Big Data in Education Sector

Editor's Notes

• #2: 1
• #3: Nelson Mandela, former president of South Africa, 1993 Nobel Peace Prize laureate. Occasion: Launch of Mindset NetworkPlace: Planetarium, University of the Witwatersrand Johannesburg South AfricaDate:  Wednesday, July 16, 2003 Source: http://db.nelsonmandela.org/speeches/pub_view.asp?pg=item&ItemID=NMS909
• #5: Source: Cave, R., Foden, N., King, M., and Stent, M. Personalised education: From curriculum to career with cognitive systems. IBM Corporation. April 2016. http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=EDW03008GBEN
• #6: … perspectives of respondents varied widely across these four major roles surveyed. A correlation analysis was run to evaluate the variance between responses from executives from the four roles surveyed in the study. The analysis revealed a significant variance between the responses from Labor / Workforce Policy executives and Industry executives. Workforce Development and Education executives were closely aligned to one another and more greatly aligned with Industry than their Labor / Workforce Policy peers.
• #7: Sources: Martec’s Law - http://chiefmartec.com/2013/06/martecs-law-technology-changes-exponentially-organizations-change-logarithmically/ IBV Millennial survey: How do you prefer to obtain network-related knowledge and skills? (Millennials n=1,153, Gen X n=353, Baby Boomers n=278)
• #8: Technology is disrupting and driving new requirements and opportunities for higher education… Increased competition through greater options Rapid emergence of blended learning models and online platforms Universities are no longer just offering the traditional brick and mortar lectures, many courses can be accessed online as well as the classroom New entrants into the higher education industry such as massive online open courses (MOOCs) deliver a greater variety in learning content to core customers online e.g.: edX, Coursera, Udacity Forcing rapid changes to curriculum to remain relevant Technological advances (e.g., 3D printing, advanced robotics, cloud, mobile, etc.) are disrupting current business needs and skills demanded Curricula must keep pace with technology changes to meet the changing demands of industry and the skills required Rapidly changing expectations from students Students have new expectations on how they interact with content and they expect educational content to be more easily accessible and engaging Students hold higher expectations of higher education today than ever before. Curricula being taught is expected to be relevant, applicable, and help build relationships Variety in curricula is imperative for students today Creating new opportunities for enhancing learning experiences Increasing number of innovative alternatives to traditional higher education models are emerging with greater emphasis on skill development Delivery methods of lesson plans are to be more engaging and interactive with the use of new technology Ability of technology to improve practice simulations making them much more realistic than before (see Center for Advanced Medical Learning and Simulation [CAMLS] case study)
• #9: … perspectives of respondents varied widely across these four major roles surveyed. A correlation analysis was run to evaluate the variance between responses from executives from the four roles surveyed in the study. The analysis revealed a significant variance between the responses from Labor / Workforce Policy executives and Industry executives. Workforce Development and Education executives were closely aligned to one another and more greatly aligned with Industry than their Labor / Workforce Policy peers.
• #10: Source: Q16 “Where do you see the greatest opportunity for technology to impact higher education?” n = 883 Higher education should embrace technology to improve education access, experience, and variety Industry and academic leaders identify the four most beneficial uses of new technology in higher education as: Promoting education access: provide greater access to classes, curricula, and other educational content Deepening education experience: integrate physical and digital worlds for a more compelling and engaging educational experience Expanding education variety: enable pursuit of educational experiences beyond traditional higher education institutions Improving outcomes: enable improved decision making by focusing on patters that demonstrably improve student success 62% of academics believe the benefits of technology outweigh the adoption costs of technology when improving the technology resources available to students and faculty. Q18 “For each of the following areas, how would you evaluate the relevant cost and benefit of each?” n = 603
• #11: Moving your company along the journey to becoming a digital business takes a combination of elements. Some of them are beyond this presentation – because they take true commitment from everyone; the executives down to the employees. However, once the decision has been made to begin the journey, the elements needed include; ideas, data, analytics, skills, and the tools to get you there. At IBM we can help with both the infrastructure, skills and processes to help guide you on this journey. In Summary – these are the areas to consider and a high level summary of the steps most organizations follow to get through their first analytics project. START WITH A REAL PROBLEM TO SOLVE - Focus on solving a real problem. This helps to ensure your strategy aligns with your business and data, provides real ROI to justify your expenses, and gives your company a win. DETERMINE DATA YOU NEED TO ANSWER YOUR QUESTIONS – Don’t limit yourself to just using internal data or structured data – think about how you could incorporate behavioral data from external sources. Think about sensor data, video, and audio and if they would help with your analytics. For example, many companies are using mobile phone as sensors to determine location and preferences of their consumers. As you start working with the data during the analytics stage, you will most likely return to this stage to either obtain more data as you continue to refine your analysis. SELECT THE "BEST” TECHNIQUES TO GENERATE VALID, RELIABLE FINDINGS - There are many techniques used to conduct analytics. Typically one chooses the technique or techniques likely to yield results for the kinds of predictions one wants to make, and then looks for the best tools to achieve the intended goals and outcomes. Selecting the most appropriate techniques for analytics has a lot to do with knowing the questions that the analysis will help answer, or the performance problems to be solved. Don’t force your research design to fit the platform; select the platform you need for achieving the goals you want to achieve. PLAN TO SPEND TIME CLEANING YOUR DATA – As mentioned during the Gather all the Data stage, you will most likely find the data contains quality issues or outliers you’d prefer to exclude from your analysis. Additionally you might find working with aggregates or transforming the data may work well with what you’re trying to accomplish. BE PREPARED TO ACT ON YOUR FINDINGS - Simply knowing the outcome isn’t enough. Your predictions must be actionable. You need to find students at risk, mitigate risks and discover how different students can be better served with targeted interventions and supports. Analytics without action don't really matter very much to anyone. Depending on the type of analytics you’re performing, deploy the outcome into either an application, report, or process.
• #12: Hortonworks Hadoop customers need large scale data ingest, transformation, cleansing, monitoring, and business level cataloging.
• #13: Now let’s dig into the IBM Data Science Experience (DSX). DSX is a single place to Learn, Create, and Collaborate – the 3 pillars of a successful data science organization. With DSX we are making it easier for data scientists and data science teams to learn new skills and technologies from the fast moving data science profession. Users can join the 400,000+ registered users on Big Data University to take courses and administer custom curriculum on Data Science. DSX also provides freely available datasets, code samples, tutorials and articles from the data science community, thereby making it easier for data scientists to learn in-context. We also know that a data science team isn’t going to standardize on a single technology or tool – data scientists need an open and integrated platform that brings all of their tools in one place. DSX brings together the best of open source such as RStudio, Spark, and Python in an integrated environment along with IBM value-adds, such as a managed Spark service and data shaping capabilities all in a secure and governed way. Users can collaborate in DSX with ease -- you can manage project assets and user collaboration through built-in social features for sharing, forking, and reusing assets. These built-in collaboration features can really help boost team productivity and managing projects across their lifecycle.