Home :: Insights :: Measuring the Effectiveness of Learning Technology Stacks

Measuring the Effectiveness of Learning Technology Stacks

November 9, 2023 | By Kelly Lake


Measuring the Effectiveness of Learning Technology Stacks

Learning technology evolves for efficiency and accessibility. Blending technology and human touch drives learning excellence. This article explores measuring a learning technology stack’s effectiveness for a roadmap toward learning excellence.

The imperative to measure the effectiveness of learning technologies: Organizations can achieve the intended learning outcomes and provide value to learners and organizations by measuring the effectiveness of learning technologies. Using a combination of evaluation methods and key performance indicators (KPIs) can provide learning leaders with a comprehensive understanding of the effectiveness of learning technologies. Furthermore, the integration of regular assessments and continuous improvement efforts into the evaluation process can help ensure that the L&D technology remains effective and aligned with evolving learning and organizational needs.

The Need for Measuring the Effectiveness of Learning Technologies

It is a necessity to ensure that the investment in L&D technology contributes to improved learning outcomes and efficiency, aligned with the overall learning goals of the organization. It enables organizations to adapt, improve, and make informed decisions in a rapidly evolving learning landscape.

The changing landscape of learning technologies:

The rapid advancements in learning technologies contribute to the shifts in the way individuals work and learn. This dynamic learning landscape reflects the evolving needs of learners and organizations. As a result, learning technologies will play a pivotal role in shaping the future of learning and performance through artificial intelligence (AI) and machine learning (ML), eLearning, blended learning, personalization, microlearning, gamification and immersive technologies such as virtual reality (VR) and augmented reality (AR), mobile learning, video and multimedia, social learning, accessibility, and sustainability.

Increased investment in learning technologies:

Recognizing the transformative power of technology in learning and development, such as identifying skill gaps and remote workforce development, a large number of organizations are investing in learning technologies. Organizations are investing in innovative technologies such as AR, VR, and AI to provide innovative learning experiences and engage learners in new ways. These investments support the evolution of learning methods and access to knowledge, making learning and skill development more customized, accessible, and effective. It also allows organizations to keep pace with the ongoing digital transformations, leverage digital tools for better outcomes, and make data-backed decisions, with cost savings and greater efficiency.

Accountability and evidence-based decision-making:

Evidence-based decisioning can inform various aspects of the learning process, including resource allocation, developing performance policies, curriculum development, assessment and evaluation, and building in accountability measures. Accountability promotes transparency in training practices and supports continuous improvement. It generally relies on data to measure the effectiveness of learning programs. Therefore, evidence-based decision-making is crucial, not only to interpret the data accurately but also to improve the quality of training. This involves identifying areas for improvement, implementing corrective measures, and building accountability.

Understanding and Defining the Role of the Different Components in a Learning Technology Stack

Producing a comprehensive view of different stacks:

A learning technology stack refers to the collection of various components and tools that work together to support and enhance the learning experience. These components can vary depending on the specific context and goals of the training program or the organization. It is, therefore, crucial to understand and define the role of different components in a learning technology stack for effective implementation and management.

Stating and evaluating the different learning technology platforms:

Below are descriptions of some key components of a learning stack and their respective roles:

  • Learning Management System (LMS): Helps manage and deliver learning content, track learner progress, and facilitate communication.
  • Content Management System (CMS): Manages and organizes digital learning content, such as course materials, multimedia, and assessments.
  • Virtual Learning Environment (VLE): Provides a digital space for learners and instructors to interact, access resources, and participate in discussions and collaborative activities.
  • Adaptive Learning Platforms: Used to personalize the learning experience by adjusting content and activities to the individual needs and progress of learners.
  • E-Portfolio Platforms: Support the creation and management of digital portfolios, showcasing learners’ work and achievements.
  • Gamification and Game-Based Learning Platforms: Use game elements to enhance engagement and motivation in the learning process.
  • Social Learning Platforms: Promote collaboration and social interaction among learners, allowing them to share insights and knowledge.
  • Video Conferencing and Webinar Platforms: Facilitate real-time video communication for virtual classrooms, webinars, and remote collaboration.
  • Learning Experience Platforms (LXPs): Focus on the learner’s overall experience, offering content curation, social learning features, and skill development pathways.
  • Content Delivery Networks (CDNs): Help ensure fast and reliable delivery of digital content, especially for multimedia and video resources.
  • Learning Analytics and Data Warehousing: Collects and analyzes data to provide insights into learner performance, engagement, and course effectiveness.
  • Content Authoring Tools: Enables instructors to create, edit, and publish digital learning content, including interactive multimedia.
  • Assessment and Testing Tools: Support the creation, administration, and scoring of quizzes, exams, and assessments.
  • Augmented Reality (AR) and Virtual Reality (VR): Enhance learning with immersive experiences and simulations, particularly in technical and vocational training.
  • Chatbots and AI-Powered Assistants: Provide effective learner support, answer questions, and offer guidance on a 24/7 basis.
  • Mobile Learning Apps: Extend learning access to mobile devices, allowing learners to engage with content on-the-go.
  • Security and Privacy Tools: Help safeguard learner data, content, and the integrity of the learning environment from growing cyber threats and data breaches.
  • Accessibility Tools and Compliance Solutions: Make learning content and platforms accessible to individuals with disabilities and compliant with accessibility standards.

Reviewing the role of technology and defining objectives:

It is essential to define the role of each component in a learning technology stack, as described above, for effective integration, workflow, and alignment with performance goals. Organizations must consider specific needs when selecting or customizing these components. Furthermore, keep the L&D technology stack current and aligned with evolving performance needs through frequent assessments and adaptation.

5 Pillars to Develop a Strategy for Measuring the Effectiveness of Learning Technologies

In the ever-evolving technological landscape, leaders must learn how to effectively utilize measurements and analytics. Understanding the measurement of technology effectiveness goes beyond tracking the number of users, frequency of use, cost savings, quality improvement, and customer satisfaction.

As a leader, there are 5 basic pillars to consider when developing a strategy for measuring effectiveness:

  1. Realize Organizational Goals

    As a leader, it is crucial to conduct a thorough assessment of organizational learning governance and ensure that the strategic learning strategy aligns with the business’s growth strategy. This includes fact-checking, gaining key opinions, and understanding the current and future capability needs of the learners and the organization. It’s important to acknowledge that the methods used to measure effectiveness in the past may need to evolve as technology advances. Knowing the immediate goals and long-term goals will shape the type of data requirement for leaders to focus on maximizing effectiveness.

  2. Utilize Technology Appropriately

    Technology can be a valuable resource for measuring effectiveness. Some effective examples include e-Learning courses, podcasts, blogs, infographics, games, and simulations.  Additionally, consider incorporating AR, VR, AI, ML, mobile learning apps, and microlearning. By leveraging the power of technology, leaders can enhance learning experiences for all. Per industry reports, 63% of companies plan to increase or maintain AI and ML in 2024. The use of technology should not be a stand-alone solution but it should be used to enhance learning.

  3. Adopt Stakeholder Champions

    It is critical to ensure that the right stakeholders are identified. Once this is done, stakeholders should provide the business goals, the needs and priorities, restrictions and limitations, and budget. Take the time to collaborate with stakeholders so they understand the importance of measuring effectiveness and how technology can help gain greater insights. Provide case studies so they become champions to support the further development of measurement throughout the organization. Building strong stakeholder relationships is key to success.

  4. Understand Technology Trends

    Looking at technology trends aligns a company’s standing and awareness among competitors. It also allows the positives and negatives of utilizing learning technologies to be weighed. Then, leaders can be empowered to speak to stakeholders and those who control the budget and decision-making. Choose the right tools focusing on security, scalability, features, and cost. Reliability usually is the deal-breaker for most organizations. The technology selected must check all the boxes to meet all organizational goals. Comprehending industry trends also offers the opportunity to benchmark L&D practices, utilize best practices, and often facilitates innovation.

  5. Development a Business Case

    By providing a Technology Business Case, leaders can show evidence-based stories for the use of learning technologies. Studies show that people remember real-life examples more readily than facts or datasets. Business cases prompt decision-making and when planned appropriately can be quite effective in getting the buy-in of management, stakeholders, and learners.
    For example, DevOps is a cultural shift that requires vision, planning, executive buy-in, and tight collaboration to successfully establish a more integrated way of developing and delivering applications. DevOps is a collection of flexible software creation and delivery practices that looks to close the gap between software development and IT operations. DevOps practices streamline software development, increase developer productivity, and enhances continuous delivery workflows to deliver better software faster. Applying AI (artificial intelligence) and advanced analytics to IT operations has transformed how organizations manage complex systems.

How to Evaluate While Assessing the Effectiveness of Learning Technology Platforms

A combination of quantitative and qualitative data, alignment with goals and objectives, and a commitment to continuous improvement are essential ingredients for effective evaluation of learning technology platforms. This structured approach empowers organizations to make informed decisions, which further help meet learning objectives, improve learning outcomes, and provide value to learners and organizations. Some of the ways organizations can consider for effective evaluation of L&D technology platforms include:

Learner feedback (feedback from both L&D and the learners):

A valuable source of information, L&D and learner feedback provides insights into the user experience, satisfaction, and areas for improvement, which ultimately contribute to the platform’s effectiveness in supporting training goals. Regular learner feedback can help organizations ensure that the L&D technology platforms remain aligned with user needs and expectations. They can use surveys, questionnaires, feedback forms, Net Promoter Score (NPS) surveys, support requests, social media discussions, usage analytics, and learning outcome data to gather learner feedback.

Review workflow efficiency and integration with other platforms:

Competent workflows and seamless integration contribute to the overall effectiveness of a learning technology platform by reducing friction, streamlining operations, and enhancing the learning experience. Reviewing workflow efficiency helps assess how the platform streamlines training processes, reduces administrative overhead, and saves time for L&D leaders and learners, resulting in enhanced efficiency, personalized learning paths, and easy-to-use interfaces. Organizations must review integration with other platforms to examine how well the platform integrates with other tools and systems, such as Learning Management Systems (LMS), Content Management Systems (CMS), LXP Platforms and analytics tools. This ensures seamless data sharing and compatibility with existing learning infrastructure, evaluates the ease of integrating third-party apps, and creates a more versatile and customizable learning environment.

Monitoring, tracking, and benchmarking existing performance data:

Effective monitoring, tracking, and benchmarking of performance data play a key role in making data-driven decisions. This helps ensure continuous improvement and optimizing the L&D technology platform for better outcomes. Monitoring involves observing the platform’s usage, user engagement, and performance data in real-time, which helps identify any anomalies, issues, or patterns as they occur, and take prompt corrective action. Tracking allows collecting and recording performance data over time to create a historical record. This data can be used to analyze trends and patterns to identify long-term changes in user behavior and platform performance. Benchmarking helps compare performance data with industry standards, best practices, or peer institutions, to determine how the platform fares in comparison to others.

Data collection and analysis to evaluate the effectiveness of learning technology platforms:

Actionable insights are crucial to assessing the learning technology platform’s performance and informing improvements. As a result, effective data collection and analysis play a vital role in evaluating the effectiveness of L&D technology platforms. By collecting relevant data from the platform, including user engagement, assessment scores, course completion rates, and user feedback, organizations can ensure data accuracy, consistency, and timeliness. Furthermore, when this data is analyzed, it provides organizations with insights into user behaviors, patterns, and trends that help assess how the platform impacts learning outcomes and user satisfaction.

ROI and cost analysis:

To determine the financial impact of the learning technology platform and assessing its overall effectiveness, organizations must conduct ROI and cost analysis. ROI analysis helps assess whether the learning gains or cost reductions justify the investment. It is particularly useful in comparing the benefits, such as improved learning outcomes or cost savings, to the costs of implementing and maintaining the platform. Cost analysis on the other hand helps analyze the total cost of ownership, considering implementation, licensing, maintenance, and staff training expenses. It also helps identify the areas where cost-efficiency can be improved.


Thinking like a business, understanding the technologies available, and remembering the human factor all make up a strong measurement strategy for enhancing performance outcomes. New technologies like AI, machine learning, and predictive intelligence provide insights into current data and future scenarios. Remember to consider all aspects of measuring learning effectiveness; this will help to build a productive roadmap toward learning excellence.

Read More:

Related Insights