Learner Analysis

Learner analysis is a crucial component of the course design process, where educators or instructional designers gather and analyze data about the learners' characteristics to inform the development and delivery of educational content. The purpose of conducting a learner analysis is to tailor the educational experience to meet the unique needs, abilities, and preferences of the learner group, thereby enhancing learning outcomes and overall course effectiveness.

Why?

Understanding the unique characteristics of your learners will help you design a course to leverage their intrinsic motivations. Additionally, identifying characteristics of a cohort or group can offer additional opportunities to engage your learners on that common ground.

For example, an executive MBA program may expect learners with some degree of professional experience, while learners in an undergraduate course may not have any relevant work history.

Here are the key aspects typically examined during a learner analysis:

1. Demographic Information

This includes age, gender, cultural and linguistic background, and possibly socio-economic status. Understanding these factors helps in designing content that is culturally and developmentally appropriate.

2. Educational Background

Knowing the learners' prior educational experiences, including their highest level of education, subject matter expertise, and familiarity with the course content, is vital. This information allows the educator to adjust the complexity and depth of the material to suit the learners' starting knowledge levels.

3. Learning Styles and Preferences

Learners have different preferences on how they receive and process information, which can be influenced by their sensory modalities (visual, auditory, kinesthetic, etc.). Understanding these styles helps in creating diversified content that can cater to varied preferences.

4. Motivation and Attitudes

Analyzing why learners are taking the course and what they hope to achieve can provide insights into their motivation levels. Additionally, their attitudes towards the subject matter, online learning, and self-directed learning are important to consider for engagement strategies.

5. Skills and Competencies

Identifying existing skills and competencies helps in setting the starting point of the instruction. This includes technical skills, such as proficiency with digital tools necessary for the course, or specific professional skills related to the course content.

6. Cognitive and Physical Abilities

Understanding any cognitive limitations (such as attention disorders) or physical disabilities (such as visual or hearing impairments) is crucial for ensuring accessibility and designing accommodations like extended time for tests, subtitles for videos, or alternative content formats.

7. Learning Goals and Objectives

Analyzing what learners aim to achieve from the course enables educators to align the course objectives with learners’ personal or professional goals, enhancing relevance and motivation.

8. Environmental Factors

Factors such as learners’ access to technology, learning environment, and time availability can affect their engagement and success in the course. These factors are particularly important in distance learning settings.

 

Conducting a learner analysis typically involves collecting data through surveys, interviews, pre-tests, and reviewing existing data on learner performance and feedback from previous courses. The findings from a learner analysis are used to make informed decisions about course design, instructional strategies, content delivery, and assessment methods, ensuring they are adapted to the needs and contexts of the learner group.

Instructions for Use:

• Distribute this worksheet to learners prior to the start of the course.
• Encourage detailed responses to understand the diverse needs and contexts of the learners.
• Analyze the collected data to adapt teaching strategies, course materials, and assessment methods to better suit the learner profiles.

This worksheet not only helps in gathering essential information but also ensures that the educational delivery is aligned with the learners' needs and circumstances, thereby enhancing their learning experience and outcomes.

You can access the Learner Analysis Worksheet on the right side of this Knowledge Base article in a word document that can be downloaded. 

Supplemental Information

For further reading, check out the following information on Learner Design and Analysis.

1. “Learning Design for Future Higher Education”:

   • This research paper provides expert insights based on empirical observations of teaching and assessment practices. It focuses on effective didactic strategies and addresses the digitization of higher education. The goal is to formulate specific learning design recommendations for the immediate future.
   • Access the full paper here: Learning Design for Future Higher Education

2. Ding’s Learning Design Library:

   • Ding has curated a library of articles, videos, books, and links related to learning design. It covers six core pillars: Empathy, Curriculum, Inclusivity, Technology, Facilitation, and Community.
   • Explore the library here: Ding’s Learning Design Library

References

Adams Becker, S., Caswell, T., Jensen, M., Ulrich, G., and Wray, E. (2014). Online Course Design Guide. (n.d.). Cambridge, Massachusetts: Massachusetts Institute of Technology. Retrieved https://edtechbooks.org/-Snvzp

Cennamo, K., & Kalk, D. (2019). Real World Instructional Design: An interative approach to designing learning experiences (2nd ed). New York, NY. Routledge.

Fink, L. D. (2013). Creating significant learning experiences: An integrated approach to designing college courses. San Francisco, CA: John Wiley & Sons.

Fulgencio, J., & Tutaleni, I. Conducting a Learner Analysis. https://edtechbooks.s3.us-west-2.amazonaws.com/pdfs/383/6283.pdf

McDonald, J.K. & West, R. E. (Eds.) (2021). Design for learning: Principles, processes, and praxis (1st ed.). EdTech Books. Retrieved from https://edtechbooks.org/id/

Saxena, M. (2011). Learner analysis framework for globalized e-learning: A case study. The International Review of Research in Open and Distributed Learning, 12(5), 93–107. https://doi.org/10.19173/irrodl.v12i5.954