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Understanding the Impact of Immersion and Authenticity on Satisfaction Behavior in Learning Analytics Tasks

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Abstract

As business analytics (BA) applications permeate across various industry sectors, the workforce needs to be trained and upskilled to meet the challenges of understanding and implementing analytics methodologies. To achieve payoffs from the resource investments in BA training, it is critical for enterprises to understand an individual’s learning behavior along with the process and outcome-centric satisfaction associated with a collaborative analytics training task. This study focuses on identifying the factors that influence the process of learning during BA training to entry-level BA users. Drawing on the theories of situated cognition, goal setting, and flow, we propose a model that explains how trainees in a group learn through a process that is influenced by the characteristics of BA training context through context authenticity, the traits of trainees through task motivation and preference towards teamwork. Using an experimental design built on data collection and a unique task of real visits to a historic cemetery, we found that context authenticity and task motivation have significant impact on focused immersion, which in turn significantly impacts process and outcome satisfaction for learning an analytics task. Results of this study extend and validate the theories of situated cognition, goal setting, and flow within the context of business analytics training. Based on these findings, we provide recommendations for practitioners for designing effective analytics tasks for better training outcomes.

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Authors and Affiliations

  1. Department of Systems & Technology, Raymond J. Harbert College of Business, Auburn University, 405 W. Magnolia Ave, Auburn, AL, 36849, USA

    Suning Zhu, Ashish Gupta, David Paradice & Casey Cegielski

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  1. Suning Zhu
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  2. Ashish Gupta
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Correspondence to Ashish Gupta.

Appendices

Appendix 1: Data Analysis Task Using Cemetery Data

This data analysis task is based on a small portion of U.S. census data. U.S. Census Bureau collected over 400 variables about the nation’s people and economy. The census data can be used for helping decision makers develop specific solutions to a wide range of problems such as healthcare planning, resource allocation in the city, policy planning, economic development, historical site planning (e.g. historical cemetery) etc. In this task, we randomly selected a small number of variables (5 variables) including age, year of death, gender, veteran status, and state.

Instead of collecting real data from the U.S. Census website, you need to use a build-in function in Excel to generate an artificial data set and visualize it using bubble charts.

Bubble chart is a type of chart that displays three dimensions of data. The first two dimensions are expressed through x coordinate and y coordinate. The third dimension is expressed through the size of the bubble. Bubble charts can facilitate the understanding of social, economic, medical, and other scientific relationships.

Every team needs to answer 6 quiz questions based the bubble charts you made. Then, everyone needs to fill out a survey to evaluate the whole data analysis task you just did. Now, please follow the instructions below to start the task.

Part 1: Generate a simulated data set.

Go to Canvas and find the assignment called “10 Points Extra Credit Task”. Download the Excel file named “Five Variable Template”. Open the file, and you will see five columns named Gender, Age, Year of Death, State, and Veteran Status, respectively. The gender and veteran status columns have already been filled with data. Specifically, gender includes female and male. For the veteran status column, we use “1” to represent that the person is NOT a veteran, and “3” to represent that the person was a veteran. You need to generate simulated data to fill column Age, Year of Death, and State. Please follow the steps 1–6 to generate .ated data for these columns.

P.S. The numbers you generated may be different from the numbers showed in the screenshots. This is very normal because the numbers are randomly generated.

  • Step1: Generate “age” data ranging from 5 to 95 by using randbetween () function. In cell B2, type “=randbetween(5,95)” and then press Enter, you will see a random age number in cell B2. Then, select cell B2, click on the lower right corner of cell B2 and drag it down, now you generate a list of random numbers for the age column.

figure a

  • Step2: Prevent random numbers in the Age column from changing. Select column B, right click your mouse, and click copy. Then, right click your mouse within column B, under paste options select paste values. This will remove the embedded randbetween() function and prevent random numbers from changing if you make any change in other columns.

  • Step3: Generate “Year of Death” data ranging from 1950 to 2016. In cell C2, type “=randbetween(1950, 2016)” and press Enter, you will see a random year in cell C2. Then select C2, click on the lower right corner of cell C2 and drag it down, now you generate a list of random numbers for the Year of Death column.

figure b

  • Step4: Prevent random numbers in the Year of Death column from changing. Select column C, right click your mouse, and click copy. Then, right click your mouse within column C, under paste options select paste values. This will remove the embedded randbetween() function and prevent random numbers from changing if you make any change in other columns.

  • Step5: Generate “State” data ranging from 1 to 5. We focus on five states within U.S. and code these five states using Arabic number 1–5. In cell D2, type “=randbetween (1,5)” and press Enter, you will see a random state number in cell D2. Select cell D2, click on the lower right corner of D2 and drag it down, now you generate a list of random numbers for the State column.

figure c

  • Step6: Prevent random numbers in the State column from changing. Select column D, right click your mouse, and click copy. Then, right click your mouse within column D, under paste options select paste values. This will remove the embedded randbetween() function and prevent random numbers from changing if you make any change in other columns.

Part2: Apply data visualization (bubble charts) to the data set you just created.

Please follow step 7–7 to make a bubble chart for females using age, year of death, and veteran status columns.

  • Step7: create a blank chart. In the Excel, click Insert–>Insert “Scatter (X, Y) or Bubble chart under Charts section, and select 2-D bubble chart. A blank bubble chart window pops up.

figure d

  • Step8: create the bubble chart for females. Click Select Data under “design” tab, the “Select Data Source” window pops up.

figure e

In the “Select Data Source” window, click Add, then the “Edit Series” window pops up.

figure f

Type “female” in the Series name field. For the Series X values, select data values in the Age column where gender = Female.

figure g

Next, clear “={1}” in the Series Y values field, and select data values in the Year of Death column where gender = Female.

figure h

Then, clear “={1}” in the Series bubble size field, and select data values in the Veteran Status column where gender = Female. Click OK in the “Edit Series” window, and click OK in the “Select Data Source” window. You will see the bubble chart for females in the file. The bubble chart you created look like the chart below.

figure i
figure j

  • Step 9: format the bounds and units for x-axis in the bubble chart. Click the bar of x-axis in your bubble chart, right click your mouse, and select Format Axis. Set Minimum = 0, Maximum = 100, Major = 10, and Minor = 2. Press Enter button, then the bar of x-axis will be reset as the screenshot below. We do no need to do anything with the y-axis of the bubble chart.

    figure k

  • Step 10: Add Axis Titles. Click Add Chart Element on the left under Design tab. Then click Axis Titles, and choose Primary Horizontal. Type “Age” in the box for x-axis title.

Again, click Add Chart Element on the left under Design tab. Then click Axis Titles, and choose Primary Vertical. Type “Year of Death” in the box for y-axis title. The chart will look like below.

figure l

Now you create a bubble chart with x-axis representing “Age”, y-axis representing “Year of Death”, and the bubble size representing “Veteran Status” (1 = non-veteran, 3 = veteran).

Please go to Canvas; find the quiz named “Questions for Data Analysis Task” under “10 Points Extra Credit Task” group; answer Q1-Q3 based on the bubble chart you just made for females by following Step 7–10. P.S. You can zoom in the chart to see things clearly.

  1. 1.

    How many females were veterans in your bubble chart?

  2. 2.

    How many females in the bubble chart died before age 50 with the year of death before 1990?

  3. 3.

    How many females in the bubble chart died after age 80?

After you finish Q1-Q3, please follow Step 11–13 to create another bubble chart for males.

  • Step11: Click on the chart you just made. Then click Select Data under Design tab. The “Select Data Source” window pops up.

figure m

  • Step 12: Click Add, and the “Edit Series” window pops up. Type “male” in the Series name field. For the Series X values field, select data values in the Age column where gender = Male.

figure n

Next, clear “={1}” in the Series Y values field, and select data values in the Year of Death column where gender = Male.

figure o

Clear “={1}” in the Series bubble size field, and select data values in the Veteran Status column where gender = Male. Then, click OK in the “Edit Series” window, and click OK in the “Select Data Source” window. You will see two bubble charts for females and males marked in different colors. A bubble chart example is shown below.

figure p

  • Step 13: Format the bounds and units for x-axis. Click the bar of x-axis in your chart, right click your mouse, and select Format Axis. Set Minimum = 0, Maximum = 100, Major = 10, and Minor = 2. Press Enter button, then the bar of x-axis will be reset. We do not need to do any change for y-axis.

Now, please go back to Canvas, and answer Q4-Q6 for quiz “Questions for the Data Analysis Task” based on the bubble chart for males and females. P.S. You can zoom in the chart to see things more clearly.

  1. 1.

    How many people (including both males and females) in the bubble chart were veterans?

  2. 2.

    Did all the veterans (both males and females) live beyond 60 years old?

  3. 3.

    How many males in the bubble chart died before age 20 with the year of death before 2000?

Appendix 2

Table 4 Constructs and Items
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Zhu, S., Gupta, A., Paradice, D. et al. Understanding the Impact of Immersion and Authenticity on Satisfaction Behavior in Learning Analytics Tasks. Inf Syst Front 21, 791–814 (2019). https://doi.org/10.1007/s10796-018-9865-4

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