W3: Changes in Student Motivation During Online Learning

In Changes In Student Motivation During Online Learning, Theodore Frick and Kyong-Jee Kim explore the factors that commonly affect student motivation in self-directed e-learning (SDEL) environments.

Review of the Literature
The article begins with a literature review of online learning which has thus far concentrated on evaluating motivation in online courses. Frick and Kim use this review to create a context on which to begin their own study on motivation in SDEL.

The main differences between online learning and SDEL are:

1. Online learning is typically more similar to traditional classroom paradigms with an instructor and peer collaboration just in an online context (like the classes in IU's IST program). Where as SDEL offers limited to no student to student and/or teacher to student interaction.
2. Online learning typically has more rigid parameters about pacing (because it is usually following a semester or other 3rd party time table). However, SDEL courses are usually self-paced and have little to no time constraints for completion.

Frick and Kim divide the factors affecting motivation in the literature into three main categories:

1. Internal - Internal factors are explained as those factors that relate to how a learner feels about the learning. For example, do they feel in control? Do they feel it's relevant? Is the design clear and professional. Or is it too busy and confusing to navigate? The theory is basically that how the student feels about the instruction/training directly affects their motivation. Many of these internal factors can be linked back to Keller's ARCS model of motivation (attention, relevance, confidence, and satisfaction), however, there are other factors as well, such as whether the design is clean, professional, and easy to navigate or not; whether the tasks are within their zone of proximal development (that which they are capable of accomplishing with limited support); whether the instruction has the right balance of academic learning time (ALT) (a ratio to describe how long is spent on activities as define by their complexity and ease of solution), and others.
2. External - External factors are the environmental factors that affect motivation. The two main ones listed being technical support and organizational support. Students reported higher satisfaction with a course if they felt they got the proper training and received positive support when they had difficulties. The literature also briefly mentions that feeling overwhelmed between a school/work/home balance is also an external factor.
3. Personal - Personal factors are all of the personal learner variables that affect one's motivation. For example, the learner's temperament, age, gender, and prior knowledge and experience when they begin the class. There is conflicting opinion in the literature on whether or not learning styles substantially affect learner motivation in online learning situations.

Summary of Study of Motivational Factors in SDEL

Using the knowledge they gained from reviewing the literature, Frick and Kim began their own study of factors affecting motivation in SDEL learning environments.

The research questions (p. 7):

• Which factors best predict learner motivation in the beginning, during, and end of self-directed e-learning (SDEL)?
• Does learner motivation change as he or she goes through instruction in SDEL?
• What factors are related to learner motivational change during SDEL?

Method

The context

Frick and Kim emailed 800 learners at a major US e-learning company which provides SDEL courses for personal professional development, cooperations, and universities. The course formats are "stand-alone, typically 6-8 hours long, self-paced instruction delivered via the web" (p. 8) that focus on information technology skills and "soft skills development (e.g. coaching skills, consulting skills)" (p. 8). These courses typically have no instructor, but learners do have the option of paying an extra fee if they want instructional support added to their course.

Participants

Frick and Kim sought out 400 undergrad and graduate students and 400 working professionals of various backgrounds. 368 responded with an almost equal distribution of students and employees and almost equal distribution of gender. The greatest age population was the 25-34 range (42%), with almost an equal distribution of 24 & younger, 35-44, and 45 & up. A good majority of respondents reported using the internet more than 20 hours a week and 3-5 software programs on a regular basis (so they are pretty familiar with technology).

The Research Instrument

Frick and Kim gathered quantitative data using a self-reporting questionnaire consisting of 59 multiple choice (Likert scale) questions and one open ended question about their general feelings on SDEL.

Data Collection and Analysis

The questionnaire was sent out to participants via listservs and email and the researchers received a 46% response rate. All responses were kept anonymous.

Results

Researchers found that the best factors in predicting learner motivation was:

1. Perceived relevance: How the learner perceived relevance affects their starting motivation, which in turn affects the during motivation, and finally the overall positive change in learner motivation throughout the course.
2. Reported technology competence: The number of software programs used on a regular basis and time spent on the internet each week directly affects learner motivation.

It seemed that the other factors were not statistically relevant for predicting learner motivation throughout and at the end of the instruction.

Additional Comments:

I feel like I personally relate more to the online learning scenarios as a student. And since starting my grad certificate in the IST program, I have definitely experienced some of the factors found to negatively affect motivation in online learning (and I concur in their affect). For example on pg. 5, it is discussed that a poorly designed website and breaks in technology can lead to learner frustration, I circled both of those, because I've had instances where the Oncourse links were so convoluted, I had trouble keeping track of what assignments were due when. And the different links weren't consistent with one another. That is really frustrating! Also, one class I took, nearly once a week one of my classmates or I had to point out to the instructor that there was a broken link to our resources. This often led to a delay of retrieving the needed resource, adding frustration.

I also doubled circled the point about the challenges adult learners face trying to strike a balance between work, home, and course demands. I was glad to see that this is something that designers are (theoretically) taking into consideration for us non-traditional students.

But perhaps my biggest circle (underline and asterix!) was on p 7 while distinguishing between the online learning and SDEL: "In SDEL, it may not be easy to find student peers for interaction - whether positive or for commiseration." I know that I am a talker. I like to talk about my problems (some might say overtalk them). And I can think of at least one class where being able to commiserate with my peers about our frustrations about the class, the instructor, and the disorganization of it all is what kept me going in that class. I have never taken an SDEL course, but I can imagine this would be a major factor for me if I did, which it seems is also an issue with SDEL learners as exemplified by their responses in the I don't want to learn by myself items (p. 11).