Author: IBL News

  • What’s the Best Way to Measure Learner Engagement?

    What’s the Best Way to Measure Learner Engagement?

    IBL News & IBL Education | New York

    There are a few different ways to measure learner engagement, and the best approach will depend on the specific context and goals of your learning program.

    Some common methods for measuring engagement include assessing learners through quizzes and tests, observing their performance on tasks or projects, tracking their participation in online discussions or other collaborative activities, collecting feedback from learners or others who have observed their performance, conducting surveys or polls to gauge learners’ interest and satisfaction, and monitoring learners’ progress through course materials or assessments to see how much they are retaining and applying what they are learning.

    Ultimately, the key is to use a combination of methods to get a well-rounded picture of learners’ engagement and to regularly check in with learners to gather their feedback and make any necessary adjustments to your program.

    It’s important to use a balanced mix of assessment methods and to regularly evaluate and adjust the assessment process to ensure that it accurately reflects learners’ progress and achievement.

    How can I use AI to improve learner performance?

    AI can be used in a variety of ways to improve learner performance. For example, AI-powered tutoring systems can provide personalized instruction and feedback to help learners improve their knowledge and skills.

    AI-powered data analysis can help educators identify trends and patterns in learners’ performance, allowing them to tailor their instruction and support to individual learners’ needs.

    Additionally, AI-powered tools can help automate some of the administrative tasks associated with education, freeing up educators to focus on supporting learners. It’s important to remember, however, that AI is not a substitute for human instruction and support, and should be used in conjunction with other teaching methods.

    How can I predict if a learner is going to become disengaged?

    It can be difficult to predict with certainty if a learner is going to become disengaged, as there are many factors that can affect a person’s level of engagement in a learning program.

    However, there are some warning signs that a learner may be at risk of becoming disengaged, such as a lack of participation in online discussions or other collaborative activities, a lack of progress or a drop in performance on assessments, or a decline in the quality of their work.

    If you notice any of these signs, it may be a good idea to reach out to the learner to see if there is anything you can do to support them and keep them engaged in the learning program.

    You could also try to identify any potential barriers to engagement that the learner may be facing and work with them to address those barriers.

    What’s the best way to engage a learner?

    The best way to engage a learner will depend on their individual needs, preferences, and learning style.

    Some general strategies for engaging learners include making the learning material relevant and applicable to their lives, providing opportunities for learners to collaborate and connect with each other, and incorporating a variety of teaching methods and learning activities to cater to different learning styles.

    Additionally, providing regular feedback, support, and encouragement can help learners stay motivated and engaged in the learning process.

    It’s also important to regularly check in with learners to gauge their engagement and to gather their feedback on how the learning program can be improved.

    A SERIES OF ARTICLES ABOUT ‘AI, CLOUD, AND ADVANCED TECHNOLOGIES IN EDUCATION’ WRITTEN BY THE IBL AI ENGINE IN DECEMBER 2022*

     

     

    *The IBL AI/ML Engine extends and hosts leading language models (LLMs) via a combination of fine-tuning, customized datasets and REST APIs to provide an all-in-one AI platform for education featuring content recommendations, assessment creation and grading, chatbots and mentors, and predictive analytics.

     

  • Selected the Ten Top Educators and Courses in MOOCs According to the edX Platform

    Selected the Ten Top Educators and Courses in MOOCs According to the edX Platform

    IBL News | New York

    edX.org, 2U’s MOOC platform, selected ten top faculty and educators on massive courses, ranging in topics from UX design to earth and environmental sciences.

    They are the ten finalists for the seventh annual edX Prize for Exceptional Contributions in Online Teaching and Learning. These instructors are recognized for their innovation when delivering student-centric, impactful learning courses.

    The winners are selected by members of the edX Partner Advisory Council.

    The winner of this year’s award will be announced by edX/2U in early 2023.

    Last year, University of Canterbury professors Ben Kennedy and Dr. Jonathan Davidson were the winners of the 2021 edX Prize for their course Exploring Volcanoes and Their Hazards: Iceland and New Zealand. They designed the course to deliver an immersive and fun virtual science experience focused on volcanic landscapes.

    Anant Agarwal, edX Founder and Chief Platform Officer at 2U, said, “from Alaska to Hong Kong, our 2022 edX prize finalists represent vastly different institutions and disciplines but are united in their commitment to broadening the horizon of society’s knowledge and understanding with free and open courses.” 

  • November 2023

    November 2023

    NOV 6, 2023 – San Francisco, CA
    OpenAI DevDay

    NOV 14, 2023 – Virtual Event
    edX Educator Conference

    NOV 28 – 30, 2023 – Sacramento, CA
    CITE Annual Conference 

     

  • What Are Language Models (LLMs) and Why Are They Interesting?

    What Are Language Models (LLMs) and Why Are They Interesting?

    IBL News & IBL Education | New York

    Language models are algorithms that can predict the next word in a sequence of words, based on the words that have come before it.

    They are interesting because they can be used in a variety of natural languages processing tasks, such as machine translation, speech recognition, and text generation.

    Language models are typically trained on large amounts of text data, which allows them to capture the statistical patterns and relationships between words in a language. This allows them to make predictions about the next word in a sequence that is often very accurate.

    What kinds of predictions can language models make?

    Language models can make predictions about the next word in a sequence of words, based on the words that have come before it.

    They can also be used to generate text that is similar to a given input, by predicting the next word in a sequence and then using that prediction as the input for the next prediction, and so on.

    This can be used to generate text that is similar to a given input or to complete sentences or paragraphs that are missing some words.

    Language models can also be used in other natural language processing tasks, such as machine translation, speech recognition, and text summarization.

    What’s the best way to measure the performance of a language model?

    One way to measure the performance of a language model is to evaluate its ability to predict the next word in a sequence of words, based on the words that have come before it. This can be done by using a test set of text data that the model has not seen during training, and comparing the model’s predictions to the actual next word in the sequence. The accuracy of the model’s predictions can then be used as a measure of its performance. Other metrics, such as the perplexity of the model, can also be used to evaluate its performance. Perplexity is a measure of how well a language model predicts a given test set of text data, and is calculated as the exponentiated average of the model’s prediction errors on the test set. A lower perplexity score indicates a better-performing language model.

    What does it mean to fine-tune a language model?

    Fine-tuning a language model means adjusting its parameters to improve its performance on a specific task or dataset. This is typically done by training the language model on a large amount of text data that is relevant to the task or dataset, in addition to the training data that the model was originally trained on. This allows the model to learn the statistical patterns and relationships between words that are specific to the task or dataset and can improve its performance on that task or dataset. Fine-tuning can be a useful technique for adapting a pre-trained language model to a new task or dataset.

    A SERIES OF ARTICLES ABOUT ‘AI, CLOUD, AND ADVANCED TECHNOLOGIES IN EDUCATION’ WRITTEN BY THE IBL AI ENGINE IN DECEMBER 2022*

     

     

    *The IBL AI/ML Engine extends and hosts leading language models (LLMs) via a combination of fine-tuning, customized datasets and REST APIs to provide an all-in-one AI platform for education featuring content recommendations, assessment creation and grading, chatbots and mentors, and predictive analytics.

  • How AI Can Support Learners

    How AI Can Support Learners

    IBL News & IBL Education | New York

    AI can support learners in a number of ways. For example, AI can be used to create personalized learning plans that cater to the specific needs and abilities of individual learners.

    This can help ensure that each learner is able to learn at their own pace and receive targeted support in areas where they may be struggling.

    AI can also be used to create interactive and engaging learning materials, such as virtual tutors or educational games, which can make the learning process more enjoyable for learners.

    Additionally, AI can be used to analyze data about learners’ progress and performance, providing teachers with valuable insights into how to best support their students.

    Here is an example of how AI can be used to support learners:

    1. A learner logs into a learning platform that uses AI to create personalized learning plans.

    2. The AI system collects data about the learner’s background, abilities, and learning goals, and uses this information to create a customized learning plan for the learner.

    3. The learning platform presents the learner with a series of lessons and activities tailored to their specific needs and abilities. These may include interactive games, videos, quizzes, and other engaging materials.

    4. As the learner progresses through the lessons, the AI system tracks their progress and performance and provides them with real-time feedback and support. For example, if the learner is struggling with a particular concept, the AI system may provide additional explanations or examples to help them understand it better.

    5. The AI system also provides teachers with insights into the learners’ progress and performance, allowing them to identify areas where the learners may need additional support and adjust their teaching accordingly.

    Overall, AI can support learners by providing them with personalized and engaging learning experiences, and by providing teachers with valuable data and insights to help them better support their students.

    A SERIES OF ARTICLES ABOUT ‘AI, CLOUD, AND ADVANCED TECHNOLOGIES IN EDUCATION’ WRITTEN BY THE IBL AI ENGINE IN DECEMBER 2022*

     

     

    *The IBL AI/ML Engine extends and hosts leading language models (LLMs) via a combination of fine-tuning, customized datasets and REST APIs to provide an all-in-one AI platform for education featuring content recommendations, assessment creation and grading, chatbots and mentors, and predictive analytics.

     

  • Potential Applications of AI in Education

    Potential Applications of AI in Education

    IBL News & IBL Education | New York

    There are many potential applications of artificial intelligence (AI) in education, including the following:

    Personalized learning: AI can be used to create personalized learning experiences for students, providing them with tailored content and feedback based on their individual needs and abilities. This can help students learn at their own pace and provide them with support and guidance when needed.

    Adaptive testing: AI can be used to create adaptive tests that adjust to the individual student’s level of knowledge and ability. This can help ensure that students are challenged and engaged, and can help teachers identify areas where students may need additional support.

    Automated grading: AI can be used to automatically grade student work, freeing up teachers’ time and allowing them to focus on providing personalized feedback and support to students. This can help reduce the workload of teachers and allow them to focus on more important tasks.

    Language learning: AI can be used to provide personalized language learning experiences, including speech recognition and natural language processing technology to help students learn and practice new languages.

    Virtual tutors: AI can be used to create virtual tutors that can provide personalized support and guidance to students. These virtual tutors can help students learn new concepts, practice skills, and get feedback on their work.

    Overall, the best applications of AI in education are those that help improve the learning experience for students and provide personalized support and guidance. By leveraging the power of AI, educators can create more engaging and effective learning environments that can help students succeed.

    A SERIES OF ARTICLES ABOUT ‘AI, CLOUD, AND ADVANCED TECHNOLOGIES IN EDUCATION’ WRITTEN BY THE IBL AI ENGINE IN DECEMBER 2022*

     

     

    *The IBL AI/ML Engine extends and hosts leading language models (LLMs) via a combination of fine-tuning, customized datasets and REST APIs to provide an all-in-one AI platform for education featuring content recommendations, assessment creation and grading, chatbots and mentors, and predictive analytics.

     

     

     

  • NYU Will Invest $1 Billion Into Its Engineering School in Brooklyn, NY

    NYU Will Invest $1 Billion Into Its Engineering School in Brooklyn, NY

    IBL News | New York

    New York University (NYU) will invest $1 billion in the Tandon School of Engineering, its flagship engineering school in Downtown Brooklyn. The goal is to improve its ranking among competitors while raising New York City’s profile in the technology sector, according to a story in The New York Times yesterday.

    NYU will add $400 million in new funds to the $600 it had already pledged to the school. The funding, which will come from the school’s reserve, will be used over a decade to revamp labs and student spaces at Tandon and expand its focus on cybersecurity and AI technology. In addition, 40 tenure-track faculty members will be hired.

    Tandon School Dean, Jelena Kovacevic, said to the Times, “no university can achieve national or international status without a viable technology school.”

    In 2015, NYU’s Engineering Faculty and Programs and the Polytechnic University renamed its merged school for trustees Ranjan and Chandrika Tandon, who donated $100 million to the institution. Last September, the university purchased a 10-story building in Brooklyn (3 MetroTech Center) to serve as the college’s central hub.

    “Engineering education is a force for social mobility, an economic engine for the borough, and a vital contributor to the city’s effort to be a world center of tech,” NYU president Andrew Hamilton said in a statement.

    The school has had two Nobel winners throughout its history. Rudolph A. Marcus, a former professor at Polytechnic, won the Nobel Prize in Chemistry for his contributions to the theory of electron transfer reactions in chemical systems. Martin L. Perl, a Polytechnic alumnus, won the Nobel Prize in Physics for his pioneering experimental contributions to lepton physics.

    Polytechnic students designed the cables used to hold up the Brooklyn Bridge. Those cables then paved the way for skyscrapers to be built in Manhattan, introducing the concept of elevators.

  • Open edX & Learning Platforms Newsletter | October – December 2022: Open edX, 2U, Coursera, Doulingo, LEGO, MasterClass.com…

    Open edX & Learning Platforms Newsletter | October – December 2022: Open edX, 2U, Coursera, Doulingo, LEGO, MasterClass.com…

    Newsletter format  |  Click here to subscribe ]

    OCTOBER – DECEMBER 2022 – NEWSLETTER #47  |  Breaking news at IBL News  |  Noticias en Español

     

    Open edX

    • The 2023 Open edX Conference Will Take Place March 28 – 31 at MIT

     

    2U / edX Platform

    • 2U Kept Flat Revenue in the Third Quarter of 2022

    • 2U Launches New Boot Camps Under the edX Brand, Retiring the Trilogy Name

    • The London School of Economics Launches a Stackable Pathway to Degrees in Mathematics and Statistics on edX

    • Cognizant Offers Five Train-To-Hire Courses on Java through edX.org

    • An edX Course Created as Peace Project Between Israel’s Jewish and Arab Cultures Makes a Global Impact

     

    Coursera

    • Coursera and SAP Release a Technology Consultant Professional Certificate

    • Coursera Improves Its Note-Taking Technology to Help Learners to Increase Retention

    • Georgetown and Coursera Offer the First Fully Online Liberal Arts Degree

    • Coursera Announces Layoffs Due to Slower Growth Rate

    • Coursera Expands Its Micro-Learning Approach by Adding Thousands of 5-10 Min Videos

     

    Learning Platforms: Transactions

    • LEGO Purchases Education-Technology Firm BrainPOP for $875 Million

    • Genius Group Acquires an American Documentary Film Company to Provide High-Quality Educational Videos

    • Duolingo Purchases the Animation Studio that Works on Its Brand

    • Zovio Sells Fullstack Academy and Liquidates the Company

    • The Owner of Inside Higher Ed Acquires a Leading Student Recruitment Events Firm

    • Anthology Sells the Blackboard K-12 Division

    • Investment Company Thoma Bravo Sells Frontline Education for $3.7 Billion

    • IXL Learning Purchased Emmersion, a Developer of AI-Powered Language Assessments

    • Scholastic Acquired the A2i System for Literacy Instructional Assessment

    • Testing and Assessment Prometric Acquires Finetune Learning

     

    Learning Platforms: Functionalities

    • Zoom Will Soon Be Installed in Tesla Cars

    • The Indian Giant BYJU’S Hires Leo Messi As Its Global Ambassador

    • D2L Issues an Interactive Content Creation Tool With Templates and Themes

    • MasterClass.com Issues a Course with Madeleine Albright and Condoleezza Rice

     

    Funding

    • EdTech Will Expand from K–12 and Higher Ed to Lifelong Learning Economy

    • A British Platform that Teaches Cybersecurity with Gamification Attracts Big Funding

     

    YouTube

    • YouTube Will Launch a @username Format to Boost User Engagement

    • YouTube Will Allow Course Creators to Charge for their Content

     

    Adobe, Figma

    • Figma’s CEO Dylan Field Pocketed One Billion More than Initially Announced by Adobe

    • Adobe’s Stock Continues to Fall as the Market Signals Its Concern About the Figma Deal

    • Figma’s $20 Billion Acquisition by Adobe Causes Concern in the Creative Community

     

    2022 Events | All of the Key Conferences Listed!

    • Education Calendar 2022  – NOVEMBER | DECEMBERConferences in Latin America & Spain

     


    This newsletter was created in collaboration with IBL Education, a New York City-based company specializing in AI-driven, skills learning platforms. We also film and produce courses for universities and business organizations. Read the latest IBL Newsletter   |  Archive of Open edX Newsletters

  • Ohio State University President Steps Down After an Investigation

    Ohio State University President Steps Down After an Investigation

    IBL News | New York

    Ohio State University President Kristina M. Johnson, 65 years old, stepped down following an investigation conducted by an outside firm. The content of that research was not disclosed. The university’s Board of Trustees asked for her resignation on Monday.

    “I’m saddened by the circumstances. My record of accomplishment at Ohio State speaks for itself, and I made the difficult decision to step down,” Johnson said.

    In a statement, Kristina M. Johnson [in the picture] expressed her gratitude and wished everyone the very best in the future. No clue of her departure was issued.

    Johnson has served only 2½ years out of her five-year contract. At the time of her departure, Johnson will have the second-shortest tenure as a president at Ohio State behind only former Ohio State President Walter Q. Scott, who served from 1881 to 1883. That does not include acting or interim presidents.

    Ohio State’s Board of Trustees will begin searching for the university’s 17th president. The university said it will share more information about the search and how the community can participate in early 2023.

  • Online Learning Newsletter | October – December 2022: Trends, AI, ML, Analytics, Universities, Higher Ed, Enterprise…

    Online Learning Newsletter | October – December 2022: Trends, AI, ML, Analytics, Universities, Higher Ed, Enterprise…

    Newsletter format  |  Click here to subscribe ]

     

    OCTOBER – DECEMBER 2022 – NEWSLETTER #53  |  Breaking news at IBL News  |  Noticias en Español

     

    Trends

    • Pandemic-Disrupted Teaching and Learning Effects Will Continue for Decades, Stanford Says

    • Higher Ed Experts Craft Their Vision to Evolve into a Hybrid Learning Scenario

    • “Career Readiness and Skill Competency Are Key Factors to Measure Student Success”

    • Learners Prefer the “Anytime-Anyplace” Approach Along with Blended Technology

    • Online Learning Is Now Seen in Positive View Among Learners, Wiley Says

    • Around 771 Million People Lack Basic Literacy Skills Today

    • Confidence In the Teaching Profession Continues to Decline in the U.S.

    • Students Say that College Is Worth What They Pay Despite the Financial Struggle

     

    AI, ML, Analytics

    • National Louis University Shared Data Model Used For Student Onboarding, Academics, and Support

    • Key Research on Data Analytics Shows How AI/ML Will Shape the University of the Future

    • Most Higher Ed CIOs Are Ready to Invest More in Analytics, Says Gartner

    • “We Need More From Technology,” Says Educause While Presenting the 2022 Top 10 Issues

    • AI Language Model GPT-3 Arrives into Higher Education

    • 74% of Users Prefer AI Chatbots for Answers to Simple Questions

    • 85% of Data is Unstructured and Not Ready for AI Use, Industry Experts Say

    • Data Mismanagement Jeopardizes the AI Achievement, Says an MIT Report

     

    Universities

    • CUNY Unveils a $1.6B Plan to Build a Science Park and Research Campus in Manhattan

    • A Duke Administrator and Cell Biologist Researcher Named MIT’s 18th President

    • Arizona State University Opens a Lab that Will Create a Metaverse with Zoom

    • UCLA Acquires Marymount California University’s Campuses for $80 Million

    • Stanford Law School Launches Controversial Income-Share Agreements as a Pilot Program

    • Harvard Business School Will Offer Its Two-Year MBA Program for Free to 200 Students

     

    Higher Ed

    • Students Name the Best Colleges in the U.S. in Princeton Review’s Annual Survey

    • U.S. Colleges and Universities Saw an Increase of 80% in International Student Enrollment

    • Stanford, Michigan, Duke, Northwestern Law Schools Join the Exodus from U.S. News Rankings

    • Harvard, Yale, and Berkeley Criticize U.S. News Rankings Methodology and Decide Not to Participate

     

    Enterprise

    • Amazon Will Invest $5,250 Per Year For Each Delivery Partner By Providing Educational Programs

    • IBM Teams with 20 Black Universities to Address the Cybersecurity Talent Shortage

    • Oracle Launches a Cloud Infrastructure that Allows ISVs to Run their Own Services

     

    Biden Administration

    • The FTC Sues Chegg for Exposing Millions of Users’ Social Security Numbers and Other Key Data

    • The Biden Administration Launches the Official Application for the Student Debt Relief

    • Six Republican-Led States Sue Biden Administration Over Student Loan Forgiveness Plan

    • President Biden’s Student Loan Cancellation Plan Will Cost $400 Billion

    • Fintech Donation Start-Up Give Campus Raises Massive Funding

     

    Conferences

    • The OLC Conference Awarded Twelve Educators for Innovation in Online Learning

    • The OLC Accelerate 2022 Conference Posts Its Program

    • Educause Recognized Five Top Educators for Their Accomplishments in Higher Ed IT

     

    2022 Events | All of the Key Conferences Listed!

    • Education Calendar 2022  – NOVEMBER | DECEMBERConferences in Latin America & Spain

     


    This newsletter was created in collaboration with IBL Education, a New York City-based company specializing in AI-driven, skills open source learning platforms, and predictive analytics. We also film and produce courses for universities and business organizations. Read the latest IBL Newsletter   |  Archive of Open edX Newsletters