In a previous blog, I gave an overview of the Western Governors University instructional design master's degree program and explained why I enrolled in and completed it. Learning Technology was the first class in the degree curriculum, but it is not the first class I summarized, as technology is not the most important part of instructional design work. I would guess this class was placed first in the curriculum because it was short and could provide a quick win for students to finish before diving into the more substantial foundations classes.
As a competency-based program, these are the competencies students need to demonstrate to pass this class:
Rather than focusing on any specific software, this course teaches learners to research emerging learning technologies and analyze how these technologies are changing current teaching and learning practices. The class also covers the evaluation of learning technologies to help learners achieve their learning goals. It discusses how to use technology to accommodate learner differences for accessibility. Implementing technology safely, legally, and ethically is a related topic in this course. Finally, it covers the general types of learning analytics that technologies generate and how the data can be used to improve the learner experience and outcomes.
Course topics:1. Analyzing the Trends and Impacts of Emerging Technologies (click to scroll down to this section)
2. Evaluating Learning Technologies (click to scroll down to this section)
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This lesson discussed how to identify emerging learning technologies, including a brief history of their use to support learning.
'Learning technology' describes the communication, information, and technological tools used to enhance learning, teaching, and assessment.
The lesson also emphasized that no technology can guarantee effective learning; good teaching skills and well-developed instructional design are always necessary. Success depends on how effectively instructional designers and trainers/teachers/facilitators focus on clear objectives, learner needs, and practical application in professional settings.
Some of the ways technology can offer opportunities for adults to upskill:
virtual simulations
self-paced courses
AI-driven learning platforms
New technologies can be used in many ways, such as:
• creating curricula based on real-world problems
• providing scaffolds and tools to enhance learning
• giving students and teachers more opportunities for feedback, reflection, and revision
• building local and global communities (teachers, trainers, researchers, and more)
• expanding opportunities for teacher education
Characteristics of emerging learning technologies and outdated technologies were also compared and discussed.
A trend is "the general movement in a particular direction of something that is developing or changing, or the way people are behaving."
Emerging trends in learning technology:
Virtual reality (VR) and augmented reality (AR) to give more hands-on experiences
Artificial intelligence/machine learning to automate grading, provide feedback, monitor student progress, and identify struggling students
Adaptive learning courseware platforms that create more personalized, data-driven learning experiences based on a student's current level of mastery.
Additional trends:
Open Education Resources
Where to find information about emerging trends:
Professional Learning Networks: informal communities of educators who share ideas and resources about teaching and learning.
These can help you identiy trends by:
National and International Organizations: These websites are places to find information, including articles, blog posts, networking opportunities, professional development resources, and webinars.
This lesson discussed how learning technologies change both teaching and learning practices, as well as the issues of equity, inclusion, and barriers in using technology.
"Equity is achieved when systemic, institutional, and historical barriers based on race, gender, sexual orientation, and other identities are dismantled and no longer determine socioeconomic, educational, and health outcomes."
Technology can expand access to resources, but it can also create barriers to equity and inclusion in education. Instructional designers need to address equity and inclusion when considering the use of technology to future-proof the experience.
Artificial Intelligence (AI) and Machine Learning Education Applications
Open Educational Resources (OER)
Extended Reality (XR) Technologies
Adaptive Learning Technologies
Games and Simulations
Others include
This chapter provided a brief history of learning management systems (LMS), including a discussion of common stakeholders and the differences between an LMS and a content management system (CMS).
An LMS is a centralized platform that facilitates the delivery of educational content, such as lessons, assignments, activities, and discussions.
This lesson also gave an overview of theoretical models and technologies that organizations use to facilitate learning, including how technology integration and delivery depend on both the type of content and the learning goals.
This lesson discussed how effective teaching and learning align on three major components:
1. Clearly articulated learning goals
2. Instructional strategies
3. Activities to help learners achieve these goals.
Learning technologies should be carefully chosen to enhance and support your particular learning goals. The software should address a need or challenge, not be used simply because it is available.
Learning technologies can promote deep learning through authentic, immersive, and adaptive learning experiences such as simulations. Deeper learning competencies include critical thinking, communication, and problem-solving. Technology can tailor instruction to meet individual student needs, and support learners in building foundational skills while encouraging engagement and creativity.
Instead of guessing at the effects of including or removing technology in the learning experience, you should measure its impact on the goals and intended outcomes.
Some goal-related benefits of technology are:
Flexibility
Personalized support
A customizable learning environment
The ability to reach learners worldwide at any time of day
Motivation from more personalized and relevant learning experiences.
When choosing and implementing technology, first identify the metrics for success and set up a way to track them over time.
Learners have many differences, including:
degrees of self-efficacy
motivation
interest
goals
attention
prior knowledge or personal experiences
feelings of belonging
Learner variability is how people differ in the way they learn information. When designing learning experiences, remember learner variability and consider how learning technologies can provide the flexibility and support needed to meet a diverse set of needs and learning differences.
The lesson discussed the debate over whether to use the term "learning disability" or "learning difference," and it preferred the term learning differences to encourage a focus on strengths, rather than just challenges.
Universal Design for Learning principles framework emphasizes the creation and implementation of customizable tools designed to serve a range of diverse learners by:
ensuring individuals can access content
engaging with learning activities
expressing their knowledge in ways that align with their abilities and preferences.
This includes assistive technologies such as text-to-speech software, closed captioning, and digital note-taking tools.
Instructional designers need to be aware of the challenges and risks associated with learning technologies, including safety, legal, and ethical implications. There is overlap among these three categories regarding being responsible users and consumers in the digital world.
Learning experience designers must know how to protect their own safety and ensure learners' security when interacting with technology.
They also need to understand the legal considerations that affect education and professional learning, including data privacy, data security, accessibility, and intellectual property regulations. Compliance with accessibility standards and the protection of learner data are critical.
Ethical issues that learning designers need to consider include data access, protection of personal information, accessibility, data ownership, and potential misinterpretation.
Safety concerns are increasing exponentially, including privacy and data protection, as well as phishing and ransomware attacks. Cyberbullying can also be a concern when using online learning platforms with students.
Learning designers need to consider ethical issues related to technology to minimize privacy risks and create an equitable environment for learners by creating policies and procedures for data collection, storage, and use. This includes issues related to copyright, accessibility, and violation of identifiable information.
An LMS or other technology can collect learner data and analyze and interpret trends and patterns to make decisions or predictions that benefit learners and organizations. Various data types can be collected within learning management systems, including learners' engagement and interactions with technology.
Learning designers should study how to present this data in a meaningful, easily readable, and understandable way for the audience. Student-facing analytic dashboards can also help students track and improve their learning practices.
This data can also predict and inform students' learning needs, helping instructors improve teaching and training practices. You can identify historical patterns and trends in data to inform student interventions and future improvements to courses or training in the learning environment.
Specific goals include:
Encouraging learners to take an active role directing their learning
Identifying learners at risk of not achieving goals
Investigating factors impacting completion or success rates
Guiding learning experience improvement decisions
Planning is necessary to identify which types of data you want to collect and why.
Types of analytics:
Descriptive analytics: Previously collected data, used to understand what happened in the past.
Diagnostic analytics: A deeper look into descriptive data, used to understand why something happened
Predictive analytics: Looking at historical data and using statistical models/algorithms to find patterns and make predictions
Prescriptive analytics: Using the information from predictive analysis to suggest actions based on emerging patterns.
Thanks for reading this overview of the Learning Technology class! The next blog will be about the class for Designing E-Learning Experiences for Adults.