Teaching Data Analytics

Pedagogy and Program Design

Susan Vowels, Katherine Leaming Goldberg

• Publisher: CRC Press
• Year: 2019
• Print ISBN: 9781138744141
• eBook ISBN: 9781351721448
• Edition: 1
• Topic: Informatique
• Subtopic: Extraction de données

The need for analytics skills is a source of the burgeoning growth in the number of analytics and decision science programs in higher education developed to feed the need for capable employees in this area. The very size and continuing growth of this need means that there is still space for new program development. Schools wishing to pursue business analytics programs intentionally assess the maturity level of their programs and take steps to close the gap.

Teaching Data Analytics: Pedagogy and Program Design is a reference for faculty and administrators seeking direction about adding or enhancing analytics offerings at their institutions. It provides guidance by examining best practices from the perspectives of faculty and practitioners. By emphasizing the connection of data analytics to organizational success, it reviews the position of analytics and decision science programs in higher education, and to review the critical connection between this area of study and career opportunities. The book features:

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• A variety of perspectives ranging from the scholarly theoretical to the practitioner applied
• An in-depth look into a wide breadth of skills from closely technology-focused to robustly soft human connection skills
• Resources for existing faculty to acquire and maintain additional analytics-relevant skills that can enrich their current course offerings.

Acknowledging the dichotomy between data analytics and data science, this book emphasizes data analytics rather than data science, although the book does touch upon the data science realm. Starting with industry perspectives, the book covers the applied world of data analytics, covering necessary skills and applications, as well as developing compelling visualizations. It then dives into pedagogical and program design approaches in data analytics education and concludes with ideas for program design tactics. This reference is a launching point for discussions about how to connect industry's need for skilled data analysts to higher education's need to design a rigorous curriculum that promotes student critical thinking, communication, and ethical skills. It also provides insight into adding new elements to existing data analytics courses and for taking the next step in adding data analytics offerings, whether it be incorporating additional analytics assignments into existing courses, offering one course designed for undergraduates, or an integrated program designed for graduate students.

SECTION II

CURRICULAR AND COCURRICULAR ASSIGNMENT DESIGN

4

FORMATIVE AND SUMMATIVE ASSESSMENTS IN TEACHING ASSOCIATION RULES

MATT NORTH

Utah Valley University

Contents

Introduction

Active Learning

Formative versus Summative Assessment

Association Rules

Direct Instruction

Formative Assessment #1

Continuing Direct Instruction

Formative Assessment #2

Going Big

Using R

Formative Assessment

Summative Assessment

Conclusion

References

Introduction

This chapter focuses on two elements of effective teaching in data analytics: assessment of learning and the analytic technique of Association Rules. The goal of this chapter is to help educators understand the essential role of assessment when teaching analytics, and to provide a tangible example of how to use assessment techniques to confirm that learners understand the analytics technique being taught. The concepts of formative and summative assessment are explained and illustrated and then reiterated through a hands-on tutorial, which demonstrates how to use the R statistical software package to generate and interpret Association Rules. By the end of the chapter, you should be able to explain both formative and summative assessment, how to calculate confidence and support percentages for Association Rules, and how to generate Association Rules in R. Since formative and summative assessments are a teaching and learning technique (as opposed to a data analytics technique), you should be able to demonstrate the application of such assessments in other instructional activities, whether related to analytics or not.

Active Learning

Let’s make this chapter interactive. To participate, here’s what you’re going to need:

• A piece of paper and a pen or pencil
• tablespoons (US measure) of salt
• tablespoons of flour
• tablespoons of water
• Food coloring (if you’re really into this)
• A spreadsheet or basic calculator

Now believe it or not, these items are going to help you learn about a data mining/analytics technique called Association Rules, and importantly for this particular chapter, how to use formative and summative assessments in teaching Association Rules. We’ll start with sa non-Association Rules example in order to focus on the assessment part first.

To start, combine the salt, flour, and water in a bowl and mix the ingredients together until your items start to combine uniformly. Once this happens, knead the product together until it is completely consistent in texture, something approximately the feel of PlayDoh™ or modeling clay. If it is too sticky, add a very little bit of flour until it is not sticky anymore. If it is too dry, do the same with a drop or two of water at a time. Once you reach the desired consistency, if you’d like, you can add a few drops of food coloring and knead it some more until the coloring is consistent. Congratulations! You’ve just made salt dough—a popular, inexpensive alternative to other molding and modeling products, popular for preschools, craft groups and rainy day kitchen table activities. Take your little ball of salt dough and set it aside for now.

Next, take your paper and writing implement and sketch out a picture of an elephant. Don’t worry; you don’t have to be an amazing artist. Just draw what you think an elephant should look like. If you’re not sure, take a little time and look at a few pictures of elephants on the Internet, or in books or photos that may be available to you. Don’t try to copy any of the images exactly, just use them to help you envision the different attributes of an elephant—body, legs, head, ears, tail, trunk—and then draw your elephant. It’s OK if you need to try two or three times, this is part of the exercise. It may be helpful to show your sketch to another person and ask them for feedback.

With your sketch now completed, return to your salt dough. Your task is to mold your ball of dough into an elephant that looks as much like your sketch as possible. Take your time. If you need tools to help you (such as a rolling pin and butter knife), go ahead and use them. Imagine that once you are done, you’ll present your work, both your sketch and your model, to a third party to be judged. This person will determine how well you followed the instructions you’ve been given and how you used those instructions to create the most realistic and accurate salt dough elephant you can.

Formative versus Summative Assessment

This exercise may seem a bit silly, but it helps to contextualize both formative and summative assessments in teaching. You started by simply receiving and following some specific instructions. Some prerequisite knowledge was assumed: you know what salt, flour, and water are, and you know how to measure in tablespoons and mix ingredients. Other knowledge was not assumed: how much of each ingredient to use, and how to combine them. This type of direct instruction is among the most common styles of teaching used (Hadi Mohammad, Nasrin, & Maryam Taleb, 2016). Direct instruction is the teaching style most learners are familiar with, and while not always the most effective, it is often the one we default to when teaching. When the subject matter is formulaic, such as teaching a recipe, it serves as an effective teaching strategy, and most learners can benefit from direct instruction, regardless of their preferred learning styles (Tomkins & Ulus, 2016).

In this example, your instructor could come to your workspace and determine whether or not you have followed instructions correctly. Keep in mind that our objective in this chapter is not for you to learn to make salt dough—the making of salt dough is a step in the lesson, but not one of our learning outcomes. It is simply part of the teaching and learning process. The instructor’s evaluation of your ability to successfully make salt dough is an example of a formative assessment. Formative assessments are usually informal reviews and examinations of a learner’s understanding of a subject or technique being taught, in order to determine the degree to which the learner is understanding and acquiring the intended knowledge (Clinchot et al., 2017). If the ultimate task of this lesson is to teach you, and other learners, how to make model elephants out of salt dough, then the formative assessment of your salt dough helps to ensure that you’re on the right track early in the learning process. If you were given all of the instruction on making a salt dough elephants all at once, and then left to your own devices to make one without any intervention, feedback or help along the way; and worse, if you made your salt dough wrong at the outset, the odds of you successfully making a salt dough elephant would decrease, perhaps dramatically, to the point where you might fail completely in your elephant-making efforts. So it is with most instruction: learners are more likely to achieve comprehension if checked along the way, and when necessary, corrected or reinforced (Klute, Apthorp, Harlacher, & Reale, 2017).

Next we move to the task of sketching your elephant on paper. This step was not presented to you in the form of direct instruction. Instead, you were left somewhat on your own to figure out how to sketch an elephant. Some recommendations were given, such as searching the Internet or books for examples of elephants. This was to help you envision what an elephant looks like, in case this was difficult for reasons that may range from unfamiliarity with elephants to a lack of aptitude in transferring thoughts to paper. It was also suggested that you might ask others for help or feedback. This task is in the vein of what is called Concept Attainment, a teaching and learning technique most often associated with constructivist theory, where students learn through guided exploration that helps them to acquire new knowledge by correctly identifying examples (and nonexamples) of the topic being taught (Bruner, 1985). Rather than being told what an elephant is, or having the attributes of an elephant dictated to you, you were charged with exploring and examining the topic on your own, seeking and evaluating sources of information, and then acting upon your learning activities to complete the task. Again, this activity would be the subject of a formative assessment along your journey to making your salt dough elephant. Your instructor could review your sketch of your elephant to determine if you were able to successfully “attain” the “concept” of an elephant and commit that concept to paper. If you got stuck along the way, your instructor might ha...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Dedication
• Contents
• Preface: Teaching Data Analytics—A Primer for Higher Education
• Acknowledgments
• Editors
• Contributors
• Section I Industry Perspective
• Section II Curricular and Cocurricular Assignment Design
• Section III Program Design Tactics
• Index