Oct 11, 2011

How can researchers' measure students' motivation, volition and attitude toward technology?

Or we can re-phase that sentence to: how can researchers measure students' motivation, volition and attitude of a technology-integrated course?

The article Sarah provided is very interesting. To me, it is obviously a very "learning science" article. It followed a very traditional quantitative research design. It is quasi-experimental, which means the participants are not randomly sampled, but researchers randomly assigned the participants to two treatment groups and also randomly assigned the teachers to different treatment groups. Independent variable is whether the group receive MVEM or not. There are 4 dependent variables to be measured: students' motivation, students' volition, students' attitude toward technology, and students' performance score. One-way ANOVA is used to determine if variance of homogeneity is fulfilled during the pre-test and if there is are significant results of difference two treatment groups in regards of four different dependent variables.  A abbreviated survey was designed to apply in the middle of the courses to measure the motivation and volition levels of individual student in order to provide appropriate instructional message via email.

Unfortunately the results of students' motivation and performance didn't meet the researchers' expectation that had significant different after the MVEM, but it has the positive effect on students' volition and attitude.   The researchers explained that could be attribute to students already had high motivation from the beginning of the class. The authors also  estimated that students will spend 30 mins. to read the message they send,  optimistically assumed that the reading time will be increased by 2.5 hrs if it is a semester-long study. How did they estimate the time? Will students' motivation, volition and attitude be increased linearly regarding time increases?

Another interesting point that brought by the researcher in the implication section is they way they encourage practitioners (online instructor)  to apply MVEM to enhance students' motivation, volition and attitude toward technology integration. They stated:
"An outside observer might note that MVEM seem promising but simply are not feasible due to the time it would take to create customized MVEM for each student. However, it would not necessarily require a great time commitment on the part of instructors. Audience analysis is something that all good instructors do anyway" (p.107).
They even proposed to develop an automated system to recognize the volitional and motivational patterns of students. I strongly disagree the way they want to interact with students based on my personal teaching philosophy. I don't think students' reflection can be easily measured and analyzed by the computer. To provide appropriate feedbacks and formative assessment has always been a job of instructors and it is always time-consuming. Nonetheless, the research was framed by positivism paradigm. To me, it is cognitivist even behaviorist, which means, everything can be measured and controlled. Students' learning can be stimulated by instructional messages that researchers provided. You give the message, they received then they should react with proper behavior. It's a little pity they didn't collect any qualitative data, such as student' essay, which may become evidence to help triangulate their results.

At the end of the reflection, I just want to mention ARCS model, which I believe I've read it in Reiser's book. However, the book is in my boxes on the way to Houston so I don't have a chance to check it out. Here I attach a diagram from the Internet, which I think will explain the model more explicitly by dividing it into several steps:

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