O
Otto Seppälä
Researcher at Aalto University
Publications - 31
Citations - 1603
Otto Seppälä is an academic researcher from Aalto University. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 10, co-authored 27 publications receiving 1429 citations. Previous affiliations of Otto Seppälä include Helsinki University of Technology.
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Proceedings ArticleDOI
Review of recent systems for automatic assessment of programming assignments
TL;DR: It is stated that too many new systems are developed, but also acknowledge the current reasons for the phenomenon, and encourages opening up the existing systems and joining efforts on developing those further.
Journal ArticleDOI
A multi-national study of reading and tracing skills in novice programmers
Raymond Lister,Elizabeth S. Adams,Sue Fitzgerald,William Fone,John Hamer,Morten Lindholm,Robert McCartney,Jan Erik Moström,Kate Sanders,Otto Seppälä,Beth Simon,Lynda Thomas +11 more
TL;DR: A study by a ITiCSE 2001 working group established that many students do not know how to program at the conclusion of their introductory courses, and studied the alternative explanation, suggesting that such students have a fragile grasp of skills that are a prerequisite for problem-solving.
Journal ArticleDOI
Visual Algorithm Simulation Exercise System with Automatic Assessment: TRAKLA2
TL;DR: A new framework, TRAKLA2, for building interactive algorithm simulation exercises, which supports automatic generation of model solutions as algorithm animations and the logging of statistical data about the interaction process resulting as students' exercises.
Journal ArticleDOI
Naturally occurring data as research instrument: analyzing examination responses to study the novice programmer
Raymond Lister,Tony Clear,Simon,Dennis Bouvier,Paul Carter,Anna Eckerdal,Jana Jackova,Mike Lopez,Robert McCartney,Phil Robbins,Otto Seppälä,Errol Thompson +11 more
TL;DR: This ITiCSE working group report presents the most recent step in the BRACElet project, which includes replication of earlier analysis using a far broader pool of naturally occurring data, refinement of the SOLO taxonomy in code-explaining questions, extension of the taxonomy to code-writing questions, and exploration of a further theoretical basis for work that until now has been primarily empirical.
Proceedings ArticleDOI
Do we know how difficult the rainfall problem is
TL;DR: It is suggested that the Rainfall Problem is not necessarily overwhelmingly difficult: Success rates vary and some reasonably good results have been achieved under multiple programming paradigms.