Archive for Teaching and Learning

Book Review and Further Thoughts: From the Ivory Tower To the Schoolhouse

schoolhouse2How much does educational research affect teacher practice? Not much, according to Jack Schneider, Holy Cross assistant professor and author of the new book From the Ivory Tower To the Schoolhouse: How Scholarship Becomes Common Knowledge in Education. Schneider, an educational historian who earned his Ph.D. at Stanford, picks up the torch carried by Larry Cuban and David Tyack for years. As institutions, schools are extremely resistant to change, and reliable pathways for translating research conclusions into practice are largely absent. So, when education practice does change as a result of education research, the reasons are worth close examination!

In the book, Schneider describes a model for the transmission of research-based ideas into practice, based on his study of four innovations that made the leap: Bloom’s taxonomy, Howard Gardner’s multiple intelligences, the project method, and direct instruction. Schneider is clear to explain that these four ideas represent the exception, not the norm. Also, the components of Schneider’s model for success hardly comprise a recipe. They are necessary, but not always sufficient, qualities for successful adoption. As Schneider expresses, luck plays a role.

Schneider’s conditions for successful transmission include: the perceived significance of the idea to educators; philosophical compatibility of the idea with current philosophy; occupational realism—the compatibility of the idea with practical constraints of teaching; and transportability, whether the idea can be simply explained and passed on. The four case studies share these qualities. Additionally, Schneider cleverly analyzes four other, research-based ideas that failed to gain adoption but bear striking similarities to the four that did. This provides strong support for the idea that the four identified characteristics are necessary conditions for adoption.Note that the scholarly merit of the idea does not make the list of success factors! With a positive reaction from educators, and a little luck, some research-based ideas tend to find adoption.

While a wonderful historical analysis, the book does not purport to predict the success of current educational innovations or provide a playbook for the design of future innovations. At the same time, I cannot help but wonder how the model applies to other, common educational practices, particularly those that we emphasize at U Prep. How does Schneider’s model apply to formative assessment, for example? Do we find such educational practices attractive because they meet Schneider’s criteria for successful transmission from research to practice?

Formative Assessment

We define formative assessment as actionable feedback on student work that does not count for a student’s term grade. Graded or ungraded, it provides students with insight into their mastery of the content, as well as a sense of direction for what to study more (or better) before the summative assessment. Not counting formative assessment in the term grade allows students to focus on the process of learning and deemphasizes the idea that students have fixed ability.

Perceived significance: Moderate. Teachers I have met almost universally agree that providing feedback on student work is one of their core responsibilities. However, teachers often balk at the idea that grades for ongoing work would not count in a student’s term grade.

Philosophical compatibility: The core idea of formative assessment is relatively compatible with common teacher opinions about student work. It’s hard to argue against feedback, and it makes sense that a student’s first assessment should provide signposts for subsequent work instead of affecting their term grade, which should reflect mastery achieved.

Occupational realism: The simple version of formative assessment is highly compatible with existing teacher practice. Just don’t count the first assessment of a body of knowledge or set of skills, then count the second or subsequent ones. The fuller concept, however, requires more significant change. The ideas that formative assessment should be specific and actionable represent a more significant departure from traditional teacher practice.

Transportability: The basic concept of formative assessment can be easily distilled to a few simple ideas and shared with teachers. Departures from the strategy are easy to spot in syllabi and examples of assessed student work. Authors and organizations have created a substantial body of conceptual and practical guides to formative assessments for the consumption of educators.

It might provide insight to apply this model to other educational practices, such as differentiated instruction, 1:1 student device programs, and individual teacher improvement. While these four criteria do not reflect any law of nature, they provide a helpful dose of realism when leading school change, underscoring the strong effects of professional culture.

Recent articles by Jack Schneider

‘If only American teachers were smarter…’ Washington Post

Closing the gap … between the university and schoolhouse Phi Delta Kappan

The Role of Data in School Decision-Making

Analyzing student and faculty data has added a critical new dimension to discussions of specific dynamics in our school. Teacher observations, administrator experience, and student anecdotes are all essential for the continual improvement of our school program. In addition, the trends, correlations, and distributions within our data have made our decision-making conversations more specific and helped resolve conflicts among competing, anecdotal points of view.

We have recently had success analyzing student and faculty data to better understand specific dynamics in our school. Many of these analyses become more clear through data visualization. Key questions include:

How often do we grant students’ top course requests?

Will our course offerings continue to accommodate a growing student body?

Are the foundational skills of our students changing over time?

Do standardized test scores predict academic performance?

What elective courses should we offer next year?

Do electronic textbooks save families money?

Our analyses of standardized test scores were the most rigorous. We created longitudinal charts of score means and medians, examined subscore trends as well, and calculated correlations among different scores. To confirm validity, three different groups performed the tests: myself, our statistics students, and a psychometrician from ERB. The fascinating, consistent result? The gut feelings of our community members have consistently had some truth to them, but anecdotal opinion has a tendency to exaggerate and oversimplify. Our data studies have both validated and identified the limits of anecdotal opinion. They have clarified the multiple facets of issues that people have reduced to simple statements.

Here are some examples of our data visualizations. Most are created in Excel using countif() and sumif() functions and chart tools. I apologize for obscuring much of the content for the sake of privacy. Instead of publishing it all publicly, I am presenting the full studies to the appropriate constituencies in our school community.

35 years of standardized test and GPA means

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Students’ initial thoughts about new elective courses

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Correlations among different standardized tests and GPA

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Longitudinal subscore analysis

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Print vs. Electronic Textbooks: Total Cost per Student

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Elective section enrollments

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Uses of Technology to Enhance Formative Assessment and Differentiated Instruction

CiC Tech Formative DifferentiatedAcademic Technology Director Jeff Tillinghast and I have co-authored an article for Curriculum In Context, the journal of the Washington State Association for Supervision and Curriculum Development, an ASCD affiliate. We wrote a practitioner’s view of how our teachers use contemporary computing technologies to provide specific, rapid, and varied feedback to students and then accordingly adjust individual student instruction. Read the article (PDF) or access the full issue. Many thanks to Seattle Pacific University professor David Denton for inviting us to contribute to the journal.

 

Computer Science: Where Are We Now?

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The view from my seat

At the NWAIS Educators Conference two weeks ago, I facilitated a session to gather teachers and school leaders to discuss the current state of computer science instruction in our schools. The importance of learning coding, in particular, has received much national attention lately through initiatives such as Code.org, Hour of Code, and the Maker movement. Computer Science courses at major universities have exploded in popularity. Technology use has become ubiquitous in practically all aspects of life and work. K-12 schools are wondering how to modify their programs in response. Should all students learn to code?

At the same time, I wonder whether parallels exist with the programming instruction movement of the 1980’s. More accessible computing languages such as BASIC and Pascal led to similar calls for programming literacy. Many K-12 schools offered their first programming courses, and a number of colleges made basic coding a graduation requirement. However, personal computers also became more available during this time, and technology literacy surpassed programming as the required competency. Programming receded as a K-12 course of study, even disappearing entirely from some schools.

At the NWAIS session, we discussed a series of questions that I think are fundamental to the question of computer science at K-12.I deliberately avoided typical questions such as what programming languages we teach or what computing platforms we use. Participants offered responses to these questions and shared a wide range of new ideas that they are trying at their schools.

What are the pros and cons of “coding?”

I asked this question to explore the distinction between coding and computer science, which I think is fundamental to the longevity and educational value of computer science instruction in K-12 schools. Coding refers to the writing of code, also known as programming, a core concept in the field of software engineering. However, software engineering is just one specialty in the discipline of computer science, and it’s an applied field, not even in the core of the discipline. A 2005 report by the CSTA Curriculum Improvement Task Force noted:

… the view that computer science equals programming is especially strong in most of the curricula because introductory courses focus (sometimes exclusively) on programming and this focus limits the ability to reliably describe the intellectual substance of the discipline. (Denning, 2004)

The core ideas in computer science are theoretical and perhaps most accessible to K-12 education through the concept of “computational thinking.” Logical and sequential reasoning, algorithms, data structures, and systematic approaches to problem solving are some of the principal concepts in computer science. Students can explore and learn these ideas with programming and even without a computerScratch is a popular learning environment in elementary grades in part because it captures some fundamental CS concepts so well, although one might argue that is miseducates for other concepts (e.g., variables).

Interestingly, the distinction between coding and computer science did not resonate with most of the participants in our conference session. While they expressed many positive reactions to the nationwide emphasis on coding, they did not share our concern about the potential conflation of coding with computer science. One school did support the idea that computer science is broad field with many applications. As an example, they offer two computer science electives, Software Development and Design & Technology, that underscore such distinctions.

Which department should house CS courses?

Similarly, the decision of where to house computer science courses has many implications. At different schools, the math, science, arts, and even languages departments house and provide credit for computer science courses. However, theorists agree that computer science is a distinct discipline, and universities typically have a college for computer science, sometimes joined with engineering. Some high schools affiliate with this idea by creating a computer science department even if it includes only one teacher. U Prep created a “general studies” course category (not an actual staff department) to house computer science, digital media, journalism, and global leadership courses.

At the elementary level, the question is a bit simpler, since the school day typically includes just two kinds of classes, homeroom and specials. “Computer class” can house many applications of technology, including computational thinking, what problems technology is good (and bad) at solving, simple physical computing, computer ethics, and basic software development. Or, computing can be integrated within homeroom.

How may we reach all students with CS? How may we attract and retain girls and traditionally underrepresented minorities?

Historically, computer science courses have appealed to a niche group of students, likely due to a self-reinforcing cycle of cultural stereotypes, curriculum, and teaching styles. How may we broaden the appeal of computer science so that all students at least consider that they might find an elective course in computer science interesting and fulfilling?

We are trying several approaches at U Prep. The school’s first full-time computer science teacher earned her major in gender studies, minor in theoretical computer science, and master’s degree in teaching. She therefore possesses the variety of life experiences needed to design our computer science program for content, teaching methods, and social dynamics. We can deconstruct how different students contextualize computer science within their cultural contexts and act in a manner that is responsive to their needs.

Another key idea in our program is the introduction of computational thinking to all students through the required courses in our early grade levels. Our computer science teacher also partners with our sixth and seventh grade science and math teachers to ensure that all students have a direct, positive experience with computer science before they have the opportunity to select subsequent elective courses.

How may we meet the needs of CS enthusiasts?

While it is critical to consider our “non-majors,” we also want to meet the needs of our computer science enthusiasts and provide welcoming spaces for geeks and non-geeks alike to explore and learn with different technologies. We aim to provide students who express high interest in computer science with a theoretical grounding through our CS courses, as well as an array of student-led, faculty-supported clubs, so that they may explore specialized fields such as mobile software development, physical computing, web programming, and security.

How can you attract and retain great CS teachers?

It is very difficult to attract and retain full-time computer science teachers at K-12. One may try to hire computer science specialists, but they tend to have little teaching experience and more lucrative job offers beyond education. Or one may hire candidates with solid teaching experience but little subject matter expertise. Neither case is ideal. At U Prep, we are trying a combination of both ideas, following the model we learned about at Menlo School. Our full-time computer science teacher plans to work with interested math teachers to first integrate computer science instruction within math courses and then recruit and train up interested math teachers to teach introductory computer science courses. While this may blur the lines between disciplines, it has a good chance of growing our pool of qualified teachers of computer science.

Where may you get support and ideas?

During a time of rapid change in the discipline, and its application to K-12 instruction, it is critical to have a solid network of CS education professionals to share ideas and approaches, and provide support for one’s work within schools. Here in Seattle, we are lucky to have the Puget Sound Computer Science Teachers Association and the University of Washington’s Computer Science and Engineering K-12 Outreach Program. Both are invaluable in our development of computer science curricula. You probably have a CSTA chapter in your area.

Book Review: Making Learning Whole

Making Learning WholeIn Making Learning Whole, David Perkins provides a highly accessible, comprehensive summary of curriculum design principles that encourage thinking, engagement, and mastery. Perkins frames the discussion within a sports metaphor, comparing the way that young people play a “junior version” of professional sports to how students might master the fundamental concepts and skills of an academic discipline such as English or science. The concepts themselves are commonly expressed in the technical language of education theorists — zone of proximal development, experiential learning, and so on. Perkins wraps these ideas within an overarching framework of accessible, common language that is friendly and approachable.  It helps if you have heard these terms before, but Perkins helpfully summarizes each concept in case you have not.

Perkins addresses one of the most significant but not well-publicized core problems with education in the United States today: the epidemic of student disengagement with school learning. American schooling has become a chore that the great majority of students suffer through. Content is dry, disconnected from real life, and overly procedural. Although many students learn to play the game of school and find success, most leave so much engagement and learning potential on the table, and an alarming number fail outright. Some find their passion for learning outside of the core school program, either in co-curricular activities or through personal hobbies. Schools, not students, are the problem. Perkins would like to see teachers “make the game worth playing.”

Unlike some education books, Perkins does not limit the text to one education concept. Each of the seven principles of “making learning whole” includes within it several curriculum design principles gleaned from education research. For example, “work on the hard parts” encompasses practice activities, formative assessment, peer- and self-assessment, isolation/reintegration, six forms of knowledge, and instructive exercises. This makes the text a rich resource for learning the practice of curriculum design, whether one is relatively new to the field or a seasoned educator.

Perkins takes the sensible route between competing ideologies. While firmly constructivist, Perkins acknowledges the importance of basic skills acquisition and other hallmarks of traditional education. He thus avoids the pitfalls of binary education debates and emphasizes a holistic view of education. For example, when exploring “playing the whole game,” Perkins includes “project-based learning, problem-based learning, case-based learning, community action initiatives, role-playing scenarios, formal debate, and studio learning.” Each of these learning forms has its books and proponents. Perkins skillfully emphasizes principles shared among these while acknowledging differences, an approach friendly to education practitioners.

The chapter on “the hidden game” is particularly powerful, as it treats fundamental flaws in thinking processes that pervade student (and teacher) work. Deficits in self-management, causal thinking, depth of explanation, and complexification affect not only learning but full participation in society. Perkins badly wants students to become logical, critical thinkers who achieve a depth of understanding that prepares them to more fully understand big, sometimes contentious ideas of our time: evolution, climate change, global conflict.

In contrast to some education experts, Perkins believes that quality curriculum is more important than quality pedagogy. Noting that students forget most of what they learn in school, one might think that the process of learning wad more important. Perkins is unwilling to throw in the towel on content, rather suggesting that reorganized content has a chance to stick.

The education profession badly needs more books like Making Learning Whole, which presents a wide range of teaching practices within a highly accessible, overarching frame. All too often, problems in education are reduced to simple forms that writers purport to solve with simple solutions. Perkins embraces complexity but also provides an opening for the everyday teacher, parent, or student to understand it. Perkins’ contribution may help the general public understand that education is a complex profession in which well-trained professionals should be supported and empowered to deepen their practice and give all kids the quality education that they deserve.

Data Visualization For Learning

While written and oral language dominate instruction, the explosion of visual information has created new opportunities to represent complexity, reveal themes, explore data, and communicate information in powerful ways. Here is an overview of some of my favorite examples of visual data representation for education.

Molecular Models

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Image from http://pymol.org/

Students cannot see individual molecules and are normally confined to shaded textbook illustrations and small plastic model building kits. Molecular modeling software represents data from crystallographic analysis of substances as 3D graphics. This allows students to more fully develop their mental concept of molecules through zoom, rotation, color, and different representations (line, spheres, mesh, etc.). Students can quickly load and manipulate dozens of different molecules (e.g., amino acids), or large molecules with interesting symmetries and structural regions (e.g., DNA, proteins).

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An alternate representation of water (http://pymol.org/)

Graphs and Charts

Most of us cannot discern patterns and trends in numerical data and instead rely on graphs to reveal them. Commonly available graphing tools have continued to improve in sophistication and integration with specific types of data sets.

GapMinder opened many eyes to the explanatory power of visually representing a huge variety of demographic data. Trends in HIV infection rates, distribution of wealth, and dozens of other data sets become visible through bubble charts. Animation makes visible trends as the data changes over time.

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HIV Epidemic 1980-2009, GapMinder

Logger Pro draws line graphs of experimental data collected from Vernier data probes. This creates nearly instant visual representations of physical phenomena as they happen.

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WorldMapper displays international demographic data differently, by distorting the sizes of countries based on different demographic measures. Map mashups have taken social networks by storm in the past year, whether in the more complex form that shades states (or even counties) based on different measures or the simpler form that simply labels states with words or visuals to reflect a trend.

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http://worldmapper.org

The D3 JavaScript library likely represents the future of mainstream data visualization. Anyone with a command of programming fundamentals can use the library to create stunning, animated representations of custom data sets. Such animations now occur commonly in mainstream publications such as the New York Times. The D3 website contains over 200 examples with source code, which one can download and modify for personal use. The range of visualization formats is stunning, driving home the idea that a practically infinite series of graph types exists beyond the usual bar, line, and pie charts. Interactive animation allows the user to see relationships and themes within the data in a manner that goes far beyond static charts.

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Source: http://d3js.org

Word Clouds

Word clouds represent text information in a simple way, by having the word size reflect its frequency in a body of text. Its effect is very direct, albeit limited, as single words lose a lot of their meaning out of the context of phrases and paragraphs. The word clouds of all of the State of the Union addresses is an effective example of making themes in history visible through word clouds.

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2013 State Of the Union Address, ABC News

Concept Maps

Concept mapping has been around for a long time but hit its peak with the use of Inspiration software. Learning specialists have advocated concept and mind mapping for years to allow students to visually organize concepts for pre-writing as well as conceptual understanding. When paired with high quality questions and feedback, concept and mind mapping can encourage critical thinking and direct study of the relationships among concepts in a topic.

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Example concept map from Inspiration.com

Earth and Space

I recently saw one of the old “Puget Sound From Space” posters hanging in a classroom.The qualification from space seems quaint now that our students can smoothly pinch and zoom satellite databases using their own phones and tablets. Thanks to Google Earth, perhaps we no longer consciously realize that most geographic and stellar imagery is a visual representation of satellite and telescope data. Radar and spectral data is combined with colorization to represent distant or very large objects as if we are viewing them with our eyes. We would also do well to remember that the objects we “see” are also only the mental representations of the patterns and qualities of light passing through our eyes and interpreted by our brains.

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http://frontierfields.org/

 

Reflections on Computer Science

We at U Prep are partway through the redesign of the school’s computer science program, to reimagine it as the study of foundational principles of computational thinking, accessible to all students regardless of prior background, and inclusive of highly engaging specialities such as robotics and website development.

The full plan includes three computer science elective classes, the integration of computer science activities into required middle school classes, and advising student clubs in robotics and other technical pursuits. This way, we will give all students the opportunity to do computer science and also provide those interested in further study an array of engaging opportunities at more and less technical levels.

While we put the full plan into place, we decided to offer a computer science course to students this year, even though our new model was not yet fully developed. Student interest was very high, and teaching a class would give us first-hand experience with developing curricula around these new principles. We staffed the course by hiring a subject-matter expert to partner with me as the experienced teacher. At the same time, we began the search for a full-time computer science teacher for next year.

We designed the course to teach fundamental concepts in algorithmic processing and data structure design through programming activities, so that students would receive explicit instruction in foundational principles of computer science while also learning programming skills. Programming was the most common learning activity, and key concepts included use of functions to repeatedly perform tasks, thinking logically and sequentially, breaking a problem into smaller parts, and figuring out how to organize real world data into structured elements. We made explicit links between the problems students were solving and the underlying concepts and thinking skills that are used throughout computer science.

We wanted students to learn to program in an environment that they would be able to use subsequently in future courses and their personal pursuits, to mirror how computing is now used in all fields of study and professions. We chose JavaScript as the development language for several reasons. The web-based applications that students commonly use (e.g., Facebook, Google Drive), are written in JavaScript. Study of JavaScript helped demystify software development, as students recognized the input elements and output formats that they created. While not an entirely strict language, JavaScript has consistent enough structure and data typing that we could teach these principles perfectly well. The development environment (Komodo) is free and multi-platform, ensuring that students could develop using their own computers and continue to use what they learned after the course was complete. The output environment (Chrome web browser) is familiar, yet students gained a new level of understanding of web page structure and performance as they created website software and debugged it using Chrome’s developer tools.

Most class time was spent writing code to solve specific problems, small ones at first and larger ones later. Students analyzed grade level enrollments, Sounders FC player salaries, and animated bouncing balls and streaming bubbles. Each activity built up students’ understanding of programming constructs, input and output, functions, parameters, and return values, conditionals and loops, arrays and objects, speed and memory usage, and more.

Students completed both a substantial individual project and a self-designed group project. In each, we explored how to analyze a real-world problem and design a solution, how to create, test, and refine software, and how to bring a project to completion. The group project introduced new dynamics: how to share, divide, and reconcile project design and development tasks among team members, and how to use an online, collaborative development environment to work on a project within a team.

Students also completed an individual research activity, in which they found and interview a computer science professional and made a short presentation to their classmates. This helped broaden students’ concept of what it means to do computer science work. Not all interview subjects were software developers, and a number applied computer science to other fields. Students learned that computer science is useful in all pursuits.

Bubbles activity
Practice with arrays, objects, Canvas, loops, and functions


Seahawks’ Keys to Success Work in Schools, Too.

The Super Bowl champion Seattle Seahawks are known for their confidence, speed, and defense. They are also known for running the most innovative coaching program in the NFL. How radical are their techniques? Not very, if you are an educator. Many of the strategies that Seahawks coaches use to get the best from their players are generally practiced by good teachers.

Treat each player as an individual

Head coach Pete Carroll: “I wanted to find out if we went to the NFL and really took care of guys, really cared about each and every individual, what would happen?” This detailed ESPN Magazine article describes the many different ways that the Seahawks take care of their players, including individual “status profiles” and counselors who check in with players after a bad practice. Individualization recognizes that each person’s circumstance and pattern of strengths and weaknesses are unique.

The best schools are built around teacher-student relationships. Students are known as individuals, with their unique personalities, interests, and learning dispositions. Students feel valued because teachers know them well and follow their development through years of study. The smaller the school, the most personal this relationship can become. Student support services, through advisors, teachers, counselors, and learning resource specialists, provide a nurturing, personalized support structure for each student.

Allow players to be themselves

A number of the Seahawks players have strong personalities. Some previously toiled within a poor team climate or openly clashed with past coaches. Those players have thrived in the Seahawks’ supportive system. When Marshawn Lynch refused to speak with reporters, and Richard Sherman delivered his famous rant on national television, the Seahawks did not penalize them (as far as we know) but rather seized on the learning moment for the players. The Seahawks organization also did not rush to the defense of those players but rather allowed them to feel the consequences of their actions from the NFL and public opinion.

At the best schools, students feel able to fully be themselves within school. They don’t have to check part of their personality at the door or conform to a school’s social norms. The best schools enforce enough rules to provide structure and also leave plenty of space to students to express themselves. Some students express learning challenges in ways that might be mistaken for obstinance, laziness, or defiance. Skilled teachers cut to the heart of the issue instead of heavily penalizing the overt behavior.

 

Have Fun

Coach Pete Carroll is well known for showing “boyish” enthusiasm on the sidelines and in practice. He has also encouraged playful contests during practices, pick-up basketball games for his players, and has a DJ play music during practices. He makes training fun, as many good teachers make learning fun, because happy people tend to perform better. Positivity is also part of the plan. Carroll and the rest of the coaching staff recognize positive play and encourage players to think optimistically about their potential and future performance. The Seahawks play from a position of confidence and strength, not fear of consequences.

The best classrooms are energizing places of enthusiasm. Teachers share their own passion for the subject and for their students. They understand that the social environment of school is absolutely vital for kids, and that a positive, inclusive social climate can enhance, rather than inhibit learning.

Experiment and iterate

The Seahawks organization has been labeled “new age” for their integration of yoga and meditation into the practice routine. However, the most significant aspect of this for me is the habit of experimentation and iteration. The Seahawks are eager to give new techniques a legitimate chance, including yoga, nutrition, social events, counselors, and more.

Pete Carroll has refined his approach through the years. Remember that he started as an assistant NFL coach and was fired twice from head coach positions (Patriots, Jets). Carroll continued to develop the model while at USC and took four years to fully refine and implement it with the Seahawks before winning the championship this year. Throughout, he undoubtedly made countless small adjustments to the approach and no doubt will continue to do so in the future.

The best schools are constantly making small adjustments to their program to sustain excellence during rapidly changing times. All members of the community contribute ideas for iterative program improvement. Innovative schools learn by doing, trying new ideas and seeing how they go.

Celebrate success

Carroll is known for leaping into the air on the sidelines, hugging his players, and even jumping into practice himself. These unabashed celebrations of success fill his players with the confidence that the head coach believes in them and recognizes their accomplishments.

The entire Seattle community, perhaps the entire northwest region, has joined in the celebration. Huge numbers of Seahawks fans attended the game. Crowd noise gave the Seahawks something of a home field advantage during the big game. An estimated 500,000 people will descend on the celebration parade downtown today.

Community celebration is self-reinforcing. Healthy schools recognize moments of success through community celebration.

David Malan on Teaching Computer Science

Three of us from U Prep attended a talk by David Malan, noted Harvard computer science instructor, at the UW school of Computer Science and Engineering. Malan walked the audience through noteworthy insights gained from teaching one of Harvard’s most popular courses, CS 50. The course has received national attention for making computer science accessible to both computer science majors and non-majors.

The national story on Malan has emphasized his personal magnetism and engaging presentation style, but Malan took his talk in a completely different direction. He presented a systems analysis of the course, students, and content, emphasizing the structural conditions that the teaching team has designed to support student success. Malan hardly mentioned his distinctive lecture style at all, instead noting that the team has reduced weekly lecture time in the course. Anyhow, only 70% of the students watch the lectures, increasingly on video as the term progresses. The core of the class, Malan states, is student work on authentic problems.

The keys to CS 50’s success, according to Malan, are the huge team of teaching fellows and alumni who provide small group and individual instruction, the focus on “memorable moments” during lectures, and the two capstone events that ground project development within a highly social, memorable context. The course provide 100 Teaching Fellows for a student enrollment of 700, and course alumni volunteer further support. Most students spent 10-20 hours per week working on the course, and a small number fall outside of that range, above or below.

Malan believes in mental reference models for concepts in computer science. At the start of the course, students build programs using Scratch (I thought that was for fourth graders!), providing a visual reference point for later programming in code. Lectures include kinesthetic demonstrations, during which students stand on stage and represent such concepts as bits in a byte or iterations of a binary search.

Later in the course, assigned problems become more challenging and complex, allowing students to engage with them at their level of mastery. Cryptography, digital forensics, spellcheck, breakout, a stock trading game, and a virtual drive through campus stretch students’ skills and knowledge. All this in a single semester course? No wonder students do so much work each week.

Malan underscored what we have also found the most interesting challenge in teaching computer science: how to engage and effectively teach students with novice, moderate, and significant experience in the field. Computer science is based on abstract principles of logical and sequential reasoning. These can pose a significant challenge to new students in the field, and yet tracking alone only serves to reinforce perceptions that only a small number of people can master computer science. We are working hard to develop the teaching techniques to make computer science accessible, relevant, and understandable to all, since computer science is now important and useful in all fields of study.

Dragon Box: Learn Algebra In a Visual Game

A few weeks ago, Wired published an article about a University of Washington professor’s experiment with algebra learning using an app called Dragon Box. Developed by a Norwegian company, the app comes in two versions, one for ages 5+ and the other for ages 12+. I bought both apps and invited our eight year-old to try them out.

Try them out he did! Perhaps not unusually for a boy his age, he completed the activities in the first app within three hours and moved on to the second app. After an additional three hours on Sunday, he announced that he had “finished” the ages 12+ app as well. Not so fast! Dragon Box invited him to “Side B,” which apparently provides about a hundred practice problems, still in the interactive environment, in traditional categories of pre-algebra and algebra problems. He still has plenty to do.

Indeed, the apps are very engaging. They provide a fun, exploration-based learning environment through which our son progressed when he correctly applied algebraic principles. Instruction was minimal. The app explained a few simple rules at the start of each set of challenges, using very simple, non-math language. Our son swiped and tapped his way through simplifying equations and solving for the unknown. Gradually, a few additional rules and more complex problems are presented until the player is multiplying by common denominators and solving complicated equations.

Ingeniously, the app starts with a sparkling box to represent an unknown variable, fantasy animals to represent numeric values, and a bar dividing right from left to represent equivalency. As one completes levels, eventually the box becomes x, the animals become numbers, the bar becomes an equal sign, and additional operands appear. The solution methods stay the same. The game is entirely faithful to the mathematical principles. Knowledge and skills learned transfer into solutions for algebraic equations.

Additional information:

We Want To Know (the Norwegian company)

Dragon Box (the apps, $6 and $10 for iOS, other mobile and desktop versions available)

Center for Game Science (University of Washington)

Kids Like to Learn Algebra, if It Comes in the Right App” (Wired)

DragonBox: Algebra Beats Angry Birds (Wired, detailed app info)