Factors Affecting Learning of Vector Math from Computer-Based Practice: Feedback Complexity and Prior Knowledge.

In experiments including over 450 university-level students, we studied the effectiveness and time efficiency of several levels of feedback complexity in simple, computer-based training utilizing static question sequences. The learning domain was simple vector math, an essential skill in introductory physics. In a unique full factorial design, we studied the relative effects of “knowledge of correct response” feedback and “elaborated feedback” (i.e., a general explanation) both separately and together. A number of other factors were analyzed, including training time, physics course grade, prior knowledge of vector math, and student beliefs about both their proficiency in and the importance of vector math. We hypothesize a simple model predicting how the effectiveness of feedback depends on prior knowledge, and the results confirm this knowledge-by-treatment interaction. Most notably, elaborated feedback is the most effective feedback, especially for students with low prior knowledge and low course grade. In contrast, knowledge of correct response feedback was less effective for low-performing students, and including both kinds of feedback did not significantly improve performance compared to elaborated feedback alone. Further, while elaborated feedback resulted in higher scores, the learning rate was at best only marginally higher because the training time was slightly longer. Training time data revealed that students spent significantly more time on the elaborated feedback after answering a training question incorrectly. Finally, we found that training improved student self-reported proficiency and that belief in the importance of the learned domain improved the effectiveness of training. Overall, we found that computer based training with static question sequences and immediate elaborated feedback in the form of simple and general explanations can be an effective way to improve student performance on a physics essential skill, especially for less prepared and low-performing students.

[1]  Jose P. Mestre,et al.  Impact of a short intervention on novices’ categorization criteria , 2012 .

[2]  R. Snow,et al.  Lecture 2: Toward a Theory of Cognitive Aptitude for Learning from Instruction , 1984 .

[3]  V. Shute Focus on Formative Feedback , 2007 .

[4]  A. Kluger,et al.  The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. , 1996 .

[5]  Gary D. Phye,et al.  Feedback Complexity and Practice: Response Pattern Analysis in Retention and Transfer. , 1989 .

[6]  Chen-Lin C. Kulik,et al.  Effectiveness of computer-based instruction: An updated analysis. , 1991 .

[7]  Chen-Lin C. Kulik,et al.  The Instructional Effect of Feedback in Test-Like Events , 1991 .

[8]  Herbert J. Walberg,et al.  Comparative Effects of Computer-Assisted Instruction: A Synthesis of Reviews , 1987 .

[9]  K. VanLehn,et al.  Why Do Only Some Events Cause Learning During Human Tutoring? , 2003 .

[10]  Eric Brewe,et al.  Exploring the relationship between self‐efficacy and retention in introductory physics , 2012 .

[11]  Fabienne M. Van der Kleij,et al.  Effects of Feedback in a Computer-Based Learning Environment on Students’ Learning Outcomes , 2013 .

[12]  Z. Križan,et al.  Do People Have Insight Into Their Abilities? A Metasynthesis , 2014, Perspectives on psychological science : a journal of the Association for Psychological Science.

[13]  Andrew F. Heckler,et al.  Adding and subtracting vectors: The problem with the arrow representation , 2015 .

[14]  Philip C. Abrami,et al.  What Forty Years of Research Says About the Impact of Technology on Learning , 2011 .

[15]  Raymond W. Kulhavy,et al.  Feedback complexity and corrective efficiency , 1985 .

[16]  Slava Kalyuga Expertise Reversal Effect and Its Implications for Learner-Tailored Instruction , 2007 .

[17]  E. Mory Feedback research revisited. , 2004 .

[18]  Genaro Zavala,et al.  Test of understanding of vectors: A reliable multiple-choice vector concept test , 2014 .

[19]  James A. Kulik,et al.  Integrating Findings from Different Levels of Instruction. , 1981 .

[20]  W. J. Roper Feedback in Computer Assisted Instruction , 1977 .

[21]  Robert W. Roeser,et al.  Cognitive Abilities and Motivational Processes in High School Students' Situational Engagement and Achievement in Science , 2002, Special Issue: A Multidimensional Approach to Achievement Validation.

[22]  Bernard P. Veldkamp,et al.  Effects of feedback in a computer-based assessment for learning , 2012, Comput. Educ..

[23]  Robert J. Crutcher,et al.  The role of deliberate practice in the acquisition of expert performance. , 1993 .

[24]  Marci S. DeCaro,et al.  The Effects of Feedback During Exploratory Mathematics Problem Solving: Prior Knowledge Matters , 2012 .

[25]  Susanne Narciss,et al.  How to design informative tutoring feedback for multi-media learning , 2004 .

[26]  JudithAnn R. Hartman,et al.  “Do we need to memorize that?” or cognitive science for chemists , 2015 .

[27]  Larry Ambrose,et al.  The power of feedback. , 2002, Healthcare executive.

[28]  Manu Kapur Productive Failure , 2006, ICLS.

[29]  Herbert J. Walberg,et al.  The effects of computers on learning , 1992 .

[30]  R. G. Duncan,et al.  Beyond the fringe: Building and evaluating scientific knowledge systems , 2009 .

[31]  Andrew F. Heckler,et al.  The effectiveness of brief, spaced practice on student difficulties with basic and essential engineering skills , 2013, 2013 IEEE Frontiers in Education Conference (FIE).

[32]  John Hattie,et al.  INSTRUCTION BASED ON FEEDBACK , 2010 .

[33]  Wim J. Nijhof,et al.  Effects of complex feedback on computer-assisted modular instruction , 2002, Comput. Educ..

[34]  Paul A. Kirschner,et al.  Ten Steps to Complex Learning: A Systematic Approach to Four-Component Instructional Design , 2007 .

[35]  D. Gilman Comparison of Several Feedback Methods for Correcting Errors by Computer-Assisted Instruction. , 1969 .

[36]  J. Sweller,et al.  Cognitive Load Theory and Complex Learning: Recent Developments and Future Directions , 2005 .

[37]  Gary E. Gladding,et al.  Clinical Study of Student Learning Using Mastery Style versus Immediate Feedback Online Activities. , 2015 .

[38]  R. D. Knight,et al.  The vector knowledge of beginning physics students , 1995 .