Flattening the classroom by flipping the teaching engagement model

Blog post
edited by
Matt Tricomi

Continuing on from: The world is getting flatter – Why isnt our educational system?

With this approach, teaching resources will not be spent on redundant or duplicative efforts such as preparing and delivering the lesson. 

The video lesson and supporting services will do that.  A simple rough order magnitude business case estimates we can shift an enormous set of resources from preparation and delivery to creativity, facilitation and assessment.  Here is how significant a shift it is:

$63,033,390,000 = (180 days/year X 3.5 hours / days X $30/hr.) X 3,335,100 teachers

 

These tools will work for the vast majority of subjects and lessons. This cursory analysis assumes 2/3 of the lessons can be affected and that teachers deliver 5 classes /day with an average teacher salary of $30 dollars an hour sans benefits.  This obviously does not include the cost of developing the alternative content which should be offset by the cost avoidance benefit of not buying text books, improvement in teacher productivity, remedial education etc… 

This approach is certainly not arguing for a reduction in teaching resources or in their level of subject matter expertise.  This approach is arguing for:

  • A reallocation of the resources away from redundant lesson preparation and delivery towards ensuring the lesson is understood.
  • A role change that would place greater responsibility on the student and introduce the opportunity to customize educational delivery.
  • teachers to become facilitators of learning and apply their creativity, knowledge and inter-personal skills but at a different phase of the learning cycle.
  • students to be able to work with parents and other students to comprehend the lesson. 
  • for student centric education.

The combination of the Khan Academy and flipped classrooms allow us to do that.  The target state value chain now adopts the “create and facilitate” functions in lieu of prepare and deliver. (See Figure 2)  Ideally, if this is implemented and it provides the opportunity to save human resources by increasing the number of student to teacher ratio, the resulting resources savings should be reallocated to Early Childhood Education (ECE). Either way, as any rationale individual would conclude, ECE should be a high priority target investment opportunity due to its Return on Investment (ROI) and social benefits (3)

With this synthesized approach, we can achieve a form of scalability that allows us to focus on the application and assessment of the student’s progress.  It allows for creativity and the development of best of breed approaches for lesson preparation and delivery.  Students can progress at personalized rates using tools that conform to their learning styles.

Now, how do now get the best “quality” lesson preparation and delivery?

We take our “best” or most impactful teachers and they become the lesson producers who create and deliver the content for this new model.  We allow the best of breed lessons to develop at a grass roots level and let the market demand for quality establish what is effective.  If we empower the educators, we will find hidden stars and performers and discover teachers who are even more creative in enhancing this new model of education.  We will have tapped into a rare commodity that will enhance other teacher’s approaches and engage the students with a personalized approach. Motivating and positioning teachers to out create one another will only ensure the students are getting the quality they deserve.

Another fundamental deficiency within the current educational system is the limited role parents have.  

They are effectively shielded from the most critical part of the process – delivery. The communication model is woefully inadequate and in essence is single point of failure network with the child as the weakest link. (See Figure 3)

 

This new model allows us to “flatten” communication increase shared access to information between parents, teachers and students. It offers a number of additional possibilities.  A student will be more empowered and vested in their educational journey and will now be more responsible and motivated to set and reach greater educational goals.  The student’s goals and progress will be easily tracked and monitored by parent and teacher.  The approach aligns well with the rapidly developing technology trends on how our whole society is researching, discovering and learning new information – self-paced, personalized and content rich.  Each lesson can be the launch point for self-exploration and research on related subjects or a deeper dive into the content.  A student’s time and motivation, home support or peer group will now be the constraining factors.  The student is no longer the weak link between parent and teacher.  Parents will have the option take a more proactive role. If they do, wonderful, if not, the student has options to pursue with peers or go solo.  Inevitably, as the amount of information and content flow increases between the parents, students and teachers, the awareness of educational system performance and accountability will organically improve. (See Figure 4)

 

We will accelerate the transformation from the teacher-centered pedantic model to a student-centered responsibility model.  

Teachers will fulfill the challenging role of content creation, facilitation and assessment. If it takes the student 10 viewings to understand the lesson, they can now do that without system or peer pressure.  The student may do the lesson by themselves, with their family or with their peers. They can and should discuss it on social networks or in their friend’s basement.  Encourage educational topics to be discussed – anywhere and everywhere. Encourage the growth of educational communities.  Let’s destroy this anti-intellectual notion that we only learn in school and that it is best to learn by oneself.

Extending lesson delivery beyond the classroom, frees the student to collaborate and explore the best means to meet the lessons ends with a less restrictive timeframe.  Students could even share a computer and learn lessons together.  Why not?  Learning with peers has proven to one of the more effective means for intellectual, social and emotional growth.  Students should be encouraged and trained to learn collaboratively.  Why would we want to constrain lessons and learning to a teacher-centric classroom?  This is certainly not what will be expected of them in the workplace or in their personnel lives.  The world is flattening, why not the educational system and the classrooms?

Parents will no longer be “blind” to how good or bad a lesson has been delivered.  

They can be active participants in educating their children using a medium that is much more natural and intuitive than a text book.  They will be able to learn for the first time or relearn, as we often have to, along with their child. They will be able to take an earlier and more pivotal role in the learning process. This is potentially the most valuable and challenging departure from the traditional model. Why is it so important?  Parents will now have the option to model education and learning in addition to all other forms of social norms. Today, we have positioned parents in the background and we wonder why we do not get more school to home communication.  The achievement gap will also improve as we can shift the roles of parent and student to be integral to personalizing the educational experience.

We all know this has to change but we have never given the parents the tools to participate nor have we positioned them effectively in the learning process. 

We ask parents to help with homework but only after the child has had the lesson.  They have no insight into how effectively it has been delivered. We ask the parent to help the frustrated child when the parent has no idea how the lesson is structured or if they are contradicting what has been stated.  Let’s face it. We have outsourced education from the family. If we believe our own rhetoric and the underlying research, we all know that bridging the learning process between educators and family is transformational and the best means to ensure lifelong learners and an educated society.

Teachers should be empowered to create a “marketplace” for lessons and to be permitted to promote and sell them to schools.  

Teachers should be financially compensated for these creative outputs but more importantly honored for creating a better way to educate a student. Education is one of the few work pursuits, other than entrepreneurship, where one can readily create or influence the value of the core product or service.  We can improve educational performance with consistent content that is bundled with a customized delivery that addresses our inherent learning differences. Students should be able to choose from these alternative designs and personalize their educational approach based on what works for them.  We can develop a core lessons taxonomy and semantic model that will provide a means to catalog or organize the marketplace.  Teachers, administrators, students and parents will be able to search and discover based on content and delivery style what is needed for the individual.  Imagine a parent and child researching or shopping for a lesson to understand the Pythagorean Theorem and having choices.  No more running out to shop for just pens, notebooks, rulers and backpacks.  The family can now research and construct personalized curriculum for the school year!

This marketplace would allow teachers to develop a stronger and more creative voice, to be the principal producers of lessons and content that speaks directly to the primary stakeholders – the students. 

Teachers are the ones who get to see and assess what is working every day.  Allow them to build it, evolve it and ensure its impact.  Restore educators to a position of honor and respect.  Give a voice to students who undoubtedly will let the system know when it is not working.  Build a smart system that feeds and learns from itself and in the process let the model flatten.

If we do this with a national commitment, we will quickly rediscover the fact that children are not “robots”. 

They are much more capable of learning and taking initiative than we have come to expect from them.  What is needed is for them to know they are the principal stakeholders in their educational pursuit.  Given the chance they will take an active role in the structuring their educational destiny from the outset in collaboration with parents, teachers, friends and peers. Our future is at stake.

(1)      National Center on Educational Statistics, http://nces.ed.gov/fastfacts/display.asp?id=84

(2)      ASCD September 2009, Volume 15, Number 3, Highly Effective Teachers: Defining Rewarding, Supporting and Expanding their Roles. Laura Varlas

(3)      The Economics of Inequality – The Value of Early Childhood Education  James Heckman, American Educator Spring 2011http://www.aft.org/pdfs/americaneducator/spring2011/Heckman.pdf 

The world is getting flatter – Why isnt our educational system

Blog post
edited by
Matt Tricomi

Problem: The world is getting flatter – Why isn`t our educational system?

There are massive functional and communication inefficiencies inherent in our current public educational system at the elementary and secondary levels.  The problems are:

  • Lesson preparation and delivery work activity is highly redundant and costly.
  • Effective communication between student, teacher and parent is woefully inadequate and compromises student potential

Using simple architecture analysis techniques looking at the enterprise and specifically dissecting the education segment, these inefficiencies have been identified, modeled and evaluated and mapped to emerging educational solutions that will redress them.  The educational solutions presented in this paper have been developing organically within the education community but do not have a cohesive adoption strategy that will optimize their full potential.

What is insanity? 

According to Einstein “it is doing the same thing over and over again and expecting different results”.  What does this quote have to do with our approach to education?  This is what we do; year after year after year.  During a typical school year, our 3,335,100 public school teachers working in 98,817(1) elementary, middle and high schools, prepare lesson plans, deliver lessons and assess student’s progress that to a large degree are redundant (See Figure 1).  This is performed at the cost of approximately $63 billion dollars a year.

 

Is this really the ideal way to run an educational system?  Is it the best use of skilled professional’s valuable time?  Is it a good use of a tremendously valuable and costly public resource? Here is the size of the resource pool that currently works in the U.S. primary and secondary education system:

  • ES and K Teachers 1,655,800 – Median Salary $50,150
  • MS Teachers 641,700 – Median Salary $50,770
  • HS Teachers 1,037,600 – Median Salary $52,200 (2)

To illustrate the point, every year tens of thousands of elementary school math teachers prepare and deliver a lesson on adding and subtracting negative numbers to their 25 or 30 children.  

Each teacher would have invested varying levels of rigor, dedication, creativity, design or customization to their approach.  Once done, the average teacher could probably expect a third of their students not be challenged, one third in need some moderate assistance and the rest to be struggling or in the process of giving up.

It is way too easy to blame the teachers. It is convenient and perhaps fashionable, to say it is the teacher’s shortcomings and fallback on sound-byte-based thinking:

  • They are not well enough prepared,
  • We don’t get the “best and the brightest”
  • Old fashioned, technically illiterate,
  • Unions, tenured and lazy,
  • Out of touch with current pedagogical approaches.

The vast majority of classroom teachers face the daunting reality that students learn in many different ways, at different rates, have different states of cognitive, emotional, and social readiness.  Not an uncommon phenomenon in most classrooms.  Imagine an educational model where the availability of a highly qualified teacher, their devotion or the amount time they have to solve a student’s learning barrier is no longer tied to a classroom clock.

Recent research strongly suggests that a highly effective teacher, given three years, can impact student achievement by 50 percentage points (2) when results are compared against other teachers and standardized test scores.  

 Regardless of one’s opinion of the value of standardized testing, these teachers are doing something very right.  They have “it”.  The data implies there are inherent benefits to be realized in high quality lesson preparation and delivery based on these individual success stories.  If we assume that only 5% of the teaching profession possesses this impact quality, it would leave us with a serious question: Can we significantly raise the performance of our teacher to a point that we could fundamentally change the existing educational model’s performance?  Let’s face it; teachers are no different than many other professionals.  They are subject to the same bell curve as are lawyers and doctors and engineers. We have a few great ones, a number of good ones, some in the middle amongst others. Enough said.

Are we betting our future on great teachers, a skill that seems to be pretty rare and should be highly cherished? 

Do we think we can train or re-craft even half our teachers to be that impactful?  No company of 1/10,000 the size of our education system would dream of trying such an approach.  Even if the best and the brightest wanted to commit to education, would we have enough money to pay for the quality and retain them? What would a business do?  They would analyze their value chain and the supporting processes and technical capacities to see what can be done to improve overall performance of the system.  They would not focus on just one high value component.  Companies would research and develop cost effective alternatives that drive systematic improvement.  The investment would be designed to compensate for the inadequacies of the system and attempt to improve the overall performance. 

In this case, how can we systematically improve the quality of lesson preparation and delivery to ensure greater student achievement? How do we tap some of those intangible qualities of impactful teachers and make them available to more students?  How do we increase the number of students who can demonstrate they  “learn” the lesson and improve their educational foundation? In essence, how do we create greater value from those rare teachers and their proven techniques?

Within education today, there are a number progressive grass root movements that are beginning to show the way to do just that. 

Many people have heard of the Khan Academy, an evolving multiple discipline digital video curriculum that enables students to interact with a lesson at their own pace, both outside or inside the classroom.   Another fascinating development is the flipped classroom. Here, creative teachers, once again, using digital video technology and the Internet, have developed video based lesson plans that allow the student to educate themselves, at their pace, within the confines of a coordinated schedule.  The student accesses the lesson online while they are at home or at a friend’s house.  The understanding of the lesson is assessed during the classroom hours.

While the students are learning the lesson at home, the teachers will have transformed the classroom time into working sessions.  In this milieu, the students get help with the application of the lesson via “homework” exercises, group discussions, collaborative projects and ultimately ensuring the qualitative understanding of the lesson.  Those that can learn faster learn more.  Those that need help are given assistance. These approaches allow students to absorb the lesson and push themselves towards personal growth instead of being subjected to the fundamental constraining parameter – the amount of teaching time in the class room.  A classroom of 25 to 30 students with differing skills and modes of learning are now free to spend the “appropriate” time to absorb the lesson in much more effective and personalized ways.  This can level the playing field and address the socio-economic achievement gaps within the system.

For more on the recommendation, continue reading to the next blog post: 


Data Science Research Areas Punch List

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added by
Wiki Admin

In Launching this Data Science Research service area, the following are areas of data science research we are actively pursuing.

Solutions 

  • Tactical Industry and Trend Context Reports: Data Visualizations
  • Implementable Changes in Industrial Engineering Practices
  • Linking Research & Commercial Industries
  • Crowd and Commercial Effectivity
  • Place-based and Geospatial business cases and impact levels by data theme, product, and service types
  • Semantic vs. machine learning applications for integrating large Corporate or Government common datasets
  • Real-Time National or World Scale Topological Big Data Modeling and Decision Support 
  • Proving existing major corporate and government datasets, social information data quality and semantic readiness, and existing or new platforms and applications to support Smart Cities in simulation environment such as urban planning, decision making, and policy/rules-based intelligence (aka Real-world SimCity and Civilization models)
  • Remote Sensing Integration with BigData Sources and Analytics
  • New Energy Model Research & Development Repository and Social Network Enhancement
  • Information Patterns & Historical Analysis
  • Integrating Computer and Library Science Techniques
  • Blending Machine Learning and Semantic Web
  • Historical Timeline Visualizations – knowledge, technical evolution
  • Roadmap Prediction Visualizations
  • AI/Robotic Integration with Decision Making
  • Data Supply Chain models analysis in support of creating data ecosystem flow for major static and real-time datasets.
  • Impacts of Next Generation or Internet2 architectures on existing content and dataset

Management

Data Science and Architecture Management Research

  • Integrating Academic GeoScience Communities using Architecture Methods 
  • Investigating how Bill/Policy Motives align with Federal Portfolio
  • Leveraging Architecture concepts to advise and improve bills
  • Real-World Enterprise Architecture analysis
  • Federal readiness for architecture and change management maturity by agency using 
  • Performance Measurement analysis for management and budget policies
  • Reduction and impact evaluation of burden on government agencies for data calls – 
  • Value-measurement on policies and metadata
  • Strategic progression of maturing datasets (i.e. What dataset to build next and butterfly effect?)
  • Realistic blending of private sector and public sector best of breed techniques
  • Historical context analysis for current information management policy and bills for future decisions
  • Analyze policy shaping techniques (i.e. market-driven policy, policy reformation, protectionism policy, new value transition or adoption) diversity by industry.
  • Improving Product Management Subjectivity
  • Agile Project Management
  • Architecture Methodology
  • Data Supply Chain Management efficiency patterns
  • Integrating Geospatial Architectures into Industry
  • Industry Acceleration & Stabilization Evaluations
  • Gaming theory application readiness for Corporate and Government policy and increasing energy and quality output (i.e. MMORPG, Social Network, Strategy games, incentive models, talent/skill development, state of integration such as Mechanical Turk models).

Data Science Research Concepts

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added by
Wiki Admin

Our corporate goal is two-fold:

  • Analyze and assure forward-thinking concepts are applicable
  • Increase our expert staff knowledge base

We first need to assure our concepts and consultants are current, relevant to our partners, clients and industry, and forward thinking; second, allowing for us to excite, retain and increase our talent knowledge base for longer period of time than typical consulting-only firms which allows us to lower personnel costs and maintain lower overhead costs. 

We are actively working and establishing new research partnership academia (i.e. major university research hubs, local STEM programs), government (i.e. Federal Programs, State, Local), municipal services (i.e. water utilities), and engineering/scientific service companies.

In considering the types of innovative data science research that Xentity is seeking to make a transformative impact upon Data Science Solutions Research and Data Science and Architecture Management Research

How do we stay on top of the evolving world of data science

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edited by
Wiki Admin

Our goal is stay involved in understanding the newer approaches, patterns and concepts in business, technology, policy and governance that could help enhance our customers capabilities in our core services based on readiness, maturity, and industry need in data science. 

In Research, we continually re-invest in new models, patterns, and constructs that go back into our designs. We are investigating new data solution architectures and methodologies to keep up with massive, and rapid change.

Our research areas will be in testing early architecture concepts and patterns that are new to client program and organizational adoption as well as research enhancements in management constructs. This could result in adding credibility to newer architectural patterns or analyzing or creating methods, approaches, and maturity for readiness for client adoption in corporate and government environments.

How can integrating data enhance products, management, applications, remote sensing, knowledge building, and culture impacts (positive and negative)? 

We are participating in forward looking academic research looking at the next wave of architecture and management in regards to Data Science

  • Can place-based and geospatial data themes, products and services be demonstrated in business cases to truly impact all areas of business – for earth-based issues to enterprise resources to social science? 

  • What is the right level of progression for metadata programs to enter into improved discovery. What is the investment balance of moving into semantic web models or interpretative signals and machine learning?
  • Do we understand national and industry datasets butterfly effect to guide strategic national or corporate investment in maturing data strategically?
  • How can we accelerate the induction of supply chain management concepts proven for decades in capital investment and industrial engineering into data science and data management?
  • How to take crowdsourcing to next maturity of game theory to not only enhance data, but increase the quality output of data and reducing the energy?

These are some of the topics we are actively and seeking to engage in the study of data science. Our research areas seek to test early architecture concepts, patterns, and management constructs  that are new to client programs and organizational adoption. 

What topics are we interested in?

 

We are actively working and establishing new research partnership academia (i.e. major university research hubs, local STEM pograms), government (i.e. Federal Programs, State, Local), municipal services (i.e. water utilities), and engineering/scientific service companies.

 

In considering the types of innovative data science research that Xentity is seeking to make a transformative impact upon the following captures some of the directions Xentity is investigating. The following are example architecture solution and management research topics and areas for information integration, information service, and analyis and synthesis research include

 

Data Science Solutions Research

 

  • Tactical Industry and Trend Context Reports: Data Visualizations
  • Implementable Changes in Industrial Engineering Practices
  • Linking Research & Commercial Industries
  • Crowd and Commercial Effectivity
  • Place-based and Geospatial business cases and impact levels by data theme, product, and service types
  • Semantic vs. machine learning applications for integrating large Corporate or Government common datasets
  • Proving existing major corporate and government datasets, social information data quality and semantic readiness, and existing or new platforms and applications to support Smart Cities in simulation environment such as urban planning, decision making, and policy/rules-based intelligence (aka Real-world SimCity and Civilization models)
  • Remote Sensing Integration with BigData Sources and Analytics
  • New Energy Model Research & Development Repository and Social Network Enhancement
  • Information Patterns & Historical Analysis
  • Integrating Computer and Library Science Techniques
  • Blending Machine Learning and Semantic Web
  • Historical Timeline Visualizations – knowledge, technical evolution
  • Roadmap Prediction Visualizations
  • AI/Robotic Integration with Decision Making
  • Data Supply Chain models analysis in support of creating data ecosystem flow for major static and real-time datasets.
  • Impacts of Next Generation or Internet2 architectures on existing content and dataset

 

Data Science and Architecture Management Research

 

  • Investigating how Bill/Policy Motives align with Federal Portfolio
  • Leveraging Architecture concepts to advise and improve bills
  • Real-World Enterprise Architecture analysis
  • Federal readiness for architecture and change management maturity by agency using 
  • Performance Measurement analysis for management and budget policies
  • Reduction and impact evaluation of burden on government agencies for data calls – 
  • Value-measurement on policies and metadata
  • Strategic progression of maturing datasets (i.e. What dataset to build next and butterfly effect?)
  • Realistic blending of private sector and public sector best of breed techniques
  • Historical context analysis for current information management policy and bills for future decisions
  • Analyze policy shaping techniques (i.e. market-driven policy, policy reformation, protectionism policy, new value transition or adoption) diversity by industry.
  • Improving Product Management Subjectivity
  • Agile Project Management
  • Architecture Methodology
  • Data Supply Chain Management efficiency patterns
  • Integrating Geospatial Architectures into Industry
  • Industry Acceleration & Stabilization Evaluations
  • Gaming theory application readiness for Corporate and Government policy and increasing energy and quality output (i.e. MMORPG, Social Network, Strategy games, incentive models, talent/skill development, state of integration such as Mechanical Turk models).