UDIT 2019 Program

UDIT program tirsdag 26. november
0900-1000
Åpning
Invitert foredrag NOKOBIT
1030 - 1200
Eksamen og evaluering
Chair: Hugo Nordseth, Nord universitet
Torstein Strømme: Pass/fail grading and educational practices in Computer Science
Hans Georg Schaathun: Den tause kunnskapen i IT-studia
Guttorm Sindre: Analyse av oppgaver og oppgavesjangre i en digital eksamen i innledende programmering
1300-1400
Invitert foredrag UDIT
Professor Alf Inge Wang, NTNU
1415-1600
Digital kompetanse
Chair: Guttorm Sindre, NTNU
Gunhild Lundberg and Leif Erik Opland: Perceived employability in online IT education
Klaudia Carcani, Camilla Gjellebæk, Susanne Koch Stigberg: Participatory design as an approach for work-integrated learning of digital competencies
Berglind F. Smaradottir and Martin W. Gerdes: Evaluering av pedagogiske metoder og organisering på et masterkurs i teknologiforståelse for helseinformatikk (Plakat)
Kirsti E. Berntsen, Grethe Sandstrak, Frode Vågen and Lars Gunnar Landrø: Lessons learned from an interdisciplinary innovation camp for bachelor students – Biomedical laboratory science & computer engineering (Plakat)
1600-1615
Pause
1615-1745
Plenary panel session: How should IT education address sustainability and climate change?
UDIT program onsdag 27. november
0845-0900
Åpning
0900-1000
Invitert foredrag NIK
Davide Roverso
Chief Analytics Officer, eSmart Systems
1030 - 1200
Undervisningsmetoder
Chair: Kirsti E. Berntsen, NTNU
Madeleine Lorås and Hallvard Trætteberg: Investigating students’ journey through a computer science program using exam data: three new approaches
Abdullah Bahmani and Rune Hjelsvold: Recorded lectures in multi-campus education: A cross-case analysis
Per Lauvås and Tomas Sandnes: Mandatory coursework in higher Norwegian IT education
1300-1400
Invitert foredrag NISK
1415-1600
Programmering
Chair: Erlend Tøssebro, UiS
Ragnhild Aalvik and Jaakko Järvi: VisAST: Generic AST visualiser for software language education
Ragnhild Kobro Runde, Kristin Marie Rørnes and Siri Moe Jensen: Students’ mental models of references in Python