How People Learn: An Evidence-Based Approach

We recently released “The Science of Learning,” a report that summarizes the cognitive science related to how students learn. The principles in this post are drawn from that report.


Women Students and Those with Lower GPAs Benefit Most From ‘Flipped Classroom’ Teaching

results of a five-year study suggesting that student gains are related to working with course material in a more timely and accurate manner. Students avoided “cramming” for tests and instead prepared ahead for classes and exams, allowing them to get higher grades. Further, the researchers saw more pronounced positive effects for female students and those who came in with a lower grade point average.

How To Bring the Joy Back Into Learning

Rantala and Määttä’s recipe for joy includes support for collaboration, respect for effortful struggle, and promotion of autonomy. Here are their ingredients, in addition to what the literature says:

1. Remove all labels.

labelling “joy” automatically takes some of the joy out of learning.

2. Savour successes and make peace with failures.

“A teacher should favour such teaching methods that enable the achievement of little intervening goals as a part of a greater learning process


Research-Based Design of the First Weeks of CS1

Juha Sorva, Otto Seppälä

November 2014

Koli Calling ’14: Proceedings of the 14th Koli Calling International Conference on Computing Education Research


On the basis of cognitive load theory, theoretical models of instructional design, and empirical ndings from computing education research, we propose three independent but com- patible and complementary frameworks that can be used in introductory programming education. Motivate{isolate{ practice{integrate is a framework that marries project-driven learning to careful management of cognitive load through the selecti

Visual program simulation in introductory programming education

Visual program simulation in introductory programming education

Sorva, Juha


Many variants of the taxonomy have been proposed in the literature. An influential variant – which I will refer to as the revised Bloom’s taxonomy – was defined by an interdisciplinary group of experts led by Anderson and Krathwohl (Anderson et al., 2001)….

Predictors of success in a first programming course

Predictors of success in a first programming course

Authors: Simon University of Newcastle, Australia Sally Fincher University of Kent, UK Anthony Robins University of Otago, NZ Bob Baker University of New South Wales, Australia Ilona Box University of Technology Sydney, Australia Quintin Cutts University of Glasgow, UK Michael de Raadt University of Southern Queensland, Australia Patricia Haden Otago Polytechnic, NZ John Hamer University of Auckland, NZ Margaret Hamilton RMIT University, Australia

A multi-national study of reading and tracing skills in novice programmers

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

December 2004 ITiCSE-WGR ’04: Working group reports from ITiCSE on Innovation and technology in computer science education

A study by a ITiCSE 2001 working group (“the McCracken Group”) established that many students do not know how to program at the conclusion of their introductory courses.

Report on the final BRACElet workshop

Report on the final BRACElet workshop

Journal of Applied Computing and Information Technology ISSN 2230-4398, Volume 15, Issue 1, 2011

a list of the core findings related to novices learning to program.

  • Academics actively seek to abstract beyond the concrete code. Whereas the novices tended not to abstract, they “could not see the forest for the trees” (Lister et al., 2006).
  • A student’s degree of mastery of code tracing tasks indicates their readiness to be able to reason about code.

A multi-national, multi- institutional study of assessment of programming skills of first-year CS students

A multi-national, multi-institutional study of assessment of programming skills of first-year CS students

Michael McCracken, Vicki Almstrum, Danny Diaz, Mark Guzdial, Dianne Hagan, Yifat Ben-David Kolikant, Cary Laxer, Lynda Thomas, Ian Utting, Tadeusz Wilusz

December 2001 SIGCSE Bulletin , Volume 33 Issue 4

we expect computing students to learn to successfully follow these steps:

1. Abstract the problem from its description

2. Generate sub-problems

3. Transform sub-problems into sub-solutions

4. Re-compose the sub-solutions into a working program



Subscribe to RSS - Research