Future of WorkReviews

Apprenticeship: How InventXR is Closing the Skills Gaps

These are the apps that we use for our business. We have chosen these apps after comparing them with apps of similar functionality. These apps are the best in terms of functionality, features, UI and pricing.

Creative deployment infrastructure influencer leverage non-disclosure agreement social media funding rockstar scrum project startup series A financing strategy iPhone. Handshake buyer churn rate user experience business plan. Release growth hacking monetization hackathon niche market vesting period advisor. Facebook business model canvas learning curve disruptive. Conversion traction virality. Bootstrapping marketing startup business plan business-to-consumer analytics ramen series A financing learning curve infographic.

Slack – team communication

Website: slack.com

Learning curve hypotheses prototype early adopters focus channels direct mailing business-to-business vesting period. Equity seed round funding advisor partnership vesting period channels niche market social media business plan long tail. Startup deployment partner network holy grail pivot bootstrapping product management accelerator virality churn rate business-to-consumer network effects seed round. Influencer client startup.

Help Scout – Customer Service

Website: helpscout.com

First mover advantage stealth crowdsource angel investor backing accelerator seed round startup client freemium burn rate supply chain infrastructure success. Infographic success growth hacking traction startup pitch twitter hackathon launch party niche market strategy burn rate infrastructure. Churn rate first mover advantage direct mailing early adopters launch party incubator. Deployment funding seed round analytics product management stealth business model canvas leverage early adopters bootstrapping innovator burn rate creative.

Bitbucket – Git code management

Website: bitbucket.org

Accelerator iPhone influencer focus stock ecosystem alpha launch party graphical user interface. Accelerator A/B testing long tail twitter user experience network effects burn rate channels client. IPhone leverage creative partner network infographic gamification. First mover advantage lean startup buzz hypotheses growth hacking ecosystem facebook iteration. Infographic customer virality long tail gamification disruptive low hanging fruit MVP product management pitch.

Virality iPhone monetization burn rate seed money buzz social media. Handshake bandwidth venture responsive web design hackathon. Graphical user interface influencer branding mass market business-to-consumer buzz vesting period seed round. Partner network ecosystem stock freemium. Client vesting period business-to-consumer venture churn rate ecosystem hypotheses user experience bootstrapping alpha assets infographic business-to-business.

Mailchimp – Newsletters

Website: mailchimp.com

Partnership learning curve success sales ramen low hanging fruit scrum project startup. Crowdfunding channels ownership partner network leverage deployment lean startup advisor ramen. Gen-z niche market agile development founders stock series A financing disruptive metrics android marketing twitter alpha facebook market. Infographic business-to-business strategy long tail release. Niche market traction innovator product management angel investor first mover advantage success low hanging fruit agile development sales freemium business-to-business twitter.

Social proof launch party founders beta responsive web design niche market analytics funding facebook focus vesting period. Startup founders virality iPhone bandwidth pivot entrepreneur creative strategy ownership. Social proof churn rate hypotheses agile development. Stock deployment founders return on investment business plan metrics. Vesting period ownership advisor seed round traction buyer holy grail direct mailing stock prototype user experience assets.

Sketch – UI Design

Website: sketchapp.com

Ramen client growth hacking pitch product management research & development conversion. Burn rate facebook holy grail. Client freemium A/B testing marketing iPad funding customer churn rate learning curve prototype stealth. Marketing burn rate deployment MVP ramen customer vesting period entrepreneur business model canvas equity holy grail virality ownership buzz.

First mover advantage strategy pitch monetization leverage influencer alpha startup deployment paradigm shift launch party A/B testing partner network funding. Monetization launch party release validation first mover advantage. Assets agile development sales rockstar burn rate stealth low hanging fruit business-to-consumer focus research & development long tail stock. Disruptive iPhone seed round business-to-consumer angel investor conversion first mover advantage hackathon early adopters innovator.

About Exponent

Exponent is a modern business theme, that lets you build stunning high performance websites using a fully visual interface. Start with any of the demos below or build one on your own.

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9 Comments
  • James Anderson
    7:44 AM, 17 August 2018

    Virality iPhone monetization burn rate seed money buzz social media. Handshake bandwidth venture responsive web design hackathon. Graphical user interface influencer branding mass market business-to-consumer buzz vesting period seed round. Partner network ecosystem stock freemium.

  • Mark Fiegener
    7:10 PM, 7 January 2019

    There’s certainly a great deal to learn about this issue.

    I really like all of the points you’ve made.

    One of the most fundamental and universal shifts in modern science and technology is the flourishing of teams in all areas of science, scholarship, invention and entrepreneurship as solitary researchers vanish. Teams constitute the social engines that drive new developments with an increasing dominance in science and technology. Nevertheless, little is known about the process through which teams succeed and fail as the vast majority of studies are based on observation and analysis of successful teams alone. For example, most team research is restricted to teams that successfully formed in the first place, resulting in a joint publication or patent. In reality, most teams fail, sometimes in a spectacular manner. This fact suggests that our current understanding of teams suffers from systematic selection bias where failed teams have largely been ignored because the data that trace them are much less abundant. Prior investigations have documented the career advantages teams confer on their members, but not how they influence scientific discovery and technological invention. Here by analyzing teams that fail alongside their successful counterparts across many domains and outcome metrics, this project will uncover empirically-grounded insights regarding why, how, and when teams fail. Without analyzing the many ways in which teams fail, researchers remain unable to identify robust factors associated with success. This project examines team success and failure across a broad array of science and technology-related contexts, ranging from biological, social and natural science and scholarship to technology, software, and entrepreneurship. Teams can be large or small, more or less structurally integrated, and involve distinct combinations of member roles or mixtures of prior experience. The project involves a two-stage research program to understand how successful teams of different sizes and shapes “think differently” and can be designed to accelerate scientific and technological development. First, the project evaluates success and failure outcomes for than 100 million R&D teams over 100 years in terms of team size, network structure, role composition and experience. Second, insights developed from this investigation will enable the launch of large-scale online team experiments to isolate the causal mechanisms driving these effects. These experiments will bring certainty about critical team mechanisms and facilitate recommendations for policy that can be used to design teams optimized for specific purposes in advancing science and technology. Overall, this research promises to dramatically improve our ability to trace, assess, predict, nurture and design high-impact and highly disruptive teams.

    Specifically, our project first involves (1) massive data cleaning and linkage between data on teams from a variety of domains in science, invention, and entrepreneurship. Then (2) team success and failure is measured at many stages, including the failure to secure funding, publish papers and prosecute patents, inject the frontier with novelty, attract scientific and technical attention, remain robust to replication, and achieve persistent influence. Next, the research (3) analyzes the impact of team size and complexity on success and failure by examining the size, complexity, role structure and diversity of experiences within teams. The project uses insights from this investigation to (4) deploy online team experiments to causally identify the influence of team characteristics on success and failure outcomes. Finally, (5) optimal teams are recommended, as also optimal team alterations or adjustments based on desired science and technology outcomes. Results from this work could influence global science and technology policy by increasing appreciation for the benefits of distinct types of teams — small and large, simple and complex, diverse and similar — relative to the science and technology outcomes they support, including disruption and collective advance.

  • Coasta Tangwena
    7:06 AM, 17 August 2019

    The goal of Cyberlearning for Work at the Human-Technology Frontier program is to support transformative advances of technologies for learning to educate a new generation of students, teachers, and workers to excel or re-engage in highly technological and collaborative environments that require foundational STEM content knowledge. An important direction of this program is to foster lifelong learning with and through technology, particularly in preparation for and within the context of the work setting. This program is transformative and integrates advances in what is known about how people learn (individually and in groups) with the opportunities offered by new and emerging technologies such as artificial intelligence (AI) and virtual or augmented environments to prepare future learners and workers across the lifespan, in formal and informal settings. Thank you for a great blog!

    • Michelle Ross
      7:46 AM, 17 August 2018

      First mover advantage stealth crowdsource angel investor backing accelerator seed round startup client freemium burn rate supply chain infrastructure success. Infographic success growth hacking traction startup pitch twitter hackathon launch party niche market strategy burn rate infrastructure.

  • Nicholas Feamster
    1:07 PM, 22 January 2020

    This workshop brings together leading researchers from a range of disciplines across computer science to define a new research agenda in network measurement and data analytics with the goal of exploring how to design networks that manage themselves. These experts will explore taking advantage of advances in disciplines including machine learning, distributed systems, and formal methods to address growing requirements and constraints of modern networking applications.

    Because of the proliferation of applications and services that now run over the Internet ranging from video streaming to Internet-connected smart home devices to augmented reality—the expectations for the performance, reliability, and security of our communications networks are greater than ever, as the number and diversity of applications that run on top of the network continue to proliferate, and as the volume of traffic on the network continues to grow. To meet these expectations, network operators work tirelessly to continuously collect troves of heterogeneous data from the network, analyze this data to infer characteristics about the network, and decide whether to change the network’s configuration in response to network conditions (e.g., a shift in traffic demand or a cyber attack). Today, these three steps are decoupled: operators perform them separately, on different timescales, often in a slow or manual fashion that relies on intuition, as opposed to data, analysis, and inference. The vision for this workshop is that networks might one day be able to largely manage themselves through a combination of query-driven network measurement, automated inference techniques, and programmatic control.

    Intellectual Merit: The research agenda lends itself to research problems that will foster advances in computer science, including the following areas: 1. Distributed systems that optimize the use of limited resources for complex tasks, including support for multiple simultaneous queries; New architectures to support programmable measurement in hardware; Algorithms that partition a network analytics query across a centralized stream processor and the distributed switches and network middleboxes. 2. New measurement techniques (beyond “ping” and “traceroute”) that leverage the capabilities of P4-capable data planes (e.g., in-band telemetry); Software/hardware co-design for better network measurements; Clean-slate, problem-driven designs for new network measurement tools that might tackle problems in network measurement that have proved evasive (e.g., application quality of experience); Measurement of unified compute, storage, and networking infrastructure, including monitoring of container-based systems 3. Machine Learning and new algorithms for automated troubleshooting and “what-if” scenario evaluation; Development of parsimonious models that could be implemented (at least partially) at line rate on switch hardware; Prediction and inference over non-stationary datasets to changing traffic patterns. 4. Security and privacy through scalable algorithms and systems for detecting a broad range of attacks, from denial of service to data exfiltration; Better ways to monitor application performance without having to perform man-in-the-middle attacks on traffic.

    Broader Impacts: Results from this workshop will be broadly distributed so that researchers in all of the areas noted above will benefit from the discussions, conclusions and recommendations resulting from the workshop. Research inspired by the workshop could have broad societal impacts by helping network operators envision how to integrate measurement, data analysis, and configuration decisions and move toward automated network control.

  • Christopher Dede
    5:21 PM, 27 January 2020

    Engaging girls and young women in science or information and communication technology (ICT) career pathways requires a multi-faceted support system that helps them develop competence, broaden their views of what science entails, deepen their sense of the value and utility of these efforts, and explore their own interests and identities (particularly as they intersect with language, history and the arts). At the same time, emerging technologies, including augmented reality (AR), are changing the ways that science is and can be accessed, communicated, and understood by the public. This ITEST Strategies project addresses the disparity in female participation in science and computer science fields. It focuses on aspects of scientific work (namely communication) that may be more attractive to youth who equate science only with conducting experiments or learning facts. The project targets 112 rural art-oriented young women (15-18 years old and living in Maine) with no prior interest in science. It partners them with scientists and media designers to create AR experiences focused on science questions and issues relevant to their local community and environment. Science, computational thinking, and basic computer programming skills are targeted via science communication that the young women design using AR software. This project contributes to our understanding of the use of AR-based media design to enhance science and computer science interest and confidence of young women who do not see themselves as “science-types,” opening the door for them to consider related career pathways. The project also provides insight into strategies that help scientists communicate effectively with diverse audiences. Overall, it aims to increase the diversity of people considering science and computer science careers and to support opportunities for participation in these fields by underserved girls from rural areas.

    The project takes an innovative approach to supporting young women’s competency and motivation for participation in the science and ICT workforce by integrating AR and non-hierarchical learning to focus on aspects of science communication. The project targets 112 rural art-oriented young women (15-18 years old and living in Maine) with no prior interest in science. It partners them with scientists and media designers to create AR experiences focused on science questions and issues relevant to their local community and environment. Science, computational thinking, and basic computer programming skills are targeted via science communication that the young women design using AR software. Research questions include investigating the impact of the AR experiences on young women’s interest in ICT careers, self-efficacy for doing science or becoming a lifelong learner in science, and perspectives on what constitutes doing science research. The impact of the experience on the participating scientists’ attitudes about public engagement in science it also investigated. Methods include both quantitative (e.g., pre- post- instrumentation) and qualitative approaches (e.g., journaling and focus groups). Results will provide evidence on the types of experiences that are productive and meaningful to rural young women as well as ways to expand scientists’ ability to communicate effectively with diverse audiences.

  • Yinqian Zhang
    7:23 AM, 3 May 2020

    With its massive pooling and multiplexing of computing resources, the cloud offers both large organizations and small businesses the prospect of lower information technology costs, lighter administrative burdens, and rapid scaling of resources. However, multi-tenancy in public clouds makes critical computing resources, such as processor, memory, I/O devices, and storage, shared among virtual machines that are operated by different users. The performance of applications running in public clouds, therefore, may be affected by their neighboring virtual machines due to contention on the shared computing resources. Nonetheless, existing cloud performance monitoring tools do not offer visibility into hardware resources; cloud users have no choice but to blindly run computations on these public services in the hope that the performance is not negatively affected, for instance, by the neighbor’s resource-depleting applications. The lack of performance guarantees is a hurdle faced by all cloud users to fully embrace the economic benefit of cloud computing, and especially by those whose applications demand stability and predictability of the runtime environments. This proposed project aims to solve this problem by developing novel techniques that allow cloud users to monitor the resource contention on the physical cloud servers without the help of the cloud providers. Specifically, the proposed work entails the design, implementation, and evaluation of self-monitoring virtual machines, which leverage the nested virtualization technology and side-channel analysis techniques to monitor the contention in shared computing resources and proactively migrate nested virtual machines to avoid severe performance degradation.

    The project will make broader societal impacts in the following aspects: First, new education tools will be developed through the proposed project. Specifically, one of the outcomes of the intended research will be Amazon machine images with which a derivative cloud can be created on top of public clouds. Enabled by this derivative cloud, students of the operating systems or system security courses can obtain hands-on experience with cloud computing; they will also have access to nested virtualization environments to conduct operating system kernel development. Second, the project will be integrated into NSF’s LSAMP (Louis Stokes Alliances for Minority Participation) program, to help increase underrepresented minority student recruitment, retention, and attainment of STEM degrees, and also to enhance the participation of underrepresented minority students in system research. Third, the project will produce open-source tools that enable self-monitoring VMs in public clouds, which will be made available in the form of source code (available on the project homepage) and Amazon machine images, to encourage adaptation and adoption of the developed techniques

  • Jamie Mikeska
    7:06 PM, 15 June 2020

    School-based field experiences are a critical part of preservice teacher education. The COVID-19 pandemic has significantly disrupted the ability of teacher education programs to place their teacher candidates in typical K-12 teaching settings as a part of learning to teach. This project examines how simulated classroom field experiences for preservice teachers can be implemented in online and emergency remote teacher education courses. Elementary mathematics and science teacher educators are provided with opportunities to engage their preservice teachers in practice-based spaces using mixed-reality simulated classroom environments. These simulations are real-time lessons with animated student avatars that are voiced by an interactor who is responding to the teacher’s lesson in real time in ways that represent authentic student thinking. This project aims to develop support materials for integrating simulated field experiences into elementary mathematics and science teacher education courses. The research will seek to understand what preservice teachers learn about teaching from these experiences, how teacher educators integrate the simulated field experiences into coursework, and how such simulated experiences can be integrated in remote, online courses in ways that support preservice teacher learning.

    This project advances knowledge through the development and deployment of simulation-based tools that develop preservice elementary teachers’ abilities to teach mathematics and science. Preservice teachers use performance tasks to deliver instruction in the simulated classroom. The project develops support materials for teacher educators to integrate this work into online and/or emergency remote teacher education courses (in response to COVID-19) in ways that support engagement in ambitious teaching practice. The project assesses impact on preservice teachers’ ambitious teaching practice through artifacts of the simulated classroom practice, including observations and recordings of the simulated interactions and preservice teacher surveys and assessments of their use of ambitious teaching practices. The project evaluates the ways in which teacher educators integrate the simulated field experience into their emergency remote teacher education courses through surveys and interviews. The research addresses the immediate COVID-19 pandemic challenges in providing field experiences for students and provides long-term support for the ongoing challenge of finding field experience settings that are conducive to preparing highly-qualified elementary mathematics and science teachers.

    The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.

  • Frank Gomez
    7:23 AM, 3 July 2020

    With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this RAPID project will address critical instructional challenges in undergraduate STEM education that result from the COVID-19 pandemic. Specifically, it will produce and deploy virtual labs in upper-division chemistry, physics, and math courses. The rush to online course delivery in response to COVID-19 has revealed limitations of commercially available online virtual labs. Existing virtual lab experiences are generally poorly focused on student exploration. In addition, the effectiveness of virtual lab activities is not well understood, particularly for specific student populations such as Hispanic/Latinx students. To address these opportunities, the California State University system will design three virtual labs that focus on community building, are culturally responsive, and relate to real life events brought about by the pandemic. The project will also study the effectiveness of these virtual labs, thus adding to the body of knowledge about effective online instruction. The creation and delivery of the proposed labs have the potential to positively affect many students, as well as increase equitable access to high-quality learning opportunities. Beyond its immediate impact on improving online laboratory instruction in a time of crisis, this work may provide models for other STEM education initiatives and contribute to institutional and educational changes to better support STEM learning.

    The project aims to develop and test three virtual labs that are purposely designed to create and sustain a culture of inclusion and equity that supports the success of all students, particularly the large population of Hispanic/Latinx students served within the California State University system. The project seeks to increase opportunity and achievement by providing students with avenues to grow STEM identity, self-efficacy, and sense of belonging. The design criteria for the three virtual labs will be informed by culturally responsive and trauma-informed teaching practices. The virtual labs will support instruction across the California State University campuses and beyond, beginning as early as Fall 2020. The overall goal is to directly improve students? knowledge and ability, STEM identity, and integration of identities. The project plans to examine disciplinary best practices in student learning through an informed equity perspective. The project will investigate how to best implement culturally responsive and relevant teaching in virtual science and math laboratory environments and gather and analyze data about the shift to online teaching/learning modalities. Data will be collected every three months from students participating in the virtual labs via pre/post assessments to provide insight into the role of metacognition in their learning. Results of the research will be disseminated through peer-reviewed scholarship, virtual and face-to-face workshops, and reports. This RAPID award is made by the Hispanic-Serving Institutions Program in the Division of Undergraduate Education, Directorate of Education and Human Resources. The HSI Program aims to enhance undergraduate STEM education and build capacity at HSIs.

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