue into the online marketplace is significant. MBA programs are ripe for disruption; most business school deans expect the part-time MBA market to shift to online delivery in the next five years. These online platforms will accelerate the shift to AI-managed learning.

The future for AI within the university is bright. Applications will proliferate and finally disrupt the teaching paradigm. The danger is for institutions that come late to the party and not of their own accord.

in EdTech
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With CBSE introducing artificial intelligence as an elective paper, students and teachers must be very excited to know how can AI help the students’ performance grow. It has been decided that the subject would be introduced in classes 8, 9 and 10 as a skill subject.

Artificial Intelligence in Schools: How AI-powered adaptive learning technology can help students

What is artificial intelligence?

Artificial intelligence is the ability of a machine to think, learn and perform tasks normally requiring human intelligence, such as visual perception, speech recognition and decision-making skills. Capabilities demonstrated by machines, including computers, from playing chess to operating cars and beyond, fall within the domain of artificial intelligence.

How AI-powered Adaptive Learning Technology brings Personalised Learning to Kids

The rapid spread of education among the masses in the industrial era made the ‘one-size-fits-all’ method of learning the most convenient one for training subsequent generations of the workforce due to lack of resources. This method of education did not cater to the interests of most students, and learning became less engaging and meaningful for them. Additionally, learning was very superficial, with learners having only a basic understanding of concepts and this led to poor retention. This problem was recognised by the 18th-century social revolutionary, Jean-Jacques Rousseau who made the following recommendations:

“Teach your scholar to observe the phenomena of nature; you will soon rouse his curiosity, but if you would have it grow, do not be in too great a hurry to satisfy this curiosity. Put the problems before him and let him solve them himself. Let him know nothing because you have told him, but because he has learnt it for himself…”

Rousseau talks about self-paced and self-styled learning methods, which came to be termed as personalised learning in the 1960s. Personalised learning includes tailoring educational content according to the learners’ strengths, needs and interests, applying competency-based progression to set the individual pace for comfortable learning, and customising instructional modes to maximise learning intake. Before technological advancement, personalised learning was possible only through one-to-one private tutorials, which could be afforded only by affluent families. The rest of the learners had to submit to ‘factory schooling’, which failed to spark interest or provide in-depth learning, thus demotivating them. However, the turn of the millennium saw technology grow by leaps and bounds and its eager adoption in upgrading several learning strategies, including personalised learning.

Adaptive tests

Personalised learning has now come within the reach of everyone through adaptive learning technology. Powered by artificial intelligence, it analyses a vast pool of data to tailor the content as per an individual’s interest and knowledge level. This is initiated with the help of adaptive tests, which accurately quantifies the knowledge of different topics of individual learners. These tests include a large pool of questions usually drawn from data collected over the years, whose difficulty level is determined on the basis of the number of students who have answered the questions correctly. Learners are first posed with a mid-level question and based on their response, the difficulty level of the next question and the subsequent ones are modified— if they answer a question of mid-level difficulty correctly, then they will be presented with a question with a higher level of difficulty, but if answered incorrectly, the system will pose a simpler question.

 

Optimal learning paths

Adaptive assessments help instructors to precisely determine where the individual learner stands at the beginning of the academic course and to measure gaps through the course of learning. These tests give detailed analytical reports of the knowledge state and learning pattern of the learner, according to which an optimal learning path is established. This constitutes the second part of adaptive learning— adaptive content. We at Next Education have designed an adaptive learning platform as part of our Next Learning Platform, which will present the optimal learning resources from our vast pool of content (simulations, real-life videos and hands-on learning tools) based on what the learner responds best to. This inspires inquiry-based learning, which ensures that students follow the best-suited learning path and attain learning goals in an optimal time.

Making personalised learning available for all

Implementing personalised learning was practically impossible before adaptive learning technology came into the scene. The two major factors affecting this were lack of qualified teachers and financial resources. Personalised instruction needs an ideal student--teacher ratio of six to eight students per teacher. Besides , most teachers lack adequate training for effective teaching. Thus, only a select few elite schools with exceptionally good teachers were able to facilitate a personalised learning environment to students.

 

herefore, in the absence of such learning opportunities in most schools, parents chose to enrol students in coaching classes or appoint private tutors. The scenario in group coaching classes was not that encouraging either. Appointing skilled private tutors might be ideal, but it is certainly be a costly affair. A private teacher would charge approximately ₹ 2,000 to ₹ 5,000 per student for one subject for a month. On the other hand, adaptive learning would cost only around ₹ 200–500 for a student per month, thereby helping students avail quality education at affordable prices. Additionally, increasing internet and digital system usage in recent years has improved access to digital education, bringing the advantages of adaptive learning to remote areas of the country.

Thus, AI-powered adaptive learning has brought personalised learning within the reach of all 21st-century learners, solving the three-fold problem of quality, cost and access that continues to plague education, especially in developing countries such as India. The continuous evolution of education technology with the help of artificial intelligence promises more wonders such as advanced language teaching tools and smart assistants in classrooms, which will change the face of education completely.

+1 vote

Artificial intelligence (AI) and emerging technologies (ET) are poised to transform modern society in profound ways. As with electricity in the last century, AI is an enabling technology that will animate everyday products and communications, endowing everything from cars to cameras with the ability to interact with the world around them, and with each other. These developments are just the beginning, and as AI/ET matures, it will have sweeping impacts on our work, security, politics, and very lives.

These technologies are already impacting the world around us, as Darrell West and I wrote in our April 2018 piece “How artificial intelligence is transforming the world,” and I highly recommend that anyone just discovering the topic of AI policy read it thoroughly. There, Darrell and I describe several important implications related to AI/ET, but chief among them is that these technology developments are on the cusp of ushering in a true revolution in human affairs at an increasingly fast pace.

As AI continues to influence and shape existing industries and allows new ones to take root, its macro-level impact, particularly in the realm of economics, will become more and more apparent. Control over the research and development of AI will become increasingly vital, and the winners of this upcoming AI-defined era in human history will be the countries and companies that can create the most powerful algorithms, assemble the most talent, collect the most data, and marshal the most computing power. This is the next great technology race of our generation and the stakes are high, particularly for the United States. If American society is to embrace the full range of social and political changes that these technologies will introduce, then it is the education and training we provide our youth and workers that will fuel the engines of future AI, and therefore geopolitical success.

It is the education and training we provide our youth and workers that will fuel the engines of future AI, and therefore geopolitical success.

I’ve studied and written extensively about the effects of AI/ET on the evolving character of war toward a concept I’ve called hyperwar—or, a new era of warfare in which, through AI, the speed of decision-making is faster than anything that has come before. At a superficial level, this topic often devolves into a discussion of “killer robots,” or at the very least, the impending use of AI in lethal autonomous weaponry. While those discussions are relevant and inextricably linked, they represent a narrow understanding of the greater issues at hand. The concern over AI’s potential or theoretical military applications must not distract us from how far-reaching the impact of AI will be in nearly all other policy domains. Health care, education, agriculture, energy, finance, and yes, national security, will all be reshaped in some way by AI—with education being the pivot point around which the future of the United States revolves. This is not solely a matter of social redress, but, in fact, a larger national issue.

A future in which the United States is second in the race for AI technology would create a situation of national technological and digital/cyber inferiority, which could in turn result in national strategic subservience.

The way we use education to prepare our next generation of leaders will directly determine whether the U.S. retains its leadership in critical fields of relevance in the emerging digital environment. Without a sufficiently educated population and workforce, the U.S. likely will slip behind other states for whom AI/ET is not only meant for improved social organization, but for strategic superiority, and ultimately digital and physical conquest. A future in which the United States is second in the race for AI technology would create a situation of national technological and digital/cyber inferiority, which could, in turn, result in national strategic subservience—something simply unimaginable.

Many Americans grew up with the understanding that the American capacity to fight and win a nuclear war was defined by its superiority in the Strategic Triad, the three legs of our strategic deterrence: our missile squadrons, our bomber fleet, and our ballistic missile submarines.  Behind that dizzying array of hardware was the undisputed power of U.S. intellectual and technical capabilities, and behind that was a near unlimited supply of talented engineers, each trained by a system of education undisputed in its excellence. That system was built from the ground up to produce crucial STEM (science, technology, engineering, and math) protégés in the quantities needed to ensure American strategic superiority, which contributed directly to the U.S. and its allies prevail in the Cold War. For the health of our American way of life, our competitive advantage, and the strategic security of our nation, the basis for tomorrow’s system of education must reflect a deliberately tuned and calibrated system that proactively emphasizes AI/ET, big data analytics, and super-computing.

Unfortunately, in both relative and absolute terms, the U.S. is falling behind in the race for superiority in these key technologies. Where the U.S. strategic advantage of the 20th Century was secured by American nuclear superiority, U.S. superiority in the 21st Century will likely be preserved, safeguarded, and sustained through a system of education that envisages the changes necessary and sufficient to embrace and apply relevant technologies. It will also be underwritten by educators who grasp the profound shifts in the pedagogical skills essential to the educational needs of the 21st Century.

in EdTech
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AI integration offers new potential to improve student outcomes and security.

Over the past several years, artificial intelligence transitioned from the movie screen to reality, and soon it will be everywhere.

The ubiquity of AI across industries leads to two key points for K–12 schools

First, K–12 schools should use current AI solutions to help with everything from classroom performance to network safety and monitoring. Second, students need to start learning how to design, manipulate and work alongside AI machines in order to build the foundation they need as they prepare to enter the workplace.

Organizing a successful AI integration and education plan will take collaboration and proper planning on the part of school decision-makers.

“AI may hold the potential to personalize instruction and learning. Yet its use in educational settings will require educators and school leaders to develop an understanding of how it can be implemented safely and smartly,” Keith Krueger, CEO of the Consortium for School Networking said in a recent statement

AI Can Act as A Multifaceted Digital Assistant

Artificial intelligence offers a helping hand to K–12 educators, staff and administrators, easing the burden of daily tasks and extending constrained resources.

Personalized learning, for example, is being rapidly adopted by educators as a key pedagogy. However, one of the most difficult parts of personalized learning is finding the time to give each student the attention he or she needs. 

AI-enabled teaching assistants and mobile applications help educators meet that challenge, using input from students to adjust course materials through educational apps, leaving teachers time to conduct the interpersonal aspects of their curricula.

AI-enabled content monitors also improve student safety. Putnam County School District adopted GoGuardian’s new content monitoring software, which uses machine learning to add context to flagged internet searches.

For example, the automated filtering solution would be able to identify a student searching about self-harm, prompting appropriate mental health intervention. 

K–12 Teachers Need to Bolster AI Curriculum

recent Gartner report predicts one in five workers will have some form of artificial intelligence as a coworker, and Forrester predicts by 2021, automation technology will account for the work of nearly 4.3 million humans worldwide. 

That means most of today’s K–12 students will enter the workforce by the time AI is well established. In order to compete, K–12 schools will need to create curricula around artificial intelligence. 

At the Montour School District in Pennsylvania, students use tablets and smart assistants like Amazon Alexa and Google Home to explore the mechanisms of machine learning.

“It’s the people that program artificial intelligence and technology that will change the future,” Justin Aglio, Montour’s director of academic achievement and district innovation, tells The Tribune-Review.

Experts realize planning AI-related curricula can be challenging, so organizations are forming to help drive K–12 education around artificial intelligence. 

The Association for the Advancement of Artificial Intelligence and the Computer Science Teachers Association recently formed the AI for K–12 Working Group, which recently drafted a report, “Envisioning AI for K–12: What should every child know about AI?” The report outlines five important ideas around the AI concepts that K–12 students should know, from how it functions to the ethics of using it. (Access the full report here.)

“It is just as important now to think about what AI education should look like in K–12, not only to ensure a more informed populace that understands the technologies they interact with every day but also to inspire the next generation of AI researchers and software developers,” the report’s authors write. “For many in this generation, AI will be an often overlooked, magical force that powers their lives much as electricity, the internal combustion engine, and networking technology power ours.”

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