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Articulate Storyline is a versatile eLearning authoring tool that allows instructional designers to create engaging and interactive eLearning content. One of the most powerful features of Storyline is its ability to create custom conversational interactions with a rich interface. These interactions can simulate real-life conversations, enhance learner engagement, and improve retention by providing a more immersive learning experience. This article will guide you through the process of creating custom conversational interactions using Articulate Storyline.

Understanding Conversational Interactions
Conversational interactions in eLearning are dialogues or exchanges that mimic real-life conversations between learners and virtual characters. These interactions can be used for various purposes, such as:

Role-playing scenarios: Allowing learners to practice communication skills in a safe environment.
Customer service training: Simulating interactions with customers to improve service skills.
Decision-making exercises: Providing scenarios where learners must choose responses and see the outcomes of their decisions.
Benefits of Using Conversational Interactions
Increased Engagement: Interactive dialogues capture learners’ attention and keep them engaged.
Enhanced Retention: Simulated conversations help learners retain information better by providing practical applications of knowledge.
Improved Skills: Role-playing and decision-making exercises enhance learners’ communication and critical thinking skills.
Realistic Practice: Learners can practice real-world scenarios without the risk of real-world consequences.
Steps to Create Custom Conversational Interactions in Articulate Storyline
Plan Your Interaction

Before you start building your interaction in Storyline, it’s important to plan it out:

Define the Objectives: What do you want learners to achieve through the interaction?
Outline the Script: Draft the dialogue, including all possible learner responses and feedback.
Design the Flow: Create a flowchart to map out the different paths the conversation could take based on learner choices.
Set Up Your Storyline Project

Create a New Project: Open Articulate Storyline and create a new project.
Add Scenes and Slides: Organize your project by adding scenes and slides. Each scene can represent a different part of the conversation, and each slide can represent a dialogue exchange.
Design the Interface

Add Characters: Use Storyline’s character library or import custom characters to represent the virtual interlocutors.
Insert Backgrounds: Set the scene by adding relevant backgrounds. This could be a virtual office, a customer service desk, or any setting relevant to your scenario.
Add Text Boxes: Place text boxes on the slides for dialogue and learner responses.

Create Interactive Elements

Buttons for Responses: Add buttons for each possible learner response. These buttons will allow learners to choose their reply.
Triggers for Navigation: Use triggers to link buttons to different slides based on the learner’s choices. This will create a branching scenario where each choice leads to a different outcome.
Variables for Tracking: Use variables to track learner choices and provide customized feedback. For example, you can create a variable to count correct responses or to store the selected responses for later feedback.
Add Audio and Visual Feedback

Record Voiceovers: Add voiceovers to make the interaction more realistic. You can record your own voice or hire professional voice actors.
Insert Animations: Use animations to bring characters to life. For example, you can animate a character to smile or frown based on the learner’s response.
Provide Feedback: Add visual and audio feedback for each response to guide learners and reinforce learning points.
Test and Refine

Preview the Interaction: Use the preview function to test your interaction and ensure that all triggers and variables work as intended.
Gather Feedback: Share the interaction with colleagues or a test group to gather feedback.
Refine and Improve: Make necessary adjustments based on feedback to improve the interaction.
Best Practices for Creating Conversational Interactions
Keep It Realistic: Ensure that the dialogues are natural and realistic. Avoid overly complex language or scenarios that learners might not encounter in real life.
Provide Clear Instructions: Clearly explain how the interaction works and what learners are expected to do.
Use Branching Wisely: While branching scenarios are powerful, they can become complex. Keep the branching manageable to avoid overwhelming the learner.
Incorporate Feedback: Provide immediate feedback for each learner response to guide them and reinforce learning.
Monitor and Update: Regularly review and update the interactions to ensure they remain relevant and effective.

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The market for ‘BigData’ is experiencing a tremendous growth, thereby creating a huge demand for skilled and trained BigData professionals across the globe. Though the demand is massive, the supply certainly seems to be falling short of the demand. The core reason might be the lack of proper homework before attending the interviews.

To make things smoother for you during the interview preparation process, we have listed top 50 commonly asked questions along with the best suited answers, which can help you to successfully crack the BigDataHadoop interview.

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Note: All the questions and answers are prepared by the subject experts who are associated with Kovid Academy.

1. What is Big-Data?

The term ‘Big-data’ is used to represent a collection of large and complex datasets, which are difficult to capture, store, process, share, analyze, and visualize using the traditional RDBMS tools.

2. Explain the five V’s of Big Data?

Big-Data is often described using the five V’s, which are:

Volume – the amounts of data generated every day, i.e. in Petabytes and Exabytes.

Velocity – the speed at which the data is generated every second. After the advent of social media, it probably takes seconds for any news to get viral across the Internet.

Variety – the different types of datagenerated every day that comes in a variety of formats like texts, audios, videos, csv, etc.

Veracity – the uncertainties or the messiness of thedata. With different forms of bigdata, it gets difficult to control the accuracy and quality. The volume often makes up the core reason behind the lack of accuracy and quality of thedata.

Value – having access to bigdata is always a good thing, but failing to extract the real value from it is completely useless. Extracting value means, drawing benefits to the organizations; achieving the return on investment (ROI); and making profits for the businesses working on big data.

3. On what concept the Hadoop framework works?

The Hadoop Framework works on:

Hadoop Distributed File System: HDFS is a Java-based storage unit in Hadoop, which offers reliable and scalable storage of large datasets. It is responsible for storing different types ofdata in the form of blocks.

Hadoop MapReduce: MapReduce is a Java-based programming paradigm that offers scalability across different Hadoop clusters. It is responsible for distributing the workload into different tasks to run in parallel. The job of ‘Map’ is to split the datasets into tuples or key-value pairs, and the ‘Reduce’ then takes the output from Map and combines it with datatuples into a smaller set of tuples.

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Hadoop YARN: Yet Another Resource Negotiator is the architectural framework in Hadoop that allows multiple data processing engines to handle storeddata in a single platform, disclosing a new completely method to analytics.

Note: Reduce jobs are performed only after the execution of Map jobs.