Bloom’s Two-Sigma Problem:
Benjamin Bloom’s 1984 research compared three learning methods: conventional teaching, mastery learning, and one-on-one tutoring.

Conventional Teaching:
Students receive subject matter in a class with a teacher lecturing and assigning texts.

Mastery Learning:
Similar to conventional teaching, but students are tested until they grasp the material. Teachers identify errors, re-teach, and continue testing until all material is learned.

One-on-One Tutoring:
The most effective method but also the most expensive.

Results:
Mastery learning resulted in one standard deviation of improvement over conventional teaching. One-on-one tutoring resulted in two standard deviations of improvement over conventional teaching.

Challenge:
Finding an affordable method that can match the effectiveness of one-on-one tutoring.

Technology’s Potential:
Exploring whether technology can provide an alternative solution to Bloom’s challenge.

Conventional Learning Problems:
* Inattention: Even in 1350, lectures faced attention issues, with only about a third of students actively engaged.
* Duration: Lectures that exceed 20 minutes result in declining attention and effectiveness.
* Oral Learning Style: Lectures cater only to oral learners, neglecting other learning styles such as visual, tactile, etc.
* Portability: Compared to musical performances, lectures lack portability, making access to information limited.

Socrates’ Approach:
* Socrates used one-on-one questioning, acting more like a tutor than a conventional teacher.
* He focused the inquiry, personalized the learning, and sometimes used bullying tactics.
* Socrates’ approach was more effective than the non-tutoring approach of conventional teaching.

The Lecture:
* The lecture was an innovation in 1350 due to the high cost of books.
* It allowed one person to share information with many students simultaneously.
* Despite the invention of affordable books by Gutenberg, lectures persisted.

Challenges with Lectures:
* They cannot exceed 20 minutes without losing effectiveness.
* They suit only oral learners, ignoring other learning styles.
* They lack portability, limiting access to information.

Alternative Learning Style Diagnosis:
* A third-grade teacher claimed to diagnose learning styles by listening to how students talk.
* The method is questionable, as evidenced by a blind engineer who used the phrase “I see what you’re saying.”
* Diagnosing learning styles remains challenging, and students may prefer different styles at different times.

Current State of Music vs. Lectures:
In the past, music options were limited to local troubadours or self-performance. Today, music lovers can access the best performances from any genre at any time. In contrast, lectures have remained largely confined to live performances at local universities, with limited portability and accessibility.

Challenges in Moving to a Star Performer Model for Lectures:
Despite the potential benefits, a shift towards star performers for lectures has not occurred. Reasons for this lack of progress are not fully understood.

Google’s Efforts to Address the Two-Sigma Problem:
Google is exploring various technologies to address the two-sigma problem and move towards a tutoring-based model without the high cost of individual tutors.

Google Applications Education Edition:
Google offers free online applications, including email, chat, calendars, webpages, and documents, branded for educational institutions. When properly integrated, these applications form a virtual learning environment.

Collaboration with Arizona State University:
Google partnered with Arizona State University to provide technology solutions for education. This partnership enables the university to access the latest technology without the burden of high costs.

Open Courseware Index:
Google, Creative Commons, and the Packard Foundation created an index of open courseware from various universities and institutions. This index allows teachers, students, and home learners to easily search and access educational materials.

Google Scholar:
Google Scholar provides access to academic journals and research articles. Some users may not be familiar with Google Scholar, making it challenging for them to find scholarly material.

Combining Scholarly and Non-Scholarly Results:
Google aims to provide a mix of scholarly and non-scholarly results in its search results, catering to users with varying levels of academic knowledge. This approach ensures that users can access relevant information without having to navigate multiple platforms.

Example Search Results for Bigtable:
A search for “Bigtable” yields a mix of academic papers, Wikipedia entries, videos, blogs, and more. Narrowing the search to specific platforms may result in missing valuable resources.

Bloom’s Challenge and Its Significance:
Bloom’s research revealed that the average student under tutoring performed two standard deviations above the control group. This means that 98% of students who received tutoring were above average, with 50% of them performing exceptionally well.

Standard Deviation and Performance:
In a standard bell-shaped curve, 50% of students are above the mean. Mastery learning shifts the distribution to the right, with 84% of students above the control mean and 16% performing exceptionally well.

Time on Task and Attention:
In conventional teaching, students were on task 65% of the time, indicating frequent attention lapses. Mastery learning improves engagement, increasing time on task to 75%. Tutoring achieves the highest level of engagement, with 90% time on task.

Correlation between Aptitude and Achievement:
Conventional teaching shows a strong correlation (0.60) between aptitude (prior knowledge) and achievement (course results). Mastery learning reduces this correlation to 0.35, and tutoring further reduces it to 0.25. This suggests that mastery learning and tutoring provide a more equitable chance for all students to succeed, regardless of their initial aptitude.

Bloom’s Suggestions for Achieving Two Sigma without Tutoring:
Careful review of previous material with enhanced cues, participation, and reinforcement. Implement a student support system, such as study groups of two or three students.

Additional Note:
The research paper mentioned a 1350 painting, which depicted two-thirds of students’ attention wandering during conventional teaching. However, the author acknowledges uncertainty about the accuracy of this data compared to Bloom’s findings.

Motivated Students:
Computer-based learning can be effective for highly motivated students. Some subjects like algebra may be suitable for this approach. However, this might not work well for all students with different interests and learning styles.

Real-World Projects:
Students can achieve remarkable results by working on real-world projects that are personally meaningful. Examples include unlocking the iPhone, designing pulse oximeters, and conducting graduate-level research in high school.

Just-In-Time Learning:
Students learn what they need to know as they progress through a project. This approach fosters collaborative learning and problem-solving skills.

Olin College:
This engineering college emphasizes hands-on projects and interdisciplinary studies. Students start with audacious projects that require them to learn new material quickly. This approach helps students become more receptive to theory later on.

Importance of Social Networking:
Frank Rhodes emphasizes the importance of community in learning. Isolation can lead to narrowness, dogmatism, and untested assumptions. Community provides diverse perspectives and challenges personal discoveries.

Synthesis:
The best education combines motivated students, real-world projects, just-in-time learning, and a strong sense of community. This approach can help students achieve the two-sigma effect and become highly successful learners.

Project-Based Approach:
Engage students in meaningful real-world projects that ignite their passion for learning. Prioritize the student’s enthusiasm over the teacher’s words to enhance learning outcomes. Utilize project-based learning to stimulate excitement and motivation.

Collaborative Learning:
Leverage teamwork to create a cost-effective alternative to individual tutoring. Facilitate peer learning and mutual assistance among students. Transform teachers into facilitators, enabling them to effectively guide and support multiple students.

Personalized Learning:
Recognize that different students learn differently. Encourage students to actively seek knowledge from a diverse range of sources. Avoid creating rigid curricula that limit individual learning paths.

Technology-Enabled Learning:
Embrace the internet’s potential to democratize access to information and resources. Facilitate peer-to-peer connections and global collaboration. Utilize technology to personalize learning and accommodate individual learning styles.

Beyond Rote Learning:
Shift the focus from rote learning to fostering creativity and critical thinking. Encourage students to explore their own ideas and learn from the consequences of their actions. Embrace uncertainty and encourage students to navigate unfamiliar territories.

Criteria for Ranking Creative Commons OpenCourseWare Materials:
Custom search engines like Google Custom Search allow users to prioritize or exclude specific websites in search results. Criteria for ranking OpenCourseWare materials are determined by the publisher of the custom search. Google provides tools for publishers to implement their own ranking policies.

Missing Star Performers in Education:
The concept of “star performers” in education, where certain teachers have a wide reach and influence, has not fully materialized. In music, while live performances still exist, recorded music from a limited number of popular groups dominates consumption. Universities’ influence and the challenges of online learning may have hindered the rise of star performers in education.

The Potential of Enhanced Online Learning:
Online education has the potential to offer higher production values, animations, simulations, and interactive elements. This can enhance the learning experience and make it more engaging and effective. Despite the potential benefits, such enhancements have not yet become widespread.

Learning from the Neanderthals:
Drawing inspiration from ancient learning models, like the Neanderthals driving mammoths off a cliff, can provide insights into effective learning. Real-world problem-solving, collaborative learning, and expert guidance are key elements of this approach. This model resonates with the modern tools and technologies available in online education.

Comparing the Socratic and Neanderthal Models:
The star performer model, with its emphasis on individual teachers, aligns more closely with the Socratic model of education. However, the future of learning may lie in a more collaborative and interactive approach akin to the Neanderthal model. This approach emphasizes hands-on experience, peer learning, and expert guidance, leveraging modern technology.

Apprenticeship Model:
Peter Norvig advocates for a return to the apprentice model of education, where students combine learning with practical experience, similar to Olin College’s approach. He believes this model prepares young people for the real world earlier and reduces the segregation of education from practical applications.

Wikipedia vs. Google:
Kanishk Bedi raises the question of whether Wikipedia’s growing knowledge repository poses a threat to Google’s search engine dominance. Peter Norvig emphasizes that Google values its partnership with Wikipedia, directing a significant portion of traffic to their platform. He believes people will continue to use general search engines for diverse information sources rather than relying solely on Wikipedia.

User-Generated Content and Refined Search Techniques:
A user inquires if user-generated content can contribute to more refined and sophisticated search techniques. Norvig acknowledges that Google techniques and algorithms can sometimes provide overwhelming information. He suggests that user-generated content and feedback can help Google refine its search algorithms and improve the overall search experience for users.

Information Overload and User-Generated Commentary:
The challenge of information overload stems from the vast amount of information available, not just the presentation of search results. Users have limited time and attention to investigate and consume information. User-generated commentary can aid in refining the information overload by highlighting valuable content within the allocated time.

Google’s Existing User-Generated Content:
Google has historically relied on user-generated content in the form of webmasters publishing material and linking between content. These actions provide signals for Google’s algorithms to judge the appropriateness and relevance of web pages. User traffic data is also utilized to gauge the importance of content.

Potential for More Explicit User Feedback:
In addition to existing sources of user-generated content, Google is exploring more explicit forms of user feedback. This includes allowing users to vote on the relevance and quality of websites for specific topics or keywords. The goal is to democratize the process of evaluating content and incorporate a broader range of voices.

Democratizing Content Evaluation:
Google aims to open up the content evaluation process beyond traditional webmasters. By allowing more users to contribute their opinions, Google seeks to capture a more diverse range of perspectives. This approach can help identify valuable content that might otherwise go unnoticed.