Browsing by Author "Polso, Kukka-Maaria"

Aims. In the context of computing education, the vast majority of prior research examining achievement goal orientations has been conducted using variable-centred methods. In order to deepen understanding of the student population and achievement motivation, this Master’s Thesis employed person-oriented perspectives. The interplay of different goal orientations was explored by identifying prevalent motivational profiles and investigating profile differences in performance. Normative and appearance performance goals were handled as separate clustering variables in addition to mastery goals for the first time. Methods. The participants were 2059 introductory programming MOOC students. Data were collected by a questionnaire and from automatically assessed programming assignments and final exam. An exploratory factor analysis (EFA) was conducted for the achievement goal orientation items to examine the factor structure. Using TwoStep cluster analysis, the students were classified into clusters according to their achievement goal orientations. Cross tabulations and analyses of variance (ANOVA) were conducted to investigate profile characteristics and differences in performance. Results and Conclusions. Five distinct achievement goal orientation profiles were identified: Approach-Oriented (31.2%), Performance-Oriented (18.9%), Combined Mastery and Performance Goals (18.0%), Low Goals (17.6.%) and Mastery-Oriented (14.3.%). Students with Combined Mastery and Performance Goals performed significantly better than students with Low Goals regarding two metrics. Consistent with previous findings, the results highlight the positive link between multiple goal pursuit and performance. Further studies are needed to investigate motivational profiles in relation to other educational outcomes in the context of computing education. This kind of knowledge is valuable for designing interventions and new courses. The article ‘Achievement Goal Orientation Profiles and Performance in a Programming MOOC’, which is based on the present thesis, will be presented at ITiCSE 2020 (Conference on Innovation and Technology in Computer Science Education) conference and published in conference proceedings.