© Shreekant W Shiralkar 2016

Shreekant W Shiralkar, IT Through Experiential Learning, 10.1007/978-1-4842-2421-2_3

3. Bidding Game

Shreekant W Shiralkar

(1)Mumbai, Maharashtra, India

Context: Collaborative Learning and Collective Understanding of ERP

During our school days, my friends and I frequently engaged in discussing specific topics from our textbooks. Each one of us comprehended a specific aspect of the larger subject, and when we shared understanding or knowledge of the topic, we found that our collective understanding helped us raise each individual’s understanding much faster and deeper than individually struggling to comprehend the subject. Later, we even formalized the process during the examination period as we found the process helping learn quickly. During my college days, we practiced the technique further by forming study groups, and when having difficulty understanding a topic, we broke it into subtopics and distributed among the group for learning parts individually and then collectively sharing it with the rest of the group. The process helped each one of us in comprehending knowledge which appeared difficult and complex to us as individuals. The results of learning through a process of discussion were impressive and gave me insight into a few aspects of the concept formally known as “cooperative learning,” which defines the process of learning together rather than being passive individual receivers of knowledge (e.g., teacher lecturing and students hearing). This process allows learners to use cognitive skills of questioning and clarifying, extrapolating and summarizing.

In one of my assignments, I was engaged to train the top management of an organization on ERP and the impact of its implementation. I anticipated that it would be a huge challenge to engage top executives in this training, as most would have had some understanding already, and applying a conventional training process risked losing their attention if my co-trainer or I fell short of their expectations. While individually each top executive may have had generic knowledge of ERP, they certainly lacked comprehensive knowledge, and more specifically a seamless collective understanding of the subject, without any gaps due to individual interpretations or exposures. The task, therefore, was multifaceted: on one hand, I had to get them interested in learning aspects of which they lacked knowledge, and on the other, I had to encourage them to share their individual understandings of the subject, facilitating development of a collective learning.

For a top executive, it is expected that he or she needs to take calculated risks in almost every key decision, whether it’s bidding for a large contract or establishing price point while taking a privately held organization for public trading. The process of bidding involves awareness of collective knowledge of capability, assessment about competition, and expertise to apply judgment based on rational (and some irrational) criteria. In the knowledge-driven economy, the contributions of each employee, regardless of level, add up to the collective capability of the organization.

With a view to facilitate collective learning in the shortest possible time for these top executives, I conceived a “Bidding Game” that leveraged cooperative learning to teach the ERP solution and the impact of its implementation in one session. The result in of Bidding Game was outstanding.

This is the premise of the game that will be explained in this chapter. The game also helps induce elements of social skills like effective communication and interpersonal and group skills in learning an otherwise abstract and complex subject.

The Bidding Game is a game played by all the participants divided into two or more teams. Teams compete on the strength of their collective knowledge of the subject. The game concludes after the collective learning on a specific subject is acquired to the appropriate level on all the essential aspects. The game format provides encouragement to each participant to contribute his or her knowledge of the subject and helps the team to win. A notional value attached to the correct and complete response helps measure the level of knowledge among participants. The competition is premised on the accuracy of the initial bid, which adds a flavor of bidding.

Figure 3-1 will help you visualize the setting created for the participants of the Bidding Game.

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Figure 3-1. Instructor inviting bids

In a hall, participants will be seated in a U-shaped arrangement, facing the projector screen. The hall will have two whiteboards on either side of the projector screen. One of the whiteboards will be titled “Knowledge Bid” and will display the bids by participating teams .

The second whiteboard will record the actual earnings or the SCORE for each of the teams. The projector screen will be used to publish the question for each of the bid, and the instructor will allow the teams to respond in sequence and will record the score on the whiteboard on the basis of the accuracy and completeness of response by the team (Figure 3-2).

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Figure 3-2. Instructor inviting response to question

In designing the Bidding Game, the elements of competition and encouraging discussion on each aspect form the core theme. The competitive aspect triggers speed, the game element induces interest without force or pressure, and finally discussions and sharing of knowledge facilitate desired coverage of the subject—for instance, technical nuances and features offered by new technology and/or processes, channelling an accelerated Learning and Collective Understanding new technology and/or processes .

Bidding Game Design

To design the Bidding Game, I recommend ensuring that the pace of learning is accelerated gradually, and that learning begins with basic aspects and moves on to the advanced and complex aspects in sequence instead of beginning with complex subjects and then concluding with basics. In the design of the sequence, care has to be exercised in segregating the basic and must-learn aspects from the “nice-to-know” aspects, and design should ensure accomplishing learning of basic and must-learn ones while provisioning for nice-to-know types based on the interest and appetite of the participants. Design the sequence in such a way that initially the participant need to spend less time and are encouraged toward the game and competition, while later parts of the sequence should ensure that participants spend more time in discussions and staying ahead of competition.

The objective—rapid development of collective learning of technology and/or new processes—necessitates a short duration of the Bidding Game.

Let us now examine the task-level details of the Bidding Game beginning with preparation/planning, recommended rules, and then the process for its execution, including steps to consolidate learning after conclusion. An overview of the entire game is depicted in Figure 3-3.

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Figure 3-3. Bidding Game process flow

Complete details of the activities in the process flow are described in detail in the following sections.

Preparation/Planning

  • Divide the subject into 20 subtopics that cover the subject comprehensively.

  • Create a question for each of the subtopics.

  • Create a sequence of questions in a way that gradually raises the level of knowledge.

  • Segment the questions into three levels: Rookie, Advanced, and Expert.

  • Assign different values to questions from the three sets, for example, $100 per question from the Rookie level, $200 per question from the Advanced level, and $300 per question from the Expert level.

  • Develop a clear rule set for the Bidding Game that can be used to explain the game to the participants.

  • Have a scoreboard that displays the bid value of the team and also their score during the progress of the game (use the whiteboard marker pens).

  • Have a large clock for monitoring time and identify assistants for keeping time and recording the score.

Recommended Rules

  • The winner is chosen on the basis of two parameters: high score as well as that which is closest to its bid.

  • Each wrong or incomplete response has a loss of value (i.e., negative marking); for example, a $50 penalty for each wrong or incomplete response.

  • $50 is deducted from the value of a passed-over question or a partly answered question.

  • The completeness of the response to a question can be challenged by competing teams to apply penalty and reduce the score.

  • There’s a limit of 5 minutes for responding to each question. Each round could begin sequence in a way that provides a fair chance to all the teams.

Once all the preparation is completed, the game can begin.

Execution

  1. All the participants are told the context and rationale for the game (i.e., what ERP is and the importance of each of them having a collective understanding of the subject, which would maximize benefit from its implementation). Also, it should be explained how playing a game such as this can increase individual understanding much faster and more deeply than individually struggling to comprehend the subject in isolation.

  2. Participants are divided into teams. Team formation can be done in any way that generates nearly equal numbers of participants for each team (dividing the room, counting off by twos, etc.)

  3. The instructor/quiz master (QM) invites bids from each of the teams, which are recorded on the whiteboard for everyone to see.

  4. The instructor launches the first question on the screen and invites the first team to take its chance, while the timekeeper monitors the time taken by the responding team.

  5. On the basis of correctness and completeness of the response, the instructor assigns a score to the team, which is recorded on the second whiteboard.

  6. In case the question is passed to the second team and they are able to respond correctly and completely, the reduced score is recorded.

  7. In case the question is not answered or is incompletely responded by any of the teams, the instructor shares the correct and complete answer and the subject is discussed and clarified.

  8. The process continues until the subject is completely covered.

  9. The instructor tallies the scores for the teams and announces the winner on the basis of the high score and the bid accuracy .

Once the game is over, observations from experience are collected and crystallized in learning in the next section.

Conclusion

  • The learning gained through the game needs to be articulated and consolidated. Debrief is a process that will aid in articulating learning that participants gained during the game.

  • The process of debrief begins with each participant sharing learning, specifically something that has changed their understanding about the subject during the game.

  • Each participant would have learned something new, be it a very basic addition to earlier knowledge of the subject or very complex information that the participant hadn’t ever known before.

  • The individual learnings are recorded on a whiteboard, which helps in crystallizing and consolidating collective understanding on the subject.

  • Once the game is over, the learning can be consolidated by presenting additional material by way of slides, videos, and so on.

Sample Artifacts

With a view to facilitate the immediate application of the approach in the chapter, a sample list of questions on ERP and Big Data along with an illustrative score sheet with result, are provided in the following section. The correct responses from multiple choices, are identified in bold.

Sample Question Cards: ERP

  1. What is the extended form of ERP?

    1. Enterprise Retail Process

    2. Enterprise Resource Planning

    3. Earning Revenue and Profit

    4. None of the above

  2. Real time in the context of ERP relates to which of the following?

    1. Time shown in the computer system synchs with your watch

    2. Processes/events happen per transaction at the same instant

    3. Both of the above

    4. None of the above

  3. What does “SOA” stand for in relation to ERP system architecture?

    1. Service-Oriented Architecture

    2. System of Accounts

    3. Statement of Account

    4. None of the above

  4. Which of these is not a packaged ERP?

    1. SAP

    2. Oracle

    3. Windows

    4. JD Edwards

  5. In the context of packaged ERP, do “Customization” and “Configuration” refer to the same process, or are they different?

    1. Same

    2. Different

    3. Don’t know

  6. Materials Management in ERP helps to/esnure ?

    1. Increase of inventory

    2. Inventory is well balanced

    3. Both of the above

    4. None of the above

  7. Sales and Distribution Module in ERP helps in which of the following?

    1. Increased customer service

    2. Reduced customer service

    3. Both of the above

    4. None of the above

  8. Financial and Controlling Module in ERP helps in which of the following?

    1. Evaluating and responding to changing business conditions with accurate, timely financial data

    2. Easy compliance with financial reporting requirements

    3. Standardizing and streamlining operations

    4. All of the above

    5. None of the above

  9. Gain from implementation of ERP results in which of the following?

    1. Improved business performance

    2. Improved decision making

    3. Increased ability to plan and grow

    4. All of the above

Sample Question Cards: Big Data

  1. What is Big Data?

    1. Data about big things

    2. Data which is extremely large in size (in petabytes)

    3. Data about data

    4. None of the above

  2. Which are not characteristics of Big Data?

    1. Volume

    2. Velocity

    3. Virtuality

    4. Variety

  3. Which are key inputs for Big Data?

    1. Increased processing power

    2. Availability of tools and techniques for Big Data

    3. Increased storage capacities

    4. All of the above

  4. Which are applications of Big Data?

    1. Targeted advertising

    2. Monitoring telecom network

    3. Customer sentiments

    4. All of the above

  5. Which tools are used for Big Data?

    1. NoSQL

    2. MapReduce

    3. Hadoop Distributed File System

    4. All of the above

  6. Social media and mobility are key contributors to Big Data: true or false?

    1. True

    2. False

  7. Which is not a term related to Big Data?

    1. DatabasesMongoDB

    2. DataTrigger

    3. Pig

    4. SPARK

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Benefit Assessment

After consolidation of the learning, it’s recommended to conduct a benefit assessment exercise to measure the gains from application of the game-based approach. The assessment could be in form of a written quiz on the subject with multiple-choice answers.

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