Achievement Goal Orientation Profiles and Performance in a Programming MOOC

: Kukka-Maaria Polso, Heta Tuominen, Arto Hellas, Petri Ihantola

: Michail Giannakos, Guttorm Sindre

: Annual Conference on Innovation & Technology in Computer Science Education

: 2020

: ITiCSE '20: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education

: 411

: 417

: 978-1-4503-6874-2

DOI: https://doi.org/10.1145/3341525.3387398

It has been suggested that performance goals focused on appearing talented (appearance goals) and those focused on outperforming others (normative goals) have different consequences, for example, regarding performance. Accordingly, applying this distinction into appearance and normative goals alongside mastery goals, this study explores what kinds of achievement goal orientation profiles are identified among over 2000 students participating in an introductory programming MOOC. Using Two-Step cluster analysis, five distinct motivational profiles are identified. Course performance and demographics of students with different goal orientation profiles are mostly similar. Students with Combined Mastery and Performance Goals perform slightly better than students with Low Goals. The observations are largely in line with previous studies conducted in different contexts. The differentiation of appearance and normative performance goals seemed to yield meaningful motivational profiles, but further studies are needed to establish their relevance and investigate whether this information can be used to improve teaching.