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Doctorate formal-final
 

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    Doctorate formal-final Doctorate formal-final Presentation Transcript

    • The Architecture of Innovation System for the Commercialization of Science - The Effect of Information Processing Model for the Decisions of Financial Resource Allocation- Kanetaka Maki Doctoral Course Student, Graduate School of Media and Governance, Keio University
    • Contents
      • My Current Status at Doctoral Course
      • My Research Questions
      • Survey of Previous Studies
      • Current Research Outputs
      • Future Research Plans
      • Additional Information
    • Contents
      • My Current Status at Doctoral Course
      • My Research Questions
      • Survey of Previous Studies
      • Current Research Outputs
      • Future Research Plans
      • Additional Information
    • My Current Status (1)
      • Name (ID):
        • Kanetaka Maki (80549208)
      • Program:
        • Policy Making and Social Innovation (PS)
      • Main Research Advisor:
        • Prof. Jiro Kokuryo (Faculty of Policy Management)
      • Co-Research Advisor:
        • Prof. Jun Murai (Faculty of Environment and Information Studies), Prof. Kiyonori Sakakibara (Faculty of Policy Management) , Prof. Satoshi Kabasawa (Graduate School of Media and Governance)
      • Research Theme:
        • The Architecture of Innovation System for the Commercialization of Science -Effect of Information Processing Model for the Decisions of Financial Resource Allocation-
      • Summary (100 words):
        • The commercialization of science research often fails due to the lack of an appropriate architecture to bridge the financial gap between science research and commercialization. The lack has created by the three trends; a dead lock of a vertically integrated innovation model, a bigger demand for science related research, and risk analysis based on financial engineering. One of the primary reasons of these failures is that most of the outputs of science research are in too-early stage for industry to get interests in their value. In this research, with taking the research theories based on previous studies, I will show an empirical study by classification of innovation systems to bridge the financial gap for the commercialization of science research, and conduct new innovation process model.
    • My Current Status (2)
      • Past
        • 2002-2008: Chief officer of SIV Entrepreneur Lab
          • Designing, implementing, and executing the innovation system at SFC.
        • 2005- current: Doctoral course student
          • research based on my practical activities & network theory: “The Role of Alumni Network for University-Based Innovation Platform”.
        • 2008 (Summer): Changed research topic
          • Separation from my practical activities.
          • “ Commercialization of Science for University-based incubation”
      • Future
        • 2010 (Spring): Aim to become doctoral candidate
        • 2010 (Summer): Aim to continue my research in the US university
    • Contents
      • My Current Status at Doctoral Course
      • My Research Questions
      • Survey of Previous Studies
      • Current Research Outputs
      • Future Research Plans
      • Additional Information
    • Changes in Innovation Systems From Vertical Integration to Horizontal Integration
      • The role of central research institute, as an engine of innovation, (vertical integration model) in large enterprise is terminated. (Rosenberg[1996])
      • Open Innovation (horizontal integration model) became main stream. (Chesbrough [2003])
      • University and research institute became the engine of innovation. [Triple Helix Model] ( Etzkowitz[2008] )
      • Academic startups (Shane[2002])
      • VC is the main source of financial support (Bygrave &Timmons[1996])
      These theories explain Silicon Valley’s Innovation System. The model fits to IT sector.
    • Performance of Biotechnology Sector
      • Many biotechnology academic startup have been launched based on Silicon Valley’s Innovation Model.
      • Many startups face financial chasm to continue their research.
      • Silicon Valley’ Innovation Model is NOT effectively working! Why?
      • Does Silicon Valley’s Innovation Model does works other sectors than IT, especially in science-related sectors ?
    • Chronicle of Organizational Innovation by Pisano Researcher Technological Innovation Organizational / Institutional Innovation Chandler Rail and telegraph systems Modern Corporation (separated ownership from management) Rosenberg, Chesbrough etc. Semiconductors, software, computers, and communications = IT Open Innovation Startups + VC (Silicon Valley’s Innovation Model) Pisano etc. Science-related Industry (ex. Biotechnology, Energy etc.) ???
    • Goal / RQs
      • Research Goal
        • Design the appropriate architecture of innovation system for the commercialization of science.
      • Research Questions
        • What are the emerging innovation systems and their structures?
        • What is the effect of information processing model and incentive structure for the decisions of the financial resource allocation?
    • Contents
      • My Current Status at Doctoral Course
      • My Research Questions
      • Survey of Previous Studies
      • Current Research Outputs
      • Future Research Plans
      • Additional Information
    • Current understandings(1) Linear Model of Innovation Basic Research Applied Research Development Commercialization University Industrial firm Start-ups + VC Original source of this linear model is unknown. Most researchers use modified model without mentioning the source. However, V. Bush’s “Science: The Endless Frontier” (1945) first describes the steps innovation. Chasm (Financial Gap)
    • Current understandings(2) Chain Linked Innovation Model f: Feedback I: New equipment stimulates science, and science generates new equipment C: Idea germination S: Company's support for long-term research Source: Created by the Center for Research and Development Strategy based on the chain-link model of Stephen J. Kline
    • Current understandings(3) Innovation Process and Research Investment People’s interesting Research investment 0 10 20 30 Dream Nightmare Real Dream Era Nightmare Era Commercialization (year) Cited from “Type2 Basic Research”,Yoshikawa face a storm of criticism
    • Current understandings(4) Specific Characteristics of Science Industry by Pisano
      • High risk of uncertainty
      • Long term of research (10-30 years)
      • Difficulty in creating the market of know-how (= difficulty of M&A)
        • Difficulty of integration
        • The degree of information asymmetry
        • The need for investments in specialized assets
        • The tacitness of the know-how
        • The degree to which the relevant intellectual property can be protected legally
      VCs need risk distribution and expect shorter time of return. Silicon Valley’s Innovation Model does not work. Financial chasm exists in innovation process of science industry.
    • Contents
      • My Current Status at Doctoral Course
      • My Research Questions
      • Survey of Previous Studies
      • Current Research Outputs
      • Future Research Plans
      • Additional Information
    • Research Design (1)
      • Defined sixteen innovation models for the commercialization of science
        • Defined based on literature review of architecture and innovation theories
        • Interviews for innovation researchers in global conferences to find emerging models
      • Collected information by secondary source for sixteen models
        • webpage, books, reports etc
      • Conducted pre-interviews for seven organizations
        • National Science Foundation, CALIT2, CITRIS. Venture Philanthropy, True Bridge, Industry Innovation Network Corp, IPS Academia Japan Inc.
    • Research Design (2)
      • Analyzed sixteen models
        • Explanatory variables: based on previous studies of innovation and architecture theories to explain incentive structure (six variables)
        • Dependent variables: based on Pisano’s framework (Difficulty in the commercialization of science) (three variables)
      • Conducted empirical new innovation model. (hypothesis)
    • Types of Innovation Systems (Classic) Type Model of innovation system Case Architecture Solution for Difficulties of Characteristic of Science History Model Sponsor Incentive Term Covering Phase High Risk Longer Term Market of Know How Type 1 Debt finance for enterprises Tesla Electric Light Company classic vertical bank interest 10 years all P G F Type 2 Central research institute operated by large enterprises Bell Lab. classic vertical capita stock + profits profit 10 years basic research, applied research P G F Type 3 Government-based grants for research institutes National Science Foundation classic horizontal tax income research outcome & economy prospriety 5years basic research,applied research P P P Type 4 National research project with initiative of the government Japan National Projects such as main-frame computer development classic horizontal tax income economy prospriety & profit 10years basic research,applied research P G F Type 5 Sogo-Shosha MITSUBISHI Corp, MITSUI Corp classic vertical / horizontal profits profit 5years applied research P P F Type 6 Start-up and venture capitalists Silicon Valley Venture Capitals classic horizontal equity capital gain 7 years applied research G F P Type 7 Angel investment Viinod Khosla, Guy Kawasaki classic horizontal equity capital gain, excitement 7 years applied research G F P Type 8 Collaborative grants of government and industry National Science Foundation classic horizontal tax income & profits economy prospriety & profit 5 years translational research, applied research F P F                        
    • Types of Innovation Systems (Emerging) Type Model of innovation system Case Architecture Solution for Difficulties of Characteristic of Science History Model Sponsor Incentive Term Covering Phase High Risk Longer Term Market of Know How Type 9 Translational research mechanism in government-based research institute RIKEN (a large natural sciences research institute in Japan), CALIT2 emerging horizontal tax income & profits deployment of research & profit 7 years translational research G F G Type 10 License free & donation CITRIS at UC Berkeley emerging horizontal tax & profits economy prospriety & profit 7 years translational research, applied research G F G Type 11 Equity based intellectual management structured for private benefits Intellectual Ventures emerging horizontal capital stock profit 10 years translational research, applied research G G F Type 12 Venture philanthropy Bill Gates Foundation emerging horizontal individual profits philanthoropy & capital gain 20 years translational research, applied research G G F Type 13 Alumni based fund Georgia Tech Alumni Fund emerging horizontal equity compassion & profit 15 years translational research, applied research G G F Type 14 Venture capital fund with platform of track-recorded managers True Bridge emerging horizontal equity capital gain 15 years translational research, applied research G G F Type 15 Government-based Fund Indusry Innovation Network Corp. emergiing horizontal equity ecnomic prospriety & capital gain 15 years translational research, applied research G G F Type 16 Equity based intellectual management structured for public benefits IPS Academia Japan, Inc. emerging horizontal equity deployment of research & profit 15 years translational research G G G
    • Metrics Solution for Difficulties of Characteristic of Science High Risk Longer Term Market of Know How Metric Mechanism of risk distribution and return Expected term for retrun Existance of platform to collaborate players for different functions Good Organized more than 10 years Organized Fair Partially organized 5-10 years Partially organized Poor Not Organized less than 5 years Not Organized
    • New Findings (1)
      • Emerging innovation models focus on
        • Deepening new science findings
        • Transforming from “Dreams / illusions of scientists” (high uncertainty) to applied research fields (lower uncertainty)
        • Providing longer term finance
        • Providing networks to related industry to share tacitness
        • Educating researchers for emerging research field
      • Methods
        • Creating translational research organization / system
        • Fundraise research from local government grants or equity-based finance.
      • Emerging models try to solve the difficulties of commercialization of science that Pisano declared.
    • New Findings (2)
      • Incentives to invest translational research
        • Type A: Cluster model
          • Translational research is essential phase to create new cluster for regional government and large enterprises in the region. They aim to attract talented human resource and create startups. (Competition of regional innovation clusters)
        • Type B: Equity-based model
          • Equity-based investment with IP protection; high risk and high return business model.
        • Type C: Venture philanthropy
          • Contribution to the society by solving social issues with financial return.
    • Traditional Linear Model of Innovation Basic Research Applied Research Development Commercialization University Industrial firm Start-ups + VC Original source of this linear model is unknown. Most researchers use modified model without mentioning the source. However, V. Bush’s “Science: The Endless Frontier” (1945) first describes the steps innovation. Chasm (Financial Gap)
    • Hypothesis Translational Research Based Innovation Process Model Commercialization Intensive Speed Global Development Intensive Speed Global Applied Research $ Medium - $ Large IP Local Translational Research $ Medium - $ Large IP / Commons Local Attract human resource from global Basic Research $Small IP / Commons National University / Research Institute Chasm (Financial Gap) Industrial firm
      • The roles of university and industrial firm may change in each industry.
      • The size and place may change in each industry.
    • Definitions
      • Basic research
        • Finding new theorems in complex phenomenon
      • Applied research
        • Finding new solutions for social needs by using theorems
      • Translational research
        • Based on basic research outputs, find new applied research fields to reduce uncertainty (The term is originally from medical research)
    • Contents
      • My Current Status at Doctoral Course
      • My Research Questions
      • Survey of Previous Studies
      • Current Research Outputs
      • Future Research Plans
      • Additional Information
    • Case Study Analysis
      • Cases
        • two samples each from three types of incentives
      • Explanatory variables
        • flow of information, quantity of information, necessity of specialized knowledge, frequency of communication
        • average size of investment, average length of project, incentives to invest
      • Dependent variables
        • amount of budgets for researchers
        • risk distribution parameter, expected term of return, communication frequency with understanding of tacitness
    • Expected Achievements
      • Academic perspective
        • Explain why current Silicon Valley’s Innovation Model, which is combination of previous studies, does not work, by defining new innovation process model using the concept of “translational research”
        • Clarify the information processing model and incentive structure of “translational research” to fill the financial gap.
      • Practical perspective
        • Researchers can find new way to fundraise and deploy their research outputs.
        • Investors can find new business chance.
        • Large enterprise can find new business chance with lower risk.
        • Supports policy makers to accelerate the innovation.
    • Milestones
      • Literature review (innovation, architecture, network, platform) (done)
      • Conduct research questions (done)
      • Research by secondary source (done)
      • Creating relationships with entities of case analysis (done)
      • Pre-interview (done)
      • Conduct hypothesis (done)
      • Deep Interviews for case study
      • Quantitative analysis for researchers (tentative)
      • Case study analysis and evaluate hypothesis
      • Publish one more research paper for English journal
      • Conduct dissertation
    • Contents
      • My Current Status at Doctoral Course
      • My Research Questions
      • Survey of Previous Studies
      • Current Research Outputs
      • Future Research Plans
      • Additional Information
    • Literature Review (1)
      • [English]
      • Baldwin, Carliss Y. and Kim B. Clark “Design Rules, Volume 1.: The Power of Modularity”, The MIT Press, 2000.
      • Bijker, Wiebe E., Hughes Thomas P. and Trevor J. Pinch (ed.) “The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology”, The MIT Press, 1987.
      • Bygrave, William D. and Jeffry A. Timmons “Venture Capital at the Crossroads”, Harvard Business School Press, 1992.
      • Chandler, Alfred D. Jr. “The Visible Hand: The Managerial Revolution in American Business”, The Belknap Press of Harvard University Press, 1977.
      • Chesbrough, Henry Willam “Open Innovation: The New Imperative for Creating and Profiting from Technology”, Harvard Business School Press, 2003.
      • Chesbrough, Henry William, Wim Vanhaverbeke and Joel West (ed.) “Open Innovation: Researching a New Paradigm”, Oxford University Press, 2008.
      • Christensen, Clayton M. “The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail”, Harvard Business School Press, 1997.
      • Cohen, WM and DA Levinthal “Absorptive-Capacity – A New Perspective on Learning and Innovation”, Administrative Science Quarterly Volume: 35 Issue:1, 1990, pp128-152
      • Etzkowitz, Henry “The Triple Helix –University-Industry-Government Innovation in Action”, Routeledge, 2008.
      • Fleming, Lee and Olav Sorenson “Science as A Map in Technological Search”, Strategic Management Journal 25, 2004, pp909-928
      • Hardin, Garrett “The tragedy of the Commons, Science”, New Series Vol. 162 No. 3859, 1968, pp. 1243-1248.
    • Literature Review (2)
      • Kao, John “Innovation Nation”, Free Press, 2007.
      • Lessig, Lawrence “CODE and other laws of cyberspace”, Basic Books, 1999.
      • Lessig, Lawrence “The future of ideas: the fate of the commons in a connected world”, Random House, 2001
      • Lessig, Lawrence “Free Culture: How Big Media Uses Technology and the Law to Lock Down Culture and Control Creativity”, Penguin, 2004.
      • Moore, Geoffrey “Crossing the Chasm: Marketing and Selling High-tech Products to Mainstream Customers”, Harper Business Essentials, 1998.
      • Nelson, Richard R. “National Innovation Systems: A Comparative Analysis”, Oxford University Press, 1993.
      • Nonaka, I. “The Dynamic Theory of Organizational Knowledge Creation”, Organization Science Volume 5 Issue:1, Feb 1994, pp14-37.
      • Nonaka, Ikujiro “The Knowledge-Creating Company”, Harvard Business School Press, 2008.
      • Pisano, Gary P. “Science Business”, Harvard Business School Press, 2006.
      • Rogers, Everett M. “Diffusion of Innovations: Fifth Edition”, The Free Press, 2003.
      • Rosenberg, S. Richard and W. J. Spencer “Engines of Innovation: U.S. Industrial Research at the End of an Era”, Harvard Business School Press, 1996.
    • Literature Review (3)
      • Saxenian, A.L. “Regional advantage: culture and competition in Silicon Valley and Route 128”, Harvard University Press, 1994.
      • Schumpeter, Joseph A. “The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle”, Harvard University Press, 1934.
      • Shane, S and S. Venkataraman “The promise of entrepreneurship as a field research”, Academy of Management Review Volume: 25 Issue:1, Jan 2000, pp217-226
      • Shane, S. Andrew “Academic Entrepreneurship: University Spinoffs and Wealth Creation”, Edward Elgar Pub, 2004.
      • Simon, Herbert A. "The Sciences of the Artificial 3rd ed.”, MIT Press, 1996.
      • Teece, DJ “Profiting from Technological Innovation – Implications for Integration, Collaboration, Licensing and Public-Policy”, Research Policy Volume 15 Issue:6, Dec 1986, pp285-305
      • Teece, DJ, G. Pisano and A. Shuen “Dynamic capabilities and strategic management”, Strategic Management Journal Volume: 18 Issue: 7, Aug. 1997, pp 509-533
      • Timmons, A. Jeffry, and Stephen Spinelli, “New Venture Creation for the 21st Century”, McGraw Hill Higher Education, 2008.
      • Yin, Robert K. “Case Study Research: Design and Methods, Third Edition”, Sage, 2002.
      • [Japanese]
      • Kokuryo, Jiro “Open innovation & University’s business incubation ,” PowerPoint Presentation to Kauffman Fellows Program Japan Summit, Oct. 2nd, 2009. EGG Japan, Tokyo, Japan.
      • Yoshikawa, Hiroyuki http://www.jstage.jst.go.jp/article/syntheng/1/1/1/_pdf, accessed Oct., 2009.
    • Journals / Presentations
      • Global Conferences
        • Kanetaka Maki et al. , “The Architecture of Innovation System for the Commercialization of Science”, ISPIM Conference 2010 (in reviewing process)
        • Kanetaka Maki et al. , “Designing the Incentive Structure for the Commercialization of Science - How to Bridge the Financial Gap between Science and Commercialization-“, IAMOT 2010, March 2010 (accepted)
        • Kanetaka Maki et al. , “Optimization of Financial Incentive Structure for the Commercialization of Science”, The 2nd ISPIM Innovation Symposium, December 2009
        • Kanetaka Maki, “The Design and Implementation of Know How Licensing Scheme for Venture Incubation”, 2006 AUTM Annual Meeting, March 2006, Orlando, USA
      • Global Journals
        • Kanetaka Maki et al., “The Architecture of Innovation System for the Commercialization of Science”, Technovation (in writing process)
    • Journals / Presentations
      • Domestic Conferences
        • 牧兼充、「大学発ベンチャー育成のためのエコシステムの創成と評価」、 ビジネスモデル学会秋季大会 2008 年、 2008 年 10 月
        • 牧兼充、「アントレプレナー育成を基盤とした大学発ベンチャー育成プラットフォームに関する研究」、ベンチャー学会第 9 回全国大会、 2006 年 11 月
        • 牧兼充、「ベンチャーインキュベーションにおける知的財産のパブリックドメインとプライベートドメインに関する考察」、第4回日本知財学会学術研究発表会、 2006 年 6 月
        • 牧兼充、「インキュベーション・プラットフォームのデザインにおけるアーキテクチャに関する考察」、産学連携学会第4回大会、 2006 年 6 月
        • 牧兼充、「ビジネスプランコンテストをプラットフォームとしたインキュベーション手法に関する考察」、ベンチャー学会第 8 回全国大会、 2005 年 10 月
        • 牧兼充、「学習支援のためのネットワークコラボレーションモデルに関する考察 ~慶應義塾湘南藤沢中等部・高等部における ThinkQuest の実践~」、教育システム情報学会第 24 回全国大会予稿集、 1999 年 8 月
        • 牧兼充、石橋啓一郎、「ユーザの視点に基づいたネットワークの性能評価に関する考察」、情報処理学会・分散システム運用技術研究会 98 年度第 3 回定例研究会予稿集、 1998 年 9 月
      • Domestic Journals
        • 牧兼充他、「地域イノベーションにおけるネットワークの閉鎖性・構造的空隙を創出するビジネス・インキュベーション・プラットフォームの設計に関する研究」、情報社会学会 ( 執筆中 )
        • 牧兼充他、「大学発ベンチャー育成のためのメンター・プラットフォームにおける同窓会ネットワーク活用に関する研究」、映像情報メディア学会誌 ( 査読中 )
        • 牧兼充他、「大学発ベンチャー企業の分類軸の確立をベースとした支援ネットワークのデザインの手法に関する研究」、ベンチャー学会「ベンチャーズレビュー」 No.12 、 2008 年 3 月発行
        • 牧兼充、「インキュベーション・プラットフォームにおけるグローバル型とローカル型のネットワークに関する考察―慶應義塾大学 SIV アントレプレナー・ラボラトリーの活動を事例に―」、ベンチャー学会「ベンチャーズレビュー」 No.9 、 2006 年 9 月発行
        • 牧兼充、「ビジネスプランコンテストをプラットフォームとしたインキュベーション手法に関する考察― SIV アントレプレナー・ラボラトリーにおけるコンテスト運営に基づいて―」、ベンチャー学会、「ベンチャーズレビュー」 No.8 、 2006 年 3 月発行
        • 牧兼充、「ベンチャー経営におけるネットワークを活用した遠隔取締役会に関する研究」、 GLOCOM REVIEW September 2003 、 2003 年 9 月
        • 牧兼充、新井正樹、近藤大和、鈴木二正、山根健、「 ThinkQuest’98 参加者へのチュートリアルの実践」、教育システム情報学会 Vol.15 No.4 ( 特集号 ) 、 1999 年 1 月
    • Additional Slides
    • Definitions
      • Science:
        • 1) Knowledge attained through study or practice
        • 2) Knowledge covering general truths of the operation of general laws, esp. as obtained and tested through scientific method and concerned with the physical world.
        • (Webster's New Collegiate Dictionary)
      • Architecture:
        • Combined factual constraints of physics, nature and technology that define the borders of human behavior in a specific situation or place. (Lessig)
      • Information Processing Model:
        • the sciences concerned with gathering, manipulating, storing, retrieving, and classifying recorded information (Farlex dictionary)
      • Incentive
        • Serving to induce or motivate (Farlex dictionary)
    • Translational Research by NIH
      • To improve human health, scientific discoveries must be translated into practical applications. Such discoveries typically begin at “the bench” with basic research ― in which scientists study disease at a molecular or cellular level ― then progress to the clinical level, or the patient's “bedside.” Scientists are increasingly aware that this bench-to-bedside approach to translational research is really a two-way street. Basic scientists provide clinicians with new tools for use in patients and for assessment of their impact, and clinical researchers make novel observations about the nature and progression of disease that often stimulate basic investigations. Translational research has proven to be a powerful process that drives the clinical research engine. However, a stronger research infrastructure could strengthen and accelerate this critical part of the clinical research enterprise. The NIH Roadmap attempts to catalyze translational research in various ways.
      • cited from: http://nihroadmap.nih.gov/clinicalresearch/overview-translational.asp
    • Current Phenomena (Pain)
      • Decrease of government based grants
        • Linkage between science research and social benefits is becoming unclear for the taxpayers. (so called “SHIWAKE”)
        • Need for military affair expense is decreasing.
      • Decrease of industry based research budgets
        • Linkage between science research and commercialization is becoming unclear
      • Decrease of equity-based finance for the academic start-ups.
        • Overachievement and destruction of financial engineering industry.
      • Who is responsible for financing the science research?
      • University, the engine of innovation, is in crisis for research budgets.
    • The Financial Engineering
      • Overachievement of financial engineering.
        • Information Asymmetry between financial engineering industry and VCs occurred.
          • VCs lost negotiation power to their LPs.
        • Majority of 2003 and 2004 vintages of VC funds are still seeking for startups to invest. (Kaplan)
          • VCs are looking for short term return. (ex. Short term business or emerging market in Asia)
        • VC model has been invented and developed for the innovation of information technology.
    • Expansion of R esearch Field in Innovation
      • 20 th century: semi-conductor  PC  Internet  dot com
      • 21 st century: science-related research
      Make solar energy economical Provide energy from fusion Develop carbon sequestration methods Manage the nitrogen cycle Provide access to clean water Restore and improve urban infrastructure Advance health informatics Engineer better medicines Reverse-engineer the brain Prevent nuclear terror Secure cyberspace Enhance virtual reality Advance personalized learning Engineer the tools of scientific discovery Breadcrumb trail National Academy of Engineering of the National Academies