Effective Work Sample Exercises for Hiring Digital Learning Specialists

In today's rapidly evolving workplace, Digital Learning Specialists have become essential team members for organizations committed to employee development and training excellence. These professionals bridge the gap between educational content and technology, creating engaging learning experiences that drive real results. Finding the right Digital Learning Specialist requires more than just reviewing resumes and conducting standard interviews—it demands seeing candidates' skills in action.

Traditional interviews often fail to reveal a candidate's true capabilities in instructional design, technical proficiency, and collaborative problem-solving. By incorporating well-designed work samples into your hiring process, you can observe firsthand how candidates approach real-world challenges they'll face in the role. These practical exercises provide invaluable insights into a candidate's thought process, creativity, and technical abilities that might otherwise remain hidden.

The most effective Digital Learning Specialists combine strong instructional design principles with technical savvy and data-driven improvement strategies. Work samples allow you to evaluate these multifaceted skills in context, helping you identify candidates who can truly deliver impactful learning experiences for your organization. Additionally, these exercises give candidates a realistic preview of the role, ensuring better alignment of expectations on both sides.

The following work sample activities are specifically designed to evaluate the core competencies required for Digital Learning Specialists: instructional design expertise, technical proficiency, collaboration skills, and continuous improvement mindset. By implementing these exercises in your hiring process, you'll be better equipped to identify candidates who can create engaging, effective digital learning experiences that drive your organization's training and development goals.

Activity #1: Microlearning Module Development

This activity evaluates a candidate's instructional design expertise and technical proficiency by challenging them to create a short, focused learning module on a specific topic. It reveals their ability to distill complex information into engaging, accessible content while demonstrating their technical skills with learning authoring tools.

Directions for the Company:

• Provide the candidate with a brief on a specific topic relevant to your organization (e.g., "Cybersecurity Basics," "Customer Service Excellence," or "Product Knowledge").
• Include key learning objectives that the module should address (limit to 2-3 objectives for this exercise).
• Specify the target audience for the learning module (e.g., new hires, sales team, customer service representatives).
• Allow candidates to use their preferred authoring tool (Articulate Storyline, Adobe Captivate, Rise, etc.) or provide access to your organization's standard tool.
• Give candidates 2-3 days to develop their microlearning module, which should be 5-10 minutes in length.
• Provide any brand guidelines or templates that should be followed.

Directions for the Candidate:

• Create a 5-10 minute microlearning module on the assigned topic that meets the specified learning objectives.
• Include at least one interactive element (quiz, drag-and-drop, scenario, etc.) to engage learners.
• Design the module for the specified target audience, considering their prior knowledge and learning needs.
• Incorporate appropriate visuals, audio (if applicable), and text to create an engaging learning experience.
• Ensure the module follows adult learning principles and best practices in instructional design.
• Be prepared to explain your design choices and how they support the learning objectives during the review session.

Feedback Mechanism:

• After reviewing the module, provide specific feedback on one aspect the candidate executed well (e.g., "Your interactive quiz effectively reinforced the key concepts").
• Offer one constructive suggestion for improvement (e.g., "The text-heavy slides could be broken up with more visuals").
• Ask the candidate to revise one specific element of their module based on your feedback, giving them 15-20 minutes to make adjustments.
• Observe how receptive they are to feedback and their ability to quickly implement improvements.

Activity #2: Learning Needs Analysis and Solution Planning

This exercise assesses a candidate's ability to analyze learning needs and develop appropriate digital learning solutions. It demonstrates their strategic thinking, problem-solving skills, and understanding of how to align learning initiatives with organizational goals.

Directions for the Company:

• Create a fictional but realistic scenario describing a performance gap or training need within your organization (e.g., "Sales team struggling with new product knowledge," "High error rates in a specific process," or "Need to train employees on new compliance requirements").
• Provide relevant background information such as audience demographics, current knowledge levels, business impact of the issue, and any constraints (budget, timeline, technology limitations).
• Include some basic data points that illustrate the problem (e.g., performance metrics, survey results, or feedback from stakeholders).
• Allow candidates 45-60 minutes to analyze the information and develop their recommendation.
• Prepare questions to probe their thinking during the presentation phase.

Directions for the Candidate:

• Review the scenario and supporting information to identify the core learning needs.
• Develop a comprehensive digital learning solution that addresses the identified needs.
• Your recommendation should include:
• Analysis of the root causes of the performance gap
• Clear learning objectives for your proposed solution
• Description of the recommended learning approach and delivery methods
• Outline of content and activities to be included
• Implementation timeline and key milestones
• Methods for measuring effectiveness and success
• Prepare a 15-minute presentation of your analysis and recommendation, followed by 15 minutes of discussion.
• Be prepared to explain the rationale behind your choices and how they address the specific needs in the scenario.

Feedback Mechanism:

• After the presentation, highlight one particularly strong aspect of their analysis or recommendation (e.g., "Your identification of the root causes was thorough and insightful").
• Provide one area where their solution could be enhanced or refined (e.g., "Consider how you might address the time constraints of the target audience").
• Ask the candidate to spend 10 minutes revising or expanding on the aspect you identified for improvement.
• Evaluate their ability to think critically about their own work and adapt their approach based on feedback.

Activity #3: Technical Support Role Play

This role play evaluates the candidate's ability to provide technical support to users of digital learning platforms, a critical aspect of the Digital Learning Specialist role. It reveals their technical knowledge, communication skills, problem-solving abilities, and customer service orientation.

Directions for the Company:

• Develop a scenario involving a common technical issue that users might encounter with your learning management system or other educational technology (e.g., trouble accessing a course, issues with video playback, or difficulty completing assessments).
• Prepare a script for the interviewer who will play the role of a frustrated user with limited technical knowledge.
• Include some challenging aspects in the scenario, such as the user being unable to clearly describe the problem, having already tried some troubleshooting steps incorrectly, or expressing frustration about the platform.
• Allocate 15-20 minutes for the role play exercise.
• If possible, provide access to a test environment of your LMS or use screenshots to simulate the troubleshooting process.

Directions for the Candidate:

• You will participate in a role play scenario where you provide technical support to a user experiencing difficulties with the learning platform.
• Listen carefully to understand the user's issue, asking clarifying questions as needed.
• Guide the user through troubleshooting steps in a clear, non-technical manner appropriate for their level of technical proficiency.
• Maintain a patient, empathetic demeanor throughout the interaction, even if the user becomes frustrated.
• Explain the cause of the issue (if identified) and provide recommendations to prevent similar problems in the future.
• Document the issue and resolution as you would in a real support situation.

Feedback Mechanism:

• After the role play, commend one aspect of their support approach that was particularly effective (e.g., "Your step-by-step guidance was very clear and easy to follow").
• Suggest one area for improvement in their technical support approach (e.g., "Consider checking for understanding more frequently when explaining technical concepts").
• Give the candidate a brief follow-up scenario related to the same issue but with a slight variation, allowing them to implement your feedback.
• Observe how they adjust their approach based on the feedback provided.

Activity #4: Learning Analytics Interpretation and Improvement Planning

This exercise assesses the candidate's ability to analyze learning data and use insights to drive continuous improvement of digital learning programs. It demonstrates their analytical thinking, data interpretation skills, and strategic approach to enhancing learning effectiveness.

Directions for the Company:

• Prepare a dataset from a fictional or anonymized digital learning program, including metrics such as:
• Completion rates for different modules
• Time spent on various activities
• Assessment scores and question-level performance
• Learner feedback and satisfaction ratings
• User engagement patterns (e.g., drop-off points, repeat visits)
• Include some clear patterns or issues in the data that require attention (e.g., high drop-off at a specific module, poor performance on certain assessment questions, or low engagement with particular content types).
• Provide context about the learning program's objectives and target audience.
• Allow candidates 45-60 minutes to analyze the data and prepare their recommendations.

Directions for the Candidate:

• Review the provided learning analytics data to identify patterns, trends, and potential issues.
• Analyze the effectiveness of the learning program based on the data, considering factors such as engagement, completion, knowledge acquisition, and learner satisfaction.
• Identify 3-5 key insights from the data that suggest opportunities for improvement.
• Develop specific, actionable recommendations to address the identified issues and enhance the overall effectiveness of the learning program.
• For each recommendation, explain:
• The data that supports this improvement opportunity
• The specific changes you propose
• How these changes will address the identified issues
• How you would measure the impact of these improvements
• Prepare a 15-minute presentation of your analysis and improvement plan, followed by 15 minutes of discussion.

Feedback Mechanism:

• After the presentation, highlight one particularly valuable insight or recommendation they provided (e.g., "Your identification of the correlation between video length and completion rates was especially insightful").
• Suggest one area where their analysis could be deepened or their recommendations refined (e.g., "Consider how you might segment the data by user demographics to uncover more targeted improvement opportunities").
• Ask the candidate to spend 10 minutes expanding on or refining their approach based on your feedback.
• Evaluate their ability to think critically about data and adapt their analytical approach.

Frequently Asked Questions

How much time should we allocate for these work sample activities?

The microlearning module development should be assigned as a take-home exercise with 2-3 days for completion. The learning needs analysis, technical support role play, and analytics interpretation exercises can each be conducted during an interview session, allocating 60-90 minutes per activity including time for feedback and discussion.

Should we use all four activities in our hiring process?

Not necessarily. Select the activities that best align with the specific responsibilities of your Digital Learning Specialist role. For most positions, using two complementary activities (e.g., the microlearning module development and either the needs analysis or analytics interpretation) provides sufficient insight while respecting candidates' time.

How should we evaluate candidates' performance on these activities?

Create a structured evaluation rubric for each activity based on the key competencies you're assessing. Include both technical aspects (e.g., instructional design quality, technical execution) and soft skills (e.g., communication clarity, receptiveness to feedback). Have multiple evaluators use the same rubric to reduce bias.

What if candidates don't have access to the same authoring tools we use?

For the microlearning module development, consider offering alternatives: allow candidates to use their preferred tools, provide temporary access to your tools, or accept low-fidelity prototypes (e.g., PowerPoint with notes explaining interactivity). The focus should be on their instructional design approach rather than tool-specific technical skills, which can be learned.

How can we make these activities accessible and fair for all candidates?

Provide clear instructions and expectations in advance. Offer reasonable accommodations when requested. Ensure scenarios don't require specialized industry knowledge unless absolutely essential for the role. Consider candidates' varying access to technology and provide options when possible.

What if a candidate performs well in interviews but struggles with the work samples?

This discrepancy is precisely why work samples are valuable—they reveal practical skills that interviews might not. Consider the specific areas where the candidate struggled and whether those skills are trainable or essential for day-one performance. Balance work sample results with other assessment methods for a complete picture.

In today's competitive talent market, finding the right Digital Learning Specialist can significantly impact your organization's training effectiveness and employee development outcomes. By incorporating these targeted work sample activities into your hiring process, you'll gain deeper insights into candidates' real-world capabilities and identify those who can truly excel in designing, developing, and delivering impactful digital learning experiences.

Ready to take your hiring process to the next level? Yardstick offers comprehensive tools to help you design and execute exceptional candidate interviews. From creating tailored job descriptions with our AI Job Description Generator to developing targeted interview questions with our AI Interview Question Generator and comprehensive evaluation frameworks with our AI Interview Guide Generator, we provide everything you need to identify and hire top Digital Learning Specialist talent. Learn more about how these work samples can be integrated into a complete interview process by visiting our Digital Learning Specialist job description.

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