Modeling Students’ Motivational Profile for Learning in Vocational Higher Education

The Abilities for Professional Learning (APL) questionnaire (Ruohotie, 2000b) was designed to measure 15 factors of motivation and learning strategies. This chapter examines the validity of six factors of the motivational part of the APL self-report instrument. The next chapter will focus on the development and validation of instruments to assess strategic skills in learning. We agree with Boekaerts (2001, 18) that the problem with extensively used self-report questionnaires is that they do not provide insight into students’ personal motivation traits in actual classroom learning situations as they are in most cases developed for measuring traits of domainspecific motivation. However, there is a shift in the way the research methodology is applied in the context of motivational research as there is growing number of moments when the students are not present simultaneously in the classroom where it is easiest to conduct the observation of general motivation traits. We refer here to computer-supported collaborative learning (CSCL) and other forms of distance learning exercised in the virtual university studies. Järvelä and Niemivirta (2001, 108) approach this issue by challenging the researchers within the framework of computersupported collaboration and learning to focus on both learner’s intrinsic and extrinsic motivational processes. In a series of empirical case studies they approach this challenge with multi-faceted research methodology using questionnaires, videotaping of students’ learning activity, stimulated recall-interviews, and repeated process-oriented interviews (Järvelä & Niemivirta, 2001, 115-122). It is clear that in order to study complex phenomenon such as student motivation, both multifaceted theoretical and methodological approach is required. Unfortunately, severe limitations for data collection exist in the context of virtual university learning. Teacher or tutor has few face to face discussions with the students. In fact, as an expert in certain area, she has to deal each time with a new group of attendees’. Furthermore, study processes including collaborative actions, such as group works, are conducted through the distance learning platforms. We believe that as the volume in virtual studies increases, the personal face to face tutoring time for each student decreases and leads to situation where the guidance is conducted via syncronous (chat) or asynchronous (email) tools. In this hectic situation the teacher or tutor has to make good use of all the available information channels in order to understand the personal needs of each student. Nokelainen and Tirri (2002) discuss in their article how to utilize computerized selfrating instruments in the context of virtual university studies.