Implementing and Developing Big Data Analytics in the K-12 Curriculum: APreliminary Stage

Peter Tong, Ph.D. Felicia Yong, B.A.

Department of Mathematics and Science Department of Modern Languages

Concordia International School Shanghai King’s University College at Western University

999 Mingyue Road, Jinqiao, Pudong, Shanghai 266 Epworth Avenue, London, Ontario

China, 201206 Canada, N6A 2M3

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Abstract

This paper focuses on the importance of developing and integrating a Big Data program into the K-12 curriculum, and describes the delivery of a pilot high school-level Big Data course at Concordia International School Shanghai (CISS), China. While universities have started offering undergraduate courses in Big Data alongside existing graduate courses, there is still a vast shortage of data scientists in comparison to the high demand of the current job market. The inability to meet this demand lies in the lack of a structured K-12 Big Data program that is fully able to prepare students with the proper set of critical thinking, inductive reasoning and analytical skills required to form a conceptual understanding of Big Data and its applications in STEM and liberal arts fields. Due to the accessible nature of Big Data in today’s learning environment where new subject matter and information are constantly evolving, the pedagogical value of Big Data provides an opportunity for a paradigm shift in teaching from “sage on the stage” to “guided on the side,” as coined by Alison King. Not only does this alternate teaching method create innovative opportunities for students to discover and learn independently, it also enables students to develop the confidence to research and teach themselves in the future. From a an introductory two-week “eXploration” high school course at CISS, Big Data Analytics (BDA) has grown, by student demand, to an new elective course – the first Big Data course offered in the international schools in Asia. With no established teaching resources, the delivery of BDA as a student-centered course consisted of lecture style, peer discussions, and practical learning through group and independent project work investigating the community, industry and commercial sectors. The pioneering of BDA at CISS confirms the stimulating and encouraging need for the specific development of Big Data in K-12 programs to enable an adaptable and progressive education for future generations.

Introduction

Big Data is constantly evolving; initially, what is now referred to as “Big Data,” has previously been known by terms such as “Data Mining” or “Analytics and Data Science” in post-secondary education. The progression in this field has exploded in the last few years. Thus, the vast shortage of data scientists arises from the lack of a structured K-12 Big Data program, which, once implemented, can prepare students with the proper set of critical thinking, inductive reasoning and analytical skills necessary to understand and manipulate Big Data and its applications.With the demand from the students at Concordia International School Shanghai, China, the school spearheaded a new elective course in its 2014-2015 academic year: Big Data Analytics. This pilot course was created to meet the needs of high school students in order to better prepare them for their university education, and as such, it is the first Big Data course that is offered in the international schools in Asia.

The Need for a Big Data Analytics K-12 Program

Data in its raw form is like an unpolished diamond: it is of no value until it is analysed, tabulated and presented in a form that is understood. Mathematicians, statisticians, scientists and computing scientists transform raw data into comprehensible and usable information. Big Data Analytics (BDA)is the current term used to describe the process of harvesting raw data and transforming the data into valuable information that can be comprehended. People in diverse fields ranging from business, economics, social sciences, arts and humanities, and the sciences are realizing the need for understanding what is Big Data and how it can be applied to benefit the commercial, industrial, academic fields, and research and development, to name a few.

Within the last decade, universities have been offering courses in Big Data at the graduate level, while undergraduate courses specifically on Big Data were only offered in the last year. Since universities are not churning out data scientists fast enough to meet the demand of the current job market, graduate students in such programs are being headhunted with a very attractive remuneration while in the midst of completing their graduate education in Big Data. A simple keyword search under “jobs for data scientists” produces numerous hits, and reveals the attractiveness of data scientists’ remunerationand job opportunities (Figure 1a and 1b).

Figure 1a: Salary Comparison (UK) Figure 1b: Job Opportunities (UK)

The natural preparation pipeline to meet the demand of data scientists is illustrated in Figure 2:

Figure 2: Preparation Pipeline from K-12 to the Job Market

However, this natural progression does not reflect the existing programs available. While Big Data education is relatively established at the graduate level and undergraduate courses are in their infancy stage, there arescarcely any programs specialized in Big Data Analytics at the K-12 level. This absence highlights animperative need in the K-12 curriculum to prepare students for this new field of education, but there are no existingparameters for this type of program development.This poses the biggest challenge in comparison to established courses in the current K-12 curriculum, for which mature syllabi, textbooks, teaching resources and pedagogies are readily accessible.

In order to introduce Big Data Analytics as a new subject into the K-12 classroom, curriculums and pedagogies have to be developed and established so students can be prepared to enter the field at the post-secondary level. The other challenge in teaching BDA in the K-12 program is that BDArequiresa background of advanced knowledge, such as information technology, programming, math, inductive reasoning and a high level of analytical skills. Pedagogically, implementing BDA in the curriculum is animmense task because BDA requires a great deal of background knowledge in various subjects. The more we try to simplify BDA for the middle and elementary school level the more challenging it will be, as young students have not had any exposure to the knowledge required to understand BDA.The question remains: How can the preliminary skills and background knowledge be introduced and taught at each level of the K-12 curriculum?

A Paradigm Shift in Teaching

In this paper, work is being carried out to develop BDA for high school students with the understanding that it will be further developed for middle and elementary school. The main content foci of this course are to create awareness, exposure, the applications and a general conceptual understanding of Big Data. Due to the accessible and constantly evolving nature of Big Data, the early stages of BDA development in highschool led to two initiatives – a paradigm shift in teaching and the birth of a new course subject: Big Data Analytics.

As a new course in high school at CISS, Big Data Analyticsprovided an opportunity for a paradigm shift in teaching. Should a student choose to further investigate a subject, well-developed resources for all levels from the Internet can supplement established courses in the current K-12 curriculum that are generally taught through the teacher directed approach. However, there are no established teaching resources of any kind for Big Data at the high school level and as with any new subject, it has to start somewhere.With the support and encouragement from the school’s administrator, Mr. Nick Kent, the course instructor took the opportunity to teach this course using “guide on the side,” a teaching method discussed by Alison King’s “From Sage on the Stage to Guide on the Side.” This is a very powerful method of teaching where students are being “guided on the side” by the teacher, as opposed to the “sage on the stage” teaching method where the teacher directly delivers information to the students. In today’s learning environment where new subject matters and information are rapidly evolving, it is very difficult toassemble current material to which students can refer. Hence, it is important for students to learn how to teach themselves, how to develop learning material and techniques, how to look for information and how to be effective communicators. In accordance with the proverb, “Give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime,” these learning skills will not only allow students to learn subject matter in the classroom, but will also give them the tools to teach themselves in future new subject areas. The goal of an educator lies beyond the mere retention and application of knowledge, and extends to the ability to create a confident learning environment, where the students gain confidence in their learning abilities when they feel they are doing the learning themselves. Through this method, students are empowered by their independent learning abilities and, as a result, they will feel a greater sense of achievementin both their education and in themselves.

Teaching BDA is most efficient when the teaching method reflects the open-ended and perpetual nature of information as it currently materialises. At the high school level, the methodology of a BDA course delivery refers to King’s “guide on the side” teaching method. The teacher is required to have a structured framework of clear guidelines, objectives and goals for the course. This teaching method also allows the teacher to bring out the strengths and colors of their students while allowing students to make improvements to their areas of weakness, through the students’ investigation of the subject matter.

A Pilot Course: Big Data Analytics

Concordia International School Shanghai is a student-centered international school that caters to expatriate students in Shanghai, where the dedicated, passionate administrators and teachers are very committed to meeting the students’ needs. CISS has a two week “eXploration” teaching time at the end of the academic year, where teachers are encouraged to teach subjects that are passionate to them or to explore new courses with the ninth andtenth graders. Initially, BDA was proposed to be an “eXploration” course, but while it was being developed for eXploration teaching, the eleventh grade was completingan internship with IBM’s Cloud Development Lab in Shanghai, where the students were introduced to Big Data through DemandTec’s Retail Challenge. Based on new interest and student demand, BDA was fast-tracked from the two week “eXploration” trial course to a new, one semester elective course – the first of its kind in international schools in Asia.

One of tasks in creating the curriculum for this new course was to develop content guidelines and essential questions. For example:

  • What is Big Data?

-How does a single piece of information transform to a big piece of information?

-The 5 V’s: Volume, Velocity, Variety, Veracity and Value

-How does Big Data different from statistics?

-Examples: Moneyball, H1N1 Flu, How Target found out about a teenage pregnancy, Oren Etzioni’sFarecast

  • How valuable is Big Data?

-Why is data information so important?

-To whom are they important?

-Why is Big Data a game changer?

  • Where can Big Data be applied?

-Financial world, education, social sciences, judicial system.

-How are corporations using Big Data to solve their problems?

  • What is the vehicle for Big Data?

-Cloud computing.

-Structured and unstructured data.

-Hardware/Software requirement.

-Management system.

-Analytics

Suggested books for this course:

  • Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schönberger and Kenneth Cukier
  • Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel and Thomas H. Davenport
  • Predictive Analytics, Data Mining and Big Data: Myths, Misconceptions and Methods by Steven Finlay

This new course was designed as a peer-learning course with the teacher in a “guide on the side” role. For this pilot course, a student delivered the day-to-day lessons using PowerPoint lecture style under the teacher’s guidance. The PowerPoint lecture style lessons were essentially a verbatim of the book used for this course, Viktor Mayer-Schönberger’s and Kenneth Cukier’s Big Data: A Revolution That Will Transform How We Live, Work, and Think, further clarified using pictures and video clips to bring the words and lessons to life.

While the general concepts of Big Data were taught through lecture style and peer discussions, the practical learning of this course occurred through its applications. The teacher incorporated both group and individual projects in coordination with the BDA course educational goals, which reference Bloom’s taxonomy as checkpoints: Knowledge, Comprehension, Application, Analysis, Synthesis, and Evaluation. The students were given in-class time for peer discussions and to further research the materials taught after each lecture. At the end of each subsection the students orally presented their knowledge and comprehension of the material by creating PowerPoint summaries of the topic, which included a different perspective of delivering the contents with different examples than the lecture.

Students were also required to complete project work as a class and individually, thereby covering the application, analysis and synthesis course goals. One class project required students to use heartbeat monitors to collect and analyse fitness data for the grading purposes of a CISS middle school physical education (PE) class. Not only did this project encourage students to recognize the practical applications of Big Data within their school community, it enabled them to use the tools and concepts of Big Data to identify flaws in the data collection system. In the execution of the project, the studentssubsequentlyworked towards improving the techniques to more accurately chart and grade the learning progress of a PE student. This was a successful practical learning opportunity for the students as they provided new insights to the middle school PE department on how to optimize instruction and what kind of data to collect, in order advance their PE instruction and coaching methods.

Since this course was designed to be student-centered and to highlight the students’ strengths and interests, students were required to research their topic of interest on Big Data applications. However, the final presentation was more than a summation of their research interests; it required a large-scale (1.8m x 2.0m) poster (Appendix A) and PowerPoint presentation to the school’s administration team, the head of school and the parent community, many of whom are industry professionals. The opportunity to present these findings to an audience greater than the school community added an unexpected level of achievement for the students: professionalism.

The course connected students to their school, local and global communities, in addition to the academic community. Big Data university academics were brought in as guest lecturers via Skype. The guest lectures were an important part of this course as they provided feedback from academic experts and gave the students a prime opportunity to learn the relevance and potential of Big Data in post-secondary education and beyond.The course opened the doors to real-world exposure and networking opportunities for the students. One of the students now has a head start in her academic career as she networked with one of the guest lecture professors, and is now collaborating with the professor on an undergraduate research project upon entering university in the fall. While this student is only one example of many, the overall outcome of the course surpassed the initial expectations.

Conclusion

I would like to acknowledge and express my gratitude to Concordia International School Shanghai’s high school principal, Mr. Nick Kent, for his encouragement, support, commitment, and willingness to embrace the risk ofbeing the first international school in Asia to pioneer a course on Big Data Analytics.I would also like to thank William Wang for initiating the idea of a BDA course and for preparing and delivering the daily lectures.

In summary, a preliminary framework for Big Data Analytics in the K-12 curriculum was developed and successfully tested through the pilot BDA CISS high school course in combination with the “guide on the side” teaching method. Evidently, the success of this course encourages further development of a K-12 BDA program, and especially highlights the needto introduce fundamental background skills at the elementary and middle school levels. For example, future developments might include programming tools and data visualization. As the field of Big Data continues to evolve, the K-12 curriculum should reflect these changes, and expose students to greater potential and possibilities for the future.