Brain-based programming continued: Effective teaching in programming courses

After the promising results of the pilot phase of "Brain-based Programming", a new teaching concept for introductory programming courses based on neurodidactical principles, the empirical study continues this year in three groups. The results obtained so far in the current semester at our university are promising, too: In the first exams the students of the experimental groups achieved significantly better than their colleagues in the traditional courses and female students seem to benefit even more of the new concept. This paper describes the basics of the teaching concept "Brain-based Programming" and reports on the empirical results regarding the positive impact this concept on the learning outcomes (Cohen's d = 0.42) as well as the students' and teachers' feedback.

[1]  John Hall.  Neuroscience and Education A review of the contribution of brain science to teaching and learning , 2005 .

[2]  Valda Miller,et al.  Peer Assisted Study Sessions (PASS) in first year chemistry and statistics courses: insights and evaluations , 2012 .

[3]  Burçin Gökkurt,et al.  The Effects of Learning Together Technique Which is based on Cooperative Learning on Students’ Achieevement in Mathematics Class , 2012 .

[4]  U. Goswami.  Neuroscience and education: from research to practice? , 2006, Nature Reviews Neuroscience.

[5]  S. Derry,et al.  Learning from Examples: Instructional Principles from the Worked Examples Research , 2000 .

[6]  Patricia Henley,et al.  Boys and Girls Learn Differently!: A Guide for Teachers and Parents , 2001 .

[7]  Cary J. Roseth,et al.  Promoting early adolescents' achievement and peer relationships: the effects of cooperative, competitive, and individualistic goal structures. , 2008, Psychological bulletin.

[8]  Alfred Bork,et al.  Multimedia in Learning , 2001 .

[9]  Ivan Kalas,et al.  Informatics as a Contribution to the Modern Constructivist Education , 2008, ISSEP.

[10]  Scotty D. Craig,et al.  The Deep-Level-Reasoning-Question Effect: The Role of Dialogue and Deep-Level-Reasoning Questions During Vicarious Learning , 2006 .

[11]  Eric R. Jensen.  Brain-Based Learning: The New Paradigm of Teaching , 2008 .

[12]  Richard E. Mayer,et al.  Multimedia Learning , 2001, Visible Learning Guide to Student Achievement.

[13]  Gerhard Roth,et al.  Bildung braucht Persönlichkeit : wie lernen gelingt , 2015 .

[14]  Geoffrey Caine,et al.  12 brain/mind learning principles in action : developing executive functions of the human brain , 2009 .

[15]  Thomas Vikberg,et al.  Massive increase in eager TAs: experiences from extreme apprenticeship-based CS1 , 2013, ITiCSE '13.

[16]  Mehmet Gultekin,et al.  The Effects of Brain-Based Learning on Academic Achievement andRetention of Knowledge in Science Course* , 2008 .

[17]  J. Geake,et al.  Cognitive Neuroscience: implications for education? , 2003 .

[18]  H. W. Reese,et al.  The Learning-by-Doing Principle , 2011 .

[19]  Gerhard Roth,et al.  Warum sind Lehren und Lernen so schwierig , 2003 .

[20]  Beth Simon,et al.  Halving fail rates using peer instruction: a study of four computer science courses , 2013, SIGCSE '13.

[21]  M. Carter.  Visible learning: a synthesis of over 800 meta‐analyses relating to achievement , 2009 .

[22]  Alexander Renkl,et al.  Learning From Examples: Fostering Self-Explanations in Computer-Based Learning Environments , 2002, Interact. Learn. Environ..

[23]  Barbara Sabitzer,et al.  Brain-based Programming , 2013, 2013 IEEE Frontiers in Education Conference (FIE).

[24]  Colleen M. Lewis.  Is pair programming more effective than other forms of collaboration for young students? , 2011, Comput. Sci. Educ..

[25]  David A Sousa,et al.  How the Brain Learns , 2000 .

[26]  Emilia Mendes,et al.  Empirical Studies of Pair Programming for CS/SE Teaching in Higher Education: A Systematic Literature Review , 2011, IEEE Transactions on Software Engineering.

[27]  Naomi J. Aldrich,et al.  Does Discovery-Based Instruction Enhance Learning?. , 2011 .